# Refolk

> Refolk is a people search engine. Headhunting and prospecting in plain English. Ask for the people you want and get them back, every time, across GitHub, LinkedIn, and the open web.

Ask for people the way you'd ask a colleague ("staff engineers in Berlin who maintain popular Rust crates") and I'll return a ranked list of real people with the evidence behind each match. Results draw on public GitHub activity, public LinkedIn and Crunchbase records, and the open web.

Key entry points: the landing page has a live demo, and every published search below is a real query with its full result list.

## Product
- [Refolk - find anyone, just ask](https://www.refolk.ai/): Landing page with a live search demo.
- [How Refolk works](https://www.refolk.ai/how-it-works): The full pipeline: query planning, live reads of public sources, and ranking with the evidence shown.
- [Guides](https://www.refolk.ai/guides): Plain-English explainers on people search, sourcing, and how the tools compare.
- [Docs](https://www.refolk.ai/docs): Canonical answers about the product: what it is, how search works, data sources, credits, privacy.
- [Support](https://www.refolk.ai/support): How to get help: the one support address, hello@refolk.ai, plus credits, applications that stopped, data removal, and account deletion.
- [Developers](https://www.refolk.ai/developers): The API and the MCP server: run the same two searches from your own code, or from any assistant that speaks MCP.
- [Published searches](https://www.refolk.ai/s): Real searches people ran, published with their full results.
- [Blog](https://www.refolk.ai/blog): Guides on headhunting, prospecting, and people search.
- [Open-source repositories](https://www.refolk.ai/repos): Trending and notable GitHub repositories, browsable by language and topic.
- [Company lists](https://www.refolk.ai/companies): Curated startup and company lists by industry, location, funding stage, and investor.

## For candidates

> Refolk also works the other way round. A job seeker pastes their career history once; I write the resume, rewrite it for every posting they apply to, draft the cover letter, and score how well they actually fit.

- [For candidates](https://www.refolk.ai/candidates): Landing page for the job-seeker product.
- [Candidate docs](https://www.refolk.ai/candidates/docs): Canonical answers about the job-seeker product: profile intake, resumes, job matches, tailoring and fit scores, what it costs, privacy.
- [Auto apply to jobs](https://www.refolk.ai/candidates/auto-apply): How automated applications work here: a tailored resume and cover letter per posting, an honest fit score, and the submit step you still do yourself.
- [Resume generator](https://www.refolk.ai/candidates/ai-resume): Resumes generated from a candidate's own history rather than a template, by role.
- [Job search guides](https://www.refolk.ai/candidates/guides): Long reference documents on running a job search: materials, applying at volume, interviewing, and negotiating.
- [Job search guide index (Markdown)](https://www.refolk.ai/candidates/guides/index.md): Every job-search guide in one plain-Markdown file.
- [Job search blog](https://www.refolk.ai/candidates/blog): Timely writing for people looking for work right now.
- [Resume guides by role](https://www.refolk.ai/candidates/resume): What a resume has to prove, per role. 174 roles covered.
- [Resume examples by role](https://www.refolk.ai/candidates/resume-examples): A complete worked sample resume per role, with each bullet explained and the weak version it replaced. 174 roles covered.
- [Resume templates](https://www.refolk.ai/candidates/resume-templates): Resume formats compared: section order, who each suits, and how each behaves in an applicant tracking system.
- [Cover letter guides by role](https://www.refolk.ai/candidates/cover-letter): The argument a cover letter should make, per role.
- [Interview prep by role](https://www.refolk.ai/candidates/interview): What interviews test, per role, and how to prepare evidence for it.
- [Jobs by role and city](https://www.refolk.ai/candidates/jobs): How the market works for a role in a given city, and where openings are actually posted.
- [Free resume builder](https://www.refolk.ai/candidates/free-resume-builder): Build a resume free from your own career history. No card, no watermark, and no paywall between you and the finished file.
- [ATS resume checker](https://www.refolk.ai/candidates/ats-resume-checker): What an applicant tracking system actually does with your resume, the eight mechanical checks worth running before you send it, and why most match scores are theatre.
- [Apply GPT](https://www.refolk.ai/candidates/apply-gpt): What people mean by an apply GPT, a prompt that genuinely works in a chat window, the four places chat stops scaling, and what a purpose-built application engine does instead.
- [Cover letter generator](https://www.refolk.ai/candidates/ai-cover-letter-generator): Generate a cover letter per posting from your own history rather than a template. What makes generated letters read as generated, and the structure that avoids it.
- [Application tracker](https://www.refolk.ai/candidates/job-application-tracker): Track every application through queued, ready, submitted, interviewing, and offer, without a spreadsheet you abandon in week two. Rows are created when the application is written.
- [Chrome extension](https://www.refolk.ai/candidates/chrome-extension): A Chrome extension that fills a job application in from the resume, cover letter, and answers already written for that exact posting, then stops at the employer's own submit button. Free, no card.

## Job search guides
- [The Live Coding Round, Run From Shared Pad to a Tested Solution](https://www.refolk.ai/candidates/guides/live-coding-round-shared-pad): Run a 45-minute live coding interview in a shared browser editor end to end, with a phase budget, narration cadence, and a stall recovery that is scored.
  - [Markdown](https://www.refolk.ai/candidates/guides/live-coding-round-shared-pad.md)
- [The Stretch-Skill Claim, Scored Per Posting to Claim, Qualify, or Hold](https://www.refolk.ai/candidates/guides/stretch-skill-claim-score): A per-posting method to score any required skill you only partly have, so you know whether to claim it, qualify it, or hold it before you submit.
  - [Markdown](https://www.refolk.ai/candidates/guides/stretch-skill-claim-score.md)
- [The Layoff-Risk Read, One Employer From WARN Filings to a Verdict](https://www.refolk.ai/candidates/guides/layoff-risk-read-warn-filings): Pull one target employer's public WARN layoff-notice trail across states, count what matters, corroborate it, and reach a documented apply, watch, or avoid verdict.
  - [Markdown](https://www.refolk.ai/candidates/guides/layoff-risk-read-warn-filings.md)
- [The Panel Interview, Run From Panelist Map to Individual Follow-Ups](https://www.refolk.ai/candidates/guides/panel-interview-panelist-map): Prepare and run a multi-interviewer panel with a per-seat coverage plan, attention-allocation sequence, interruption scripts, and individualized thank-yous.
  - [Markdown](https://www.refolk.ai/candidates/guides/panel-interview-panelist-map.md)
- [The One-Link Work Sample Portfolio for Non-Portfolio Roles](https://www.refolk.ai/candidates/guides/one-link-work-sample-portfolio): A step-by-step method to turn spreadsheets, decks, and process docs into three to five sanitized work samples behind one shareable link, with no website needed.
  - [Markdown](https://www.refolk.ai/candidates/guides/one-link-work-sample-portfolio.md)
- [The Field-Switch Informational Interview Run, From Target List to a Referral](https://www.refolk.ai/candidates/guides/field-switch-informational-interview-run): Run a weekly campaign of informational interviews in a field you have never worked in, from target list to a referral, with volumes, scripts, and a tracked path.
  - [Markdown](https://www.refolk.ai/candidates/guides/field-switch-informational-interview-run.md)
- [The Forfeited-Pay Make-Whole, One Vesting Schedule to a Signed Sign-On](https://www.refolk.ai/candidates/guides/forfeited-pay-make-whole): Convert one vesting schedule and a pending bonus into a defensible forgone-pay figure, then win a make-whole sign-on whose clawback cannot re-trap you.
  - [Markdown](https://www.refolk.ai/candidates/guides/forfeited-pay-make-whole.md)
- [The AI-Exposure Read, Scored to Hold, Specialize, or Pivot](https://www.refolk.ai/candidates/guides/ai-exposure-read-score): Score your own occupation on five weighted signals from named public datasets, then convert the score into a decision to hold your target, specialize, or pivot.
  - [Markdown](https://www.refolk.ai/candidates/guides/ai-exposure-read-score.md)
- [The Rescinded-Offer Recovery, From Pulled Letter to a Restarted Search](https://www.refolk.ai/candidates/guides/rescinded-offer-recovery-playbook-2): A two-week, day-by-day recovery sequence after a job offer is rescinded, including the un-resign ask, FCRA rights, reopening unemployment, and restarting outreach.
  - [Markdown](https://www.refolk.ai/candidates/guides/rescinded-offer-recovery-playbook-2.md)
- [The Two-Plan Health Cost Teardown, Two SBCs to a Yearly Number](https://www.refolk.ai/candidates/guides/two-plan-health-cost-teardown): Carry two Summary of Benefits and Coverage documents through premiums, deductible, coinsurance, and employer HSA money to three annual numbers and a decision.
  - [Markdown](https://www.refolk.ai/candidates/guides/two-plan-health-cost-teardown.md)
- [The Tailoring Effort Score, From Posting to a Ten-Minute or Hour Call](https://www.refolk.ai/candidates/guides/tailoring-effort-score): A scoring framework to decide, per posting, whether a job application deserves a ten-minute pass or a full hour of tailoring. Built for high-volume searches.
  - [Markdown](https://www.refolk.ai/candidates/guides/tailoring-effort-score.md)
- [The 30-60-90 Day Plan, From Posting to a Defended Presentation](https://www.refolk.ai/candidates/guides/thirty-sixty-ninety-plan-defended): Turn a job posting into a 30-60-90 day plan with phase goals specific enough to survive live follow-up questions, and present it without overpromising. A build-and-defend method.
  - [Markdown](https://www.refolk.ai/candidates/guides/thirty-sixty-ninety-plan-defended.md)
- [The Foreign-Degree Recognition Run, From Transcript to a Usable Equivalency](https://www.refolk.ai/candidates/guides/foreign-degree-recognition-run): Decide if you need a credential evaluation, order the right report type from an evaluator the target accepts, and state the equivalency so degree screens clear.
  - [Markdown](https://www.refolk.ai/candidates/guides/foreign-degree-recognition-run.md)
- [The Confidential-Work Portfolio Piece, Scored to Show, Sanitize, or Omit](https://www.refolk.ai/candidates/guides/confidential-work-portfolio-piece): A scoring framework for putting NDA-bound or proprietary projects in your portfolio: read what the agreement blocks, pick a compliant treatment, attach a disclosure line.
  - [Markdown](https://www.refolk.ai/candidates/guides/confidential-work-portfolio-piece.md)
- [The Military-to-Civilian Resume, One Service Record Carried to a Draft](https://www.refolk.ai/candidates/guides/military-to-civilian-resume-worked): Turn a DD-214 and evaluations into a civilian resume an ATS and a non-military manager can both read, carried through every translation fork with the wrong turns.
  - [Markdown](https://www.refolk.ai/candidates/guides/military-to-civilian-resume-worked.md)
- [The Sole-Offer Counter, From Written Offer to a Signed Increase](https://www.refolk.ai/candidates/guides/sole-offer-counter-signed-increase): Run a single-offer salary negotiation with no competing offer, from the written offer to a signed increase, using market data and a concession ladder.
  - [Markdown](https://www.refolk.ai/candidates/guides/sole-offer-counter-signed-increase.md)
- [The Switch-Premium Score, to Search Now, Hold, or Press Internally](https://www.refolk.ai/candidates/guides/switch-premium-score): Estimate your field's current job-switcher wage gap, convert any offer into a net comparable number, and score whether to search now, hold, or press for a raise.
  - [Markdown](https://www.refolk.ai/candidates/guides/switch-premium-score.md)
- [The Working Interview, Run From Trial Invite to an Offer Decision](https://www.refolk.ai/candidates/guides/working-interview-trial-playbook): Run a working interview or paid trial from accepting terms to an offer: lock scope and pay in writing, check your wage rights, perform, and convert or walk away.
  - [Markdown](https://www.refolk.ai/candidates/guides/working-interview-trial-playbook.md)
- [The Search-Tracking Standard, and the Minimum Record That Passes](https://www.refolk.ai/candidates/guides/search-tracking-standard-minimum-record): Grade your job-search tracker pass or fail against a fixed minimum field set and upkeep rule, so every live application has a named next action.
  - [Markdown](https://www.refolk.ai/candidates/guides/search-tracking-standard-minimum-record.md)
- [The Application Portal Reference, One Row per ATS You Clear](https://www.refolk.ai/candidates/guides/application-portal-ats-reference): Identify which ATS a job posting runs on, predict which fields it forces you to re-enter, and clear each portal's form by the shortest safe path.
  - [Markdown](https://www.refolk.ai/candidates/guides/application-portal-ats-reference.md)
- [The Remote-Arrangement Clause, From Verbal Promise to Signed Offer](https://www.refolk.ai/candidates/guides/remote-arrangement-clause-offer-letter): Convert a verbal remote or hybrid promise into binding offer-letter language or a signed addendum, with the exact terms a clause must name to hold.
  - [Markdown](https://www.refolk.ai/candidates/guides/remote-arrangement-clause-offer-letter.md)
- [The Visa Sponsorship Target List, From Disclosure Data to a Ranked Shortlist](https://www.refolk.ai/candidates/guides/visa-sponsorship-target-list): Turn your visa status and target role into a ranked, verified shortlist of employers whose filing history and per-role sponsorship math support an application.
  - [Markdown](https://www.refolk.ai/candidates/guides/visa-sponsorship-target-list.md)
- [The Competing-Offer Leverage Play, From a Second Offer to a Raised Package](https://www.refolk.ai/candidates/guides/competing-offer-leverage-play): Run the full sequence to turn a real second written offer into a higher package on the job you actually want, with both offers still intact. The exact procedure.
  - [Markdown](https://www.refolk.ai/candidates/guides/competing-offer-leverage-play.md)
- [The Severance Counter, From Offered Package to a Signed Improvement](https://www.refolk.ai/candidates/guides/severance-counter-playbook): Run a severance counter end to end after a layoff: calculate your review and revocation clocks, pick components to push, and carry an anchored written counter to signed terms.
  - [Markdown](https://www.refolk.ai/candidates/guides/severance-counter-playbook.md)
- [The No-Contact Referral Run, From a Cold Posting to Replied Asks](https://www.refolk.ai/candidates/guides/no-contact-referral-run): A step-by-step method to turn a posting at a company where you know no one into a submitted referral, with contact order, reply cadence, and a stop rule.
  - [Markdown](https://www.refolk.ai/candidates/guides/no-contact-referral-run.md)
- [The Field Hiring Calendar, Paced From Posting Counts to Your Search](https://www.refolk.ai/candidates/guides/field-hiring-calendar-posting-counts): Build a month-by-month hiring calendar for your exact role and metro from public posting counts, then pace applications, networking, and prep to its peaks and lulls.
  - [Markdown](https://www.refolk.ai/candidates/guides/field-hiring-calendar-posting-counts.md)
- [The Pay-Talk Readiness Standard, Graded Before the Question Lands](https://www.refolk.ai/candidates/guides/pay-talk-readiness-standard): Grade your salary-expectations prep pass or fail against shared criteria before any interview, so you never improvise a compensation number live.
  - [Markdown](https://www.refolk.ai/candidates/guides/pay-talk-readiness-standard.md)
- [The Band-Floor Resume, Reworked Line by Line to the Top of Its Range](https://www.refolk.ai/candidates/guides/band-floor-resume-reworked-line-by-line): Rework a resume that keeps getting priced at the bottom of the band, line by line, into a defensible top-third read without crossing into inflated or mislevel claims.
  - [Markdown](https://www.refolk.ai/candidates/guides/band-floor-resume-reworked-line-by-line.md)
- [The Conversational AI Voice Screen, From Invite Link to a Finished Transcript](https://www.refolk.ai/candidates/guides/conversational-ai-voice-screen): A stage-by-stage method to run a live AI voice interview end to end, from verifying the invite to closing a transcript that scores high enough to reach a human.
  - [Markdown](https://www.refolk.ai/candidates/guides/conversational-ai-voice-screen.md)
- [The Padded-Range Batch, Posted Spreads Read to a Real Floor](https://www.refolk.ai/candidates/guides/padded-range-batch-real-floor): Take a batch of job postings with wildly different salary ranges, compute the spread, flag padding and multi-level reqs, and rank your apply order by real floor.
  - [Markdown](https://www.refolk.ai/candidates/guides/padded-range-batch-real-floor.md)
- [The Transition Search Runway Standard, and What Fails a Pass](https://www.refolk.ai/candidates/guides/transition-search-runway-standard): Grade whether your career-change, re-entry, or post-layoff search is funded to outlast its realistic duration, and know the exact lever to pull if it fails.
  - [Markdown](https://www.refolk.ai/candidates/guides/transition-search-runway-standard.md)
- [The Hiring Manager Screen, From Handoff to a Loop Invite](https://www.refolk.ai/candidates/guides/hiring-manager-screen-to-loop): Prepare for and run the first call with your future boss so it converts into a full interview loop invite, with round-specific criteria and a read on whether you advanced.
  - [Markdown](https://www.refolk.ai/candidates/guides/hiring-manager-screen-to-loop.md)
- [The Demand-Sourced Resume, From Posting Frequency to a Finished Draft](https://www.refolk.ai/candidates/guides/demand-sourced-resume-skills): Rebuild your resume from real posting demand: pull the signals, classify skills, and place each as a defensible bullet or ATS keyword. The full procedure.
  - [Markdown](https://www.refolk.ai/candidates/guides/demand-sourced-resume-skills.md)
- [The Candidate Back-Channel Standard, Graded Before You Sign](https://www.refolk.ai/candidates/guides/candidate-back-channel-standard): A gradeable bar for vetting an employer through off-the-record calls, so you can label your vet complete, insufficient, or blocked before you sign the offer.
  - [Markdown](https://www.refolk.ai/candidates/guides/candidate-back-channel-standard.md)
- [The Band-Consistent Materials Standard, Graded Before You Publish](https://www.refolk.ai/candidates/guides/band-consistent-materials-standard): A pass or fail rubric for grading every pay signal in your resume and profile, so you can find the exact line anchoring you low or pricing you out.
  - [Markdown](https://www.refolk.ai/candidates/guides/band-consistent-materials-standard.md)
- [The Salary-Expectations Answer Kit, Built Once to Deploy Across a Batch](https://www.refolk.ai/candidates/guides/salary-expectations-answer-kit): Build a floor, target, and stretch figure set plus per-field entry rules once, so a batch of applications gives every pay field a consistent, ATS-safe answer.
  - [Markdown](https://www.refolk.ai/candidates/guides/salary-expectations-answer-kit.md)
- [The Internal Transfer Playbook, From Posting to a Landed Move](https://www.refolk.ai/candidates/guides/internal-transfer-playbook): Run an internal transfer end to end: clear the eligibility gates, time the manager conversation, line up an advocate, apply, and recover cleanly if denied.
  - [Markdown](https://www.refolk.ai/candidates/guides/internal-transfer-playbook.md)
- [The One-Way Video Interview, From Invite Link to Submitted Recordings](https://www.refolk.ai/candidates/guides/one-way-video-interview-procedure): Run an asynchronous video interview end to end: read the spec, rehearse to the clock, use the prep countdown, spend retakes well, and submit before the deadline.
  - [Markdown](https://www.refolk.ai/candidates/guides/one-way-video-interview-procedure.md)
- [The Normal-Loop Standard, Graded Against Market Thresholds by Role Class](https://www.refolk.ai/candidates/guides/normal-loop-standard-by-role): Grade any interview loop pass or fail against documented market thresholds for round count, hours, and stage gaps, then name exactly which criterion a broken process fails.
  - [Markdown](https://www.refolk.ai/candidates/guides/normal-loop-standard-by-role.md)
- [The Pre-Check Resume Line, Scored to Fix, Disclose, or Hold](https://www.refolk.ai/candidates/guides/resume-line-fix-disclose-hold): Score any resume or application line for background-check risk and route it to correct, disclose, or hold before the verification runs against your contingent offer.
  - [Markdown](https://www.refolk.ai/candidates/guides/resume-line-fix-disclose-hold.md)
- [The Resume File and Delivery Reference, One Row per Format and Channel](https://www.refolk.ai/candidates/guides/resume-file-delivery-reference): Decide which resume file format and filename to send through each submission channel so it parses cleanly and reads well, one lookup row at a time.
  - [Markdown](https://www.refolk.ai/candidates/guides/resume-file-delivery-reference.md)
- [The Field-Switch Resume, From Old-Field History to a New-Field Draft](https://www.refolk.ai/candidates/guides/field-switch-resume-build): Build a hybrid career change resume end to end: extract old-field history, map a target-posting skills matrix, and ship a parse-verified new-field draft.
  - [Markdown](https://www.refolk.ai/candidates/guides/field-switch-resume-build.md)
- [The Blend-In Interview, One Answer Set Repositioned to a Single Thread](https://www.refolk.ai/candidates/guides/blend-in-interview-one-thread): Rewrite flat, interchangeable interview answers around one selling thread so each reads as distinct, evaluable signal instead of a canned response.
  - [Markdown](https://www.refolk.ai/candidates/guides/blend-in-interview-one-thread.md)
- [The Interview-Defensible Resume Standard, Graded Line by Line](https://www.refolk.ai/candidates/guides/interview-defensible-resume-standard-2): Grade the exact resume the interviewer holds line by line, pass or fail on defensibility, and know which lines to re-anchor, rewrite, or cut before the loop.
  - [Markdown](https://www.refolk.ai/candidates/guides/interview-defensible-resume-standard-2.md)
- [The Open-Floor Prompt Reference, One Row per Invitation to Sell Yourself](https://www.refolk.ai/candidates/guides/open-floor-prompt-reference): Identify any open-floor interview prompt by its phrasing, name what it tests, and route the matching slice of your positioning thesis without repeating yourself.
  - [Markdown](https://www.refolk.ai/candidates/guides/open-floor-prompt-reference.md)
- [The Recruiter-Screen Cluster, One Week of Calls Kept Distinct](https://www.refolk.ai/candidates/guides/recruiter-screen-cluster-one-week): Run a week of back-to-back recruiter screens without blending companies, using a per-call prep sheet, spaced calls, and a log filled within five minutes.
  - [Markdown](https://www.refolk.ai/candidates/guides/recruiter-screen-cluster-one-week.md)
- [The Resume-to-Records Reconciliation, Run Before the Background Check](https://www.refolk.ai/candidates/guides/resume-records-reconciliation): Reconcile your resume, your background-check form, and your payroll records the week a conditional offer lands, so verification clears without a discrepancy flag.
  - [Markdown](https://www.refolk.ai/candidates/guides/resume-records-reconciliation.md)
- [The Career-Switch Interview Case Standard, Graded Before the Loop](https://www.refolk.ai/candidates/guides/career-switch-interview-case-standard): A pass or fail rubric that grades your career-switch interview case on every concern a hiring manager tests, so you fix the weak element before round one.
  - [Markdown](https://www.refolk.ai/candidates/guides/career-switch-interview-case-standard.md)
- [The Hiring Momentum Score, to Prioritize, Watch, or Skip One Company](https://www.refolk.ai/candidates/guides/hiring-momentum-score-company): Score whether one target company is expanding, holding, or contracting hiring in your function from public data, then decide to prioritize, watch, or skip it.
  - [Markdown](https://www.refolk.ai/candidates/guides/hiring-momentum-score-company.md)
- [The Live-Loop Target, Sized From Market Interview-to-Offer Rates](https://www.refolk.ai/candidates/guides/live-loop-target-offer-math): Compute how many concurrent interview loops and feeder applications you need to land one accepted offer by your deadline, adjusted for role and sector.
  - [Markdown](https://www.refolk.ai/candidates/guides/live-loop-target-offer-math.md)
- [The Resume Claim and Its Source of Record, Field by Field](https://www.refolk.ai/candidates/guides/resume-claim-source-of-record): Map each resume field to the record a verifier pulls, what that source returns, and where an honest claim diverges, so you certify the background form without a flag.
  - [Markdown](https://www.refolk.ai/candidates/guides/resume-claim-source-of-record.md)
- [The Overqualified Objection, Carried Through One Downshift Loop](https://www.refolk.ai/candidates/guides/overqualified-downshift-loop): A round-by-round method for the overqualified objection when applying for a lower level job, retiring cost, flight risk, and boredom fears in order.
  - [Markdown](https://www.refolk.ai/candidates/guides/overqualified-downshift-loop.md)
- [The Reference Panel, Chosen and Coached Before Anyone Gets Called](https://www.refolk.ai/candidates/guides/reference-panel-chosen-and-coached): Select, sequence, and brief a reference panel and manage backchannel exposure so every likely call reinforces one narrative before your offer lands.
  - [Markdown](https://www.refolk.ai/candidates/guides/reference-panel-chosen-and-coached.md)
- [The Behavioral Answer Standard, Graded Before You Speak It](https://www.refolk.ai/candidates/guides/behavioral-answer-standard-graded): Grade one prepared behavioral interview answer pass or fail on the dimensions interviewers score, find the one fault that caps it, and know what to rebuild.
  - [Markdown](https://www.refolk.ai/candidates/guides/behavioral-answer-standard-graded.md)
- [The Warm-Referral Run, From Target Postings to Submitted Referrals](https://www.refolk.ai/candidates/guides/warm-referral-run): Run referrals as a channel across your whole target list: map each posting to an insider, sequence the ask, and track follow-ups so no referral slips.
  - [Markdown](https://www.refolk.ai/candidates/guides/warm-referral-run.md)
- [The Screen-Anchored Pay Number, Traced to the Offer](https://www.refolk.ai/candidates/guides/trace-salary-number-to-offer): Trace how a salary number you gave on the recruiter screen travels to the offer, spot where it hardens, and run the reset script before it locks.
  - [Markdown](https://www.refolk.ai/candidates/guides/trace-salary-number-to-offer.md)
- [The Post-Offer Approver Interview, Carried to a Written Yes](https://www.refolk.ai/candidates/guides/post-offer-approver-interview): Run the late-stage sign-off call with a VP who never interviewed you as the live evaluation it is, and convert it into a signed offer instead of a rescind.
  - [Markdown](https://www.refolk.ai/candidates/guides/post-offer-approver-interview.md)
- [The Live-Demand Application Batch Standard, and What Fails the Reality Check](https://www.refolk.ai/candidates/guides/live-demand-application-batch-standard): Grade a whole batch of target job postings pass or fail against fixed freshness, repost, and employer-activity thresholds before you spend tailoring hours.
  - [Markdown](https://www.refolk.ai/candidates/guides/live-demand-application-batch-standard.md)
- [The Free-Text Angle, Scored Per Posting to Lead, Support, or Cut](https://www.refolk.ai/candidates/guides/free-text-angle-scored-per-posting): Score each selling point against the posting and the character limit to decide which one leads the application free-text box, which supports, and which gets cut.
  - [Markdown](https://www.refolk.ai/candidates/guides/free-text-angle-scored-per-posting.md)
- [The Parse-Clean Resume Standard, Graded Before the Batch](https://www.refolk.ai/candidates/guides/parse-clean-resume-standard): Grade your master resume pass or fail on every field an ATS must extract, run the extraction test that proves it, and fix each failure before you apply.
  - [Markdown](https://www.refolk.ai/candidates/guides/parse-clean-resume-standard.md)

## Job search blog posts
- [The Dec. 11 Cliff: Rewriting a Federal Contractor Resume Fast](https://www.refolk.ai/candidates/blog/federal-contractor-resume-december-11-cliff): Federal postings are down 30.6% YoY and the next shutdown fight hits Dec. 11, 2026. Here is how to rewrite a federal contractor resume in six weeks.
- [The Nov. 10 Deadline: An H-1B Resume for a Zero-Day Grace Period](https://www.refolk.ai/candidates/blog/h1b-zero-day-grace-period-resume): DHS wants to kill the 60-day H-1B grace period. Here is the pre-layoff resume, LinkedIn, and cap-exempt strategy to be transfer-ready on day zero.
- [The 3:47 AM Rejection: What Mobley v. Workday Means for Resumes 40+](https://www.refolk.ai/candidates/blog/mobley-workday-sub-hour-rejection-resume-playbook): Mobley v. Workday is deep in discovery. Here is how to spot the sub-hour auto-reject, document it, and rewrite the date fields that trigger it.
- [Wells Fargo's 23 WARNs, 650 Jobs: A Resume for AI's Slow Bleed](https://www.refolk.ai/candidates/blog/wells-fargo-warn-west-des-moines-ai-resume): Wells Fargo's 23rd 2026 WARN hits West Des Moines Nov. 28. Here is the 60-day resume playbook for ops workers facing AI-driven cuts.
- [Ninja Theory Resume Guide: Writing a CV for a Game That Won't Ship](https://www.refolk.ai/candidates/blog/ninja-theory-senua-resume-unreleased-game): After Microsoft's Ninja Theory sale attempts collapsed, here is how to write a game developer resume for Senua, an unreleased, possibly cancelled AAA title.
- [Disney's 300-Person HR Cut: The 19-Person Pivot Lane Ex-Recruiters Miss](https://www.refolk.ai/candidates/blog/disney-hr-layoffs-recruiter-resume-pivot): Disney cut 300 HR and tech staff on Sept 30, 2026. Here is the resume pivot ex-recruiters should actually run, with numbers from Refolk's index.
- [How to Spot an Undisclosed AI Interview Before You Record](https://www.refolk.ai/candidates/blog/spot-undisclosed-ai-interview-before-you-record): Greenhouse's 2026 report shows 38% of US candidates have walked over AI interviews. Here's how to spot one from the invite and decide fast.
- [The 2-Week Date Stretch That Fails HireRight in 2026](https://www.refolk.ai/candidates/blog/resume-dates-payroll-background-check-2026): Why a two-week resume date fudge now triggers HireRight's silent Complete Discrepancy flag, and the Equifax audit that catches it first.
- [The 47% Tech Vacancy Gap and Why the 72-Hour Rule Works](https://www.refolk.ai/candidates/blog/72-hour-rule-tech-ghost-jobs-2026): Tech's vacancy-to-hire gap hit 47% in 2026. Here is why applying only to postings under 72 hours old is the cleanest counter-move.
- [LinkedIn's 8-of-10 Rule: Why Keyword Resumes Now Rank Lower](https://www.refolk.ai/candidates/blog/linkedin-semantic-search-resume-2026): LinkedIn's 2026 semantic search and Job Match Score punish keyword-stuffed profiles. Here is the rewrite that ranks under the new model.
- [The 17-to-1 Trap: Why Senior Resumes Lose Junior Roles 4x More](https://www.refolk.ai/candidates/blog/overqualified-resume-rejection-senior-junior-roles): Pin's 500K-rejection study shows "overqualified" kills 13% of junior applications. Here's how to defuse the signal when applying down after a layoff.
- [Oracle's 359 Seattle Cut: The OCI Resume for a Nov. 13 Exit](https://www.refolk.ai/candidates/blog/oracle-359-seattle-oci-resume-november-13): Oracle's 359 Washington layoffs land Nov. 13, 2026. How ex-OCI engineers should rewrite the resume for AWS, Azure, and AI-infra roles.
- [The 196,682-Resume Study: Hidden White Text Gets You Flagged](https://www.refolk.ai/candidates/blog/usenix-196682-resume-prompt-injection-study): A USENIX 2026 study of 196,682 resumes found 90% of hidden content isn't prompt injection, and ATS vendors already catch it. Here's what to do instead.
- [Meta's 4-Month Virtue AI Unwind: The Acqui-Hire Resume Playbook](https://www.refolk.ai/candidates/blog/meta-virtue-ai-acquihire-resume-playbook): Dawn Song, Bo Li, and Sanmi Koyejo got four months inside Meta Superintelligence Labs. Here is the acqui-hire resume that survives it.
- [Amazon's 14,000 Cut: Two Resumes Before the 90-Day Badge Flips](https://www.refolk.ai/candidates/blog/amazon-14000-layoffs-90-day-two-resumes): Amazon cut ~14,000 corporate roles with a 90-day internal clock. Here is the two-track resume playbook for the internal portal and the external market.
- [Nike Pace $1B Cut: The 15-Month Resume Head Start Before 2027](https://www.refolk.ai/candidates/blog/nike-pace-restructuring-resume-head-start-2027): Nike's Pace restructuring hits in 2027. Here's how Beaverton merchandisers, Jordan marketers, and digital PMs rework a resume now, before the glut.
- [Dartmouth Health's 303 Cancelled Reqs: Resume Moves for Orphaned Applicants](https://www.refolk.ai/candidates/blog/dartmouth-health-303-cancelled-reqs-resume): Dartmouth Health cancelled 303 reqs on Sept 15, 2026. Here is how orphaned applicants rewrite the resume to land a surviving role at the same employer.
- [Kaiser's 147 WARN Cut: The Admin Resume Healthcare Still Hires](https://www.refolk.ai/candidates/blog/kaiser-147-warn-healthcare-admin-resume): Kaiser cut 147 California admins the same week health added 55,000 jobs. Here is the resume rewrite that lands you back in-sector fast.
- [Conifer's 1,037 Remote RCM Layoffs: Resume Pivot for Nov. 2](https://www.refolk.ai/candidates/blog/conifer-1037-rcm-resume-pivot-nov-2026): Conifer's Sept. 2 WARN cuts 1,037 remote RCM jobs by Nov. 2. Here is the resume pivot to insourcers, rival vendors, and payers.
- [Trinity Health's 557 Livonia Cut: Two Resumes for a Vendor Layoff](https://www.refolk.ai/candidates/blog/trinity-health-557-livonia-it-layoffs-resume): Trinity Health's 557-person Livonia IT layoff needs two resumes: one for the vendor rebadge, one for the next regulated IT shop.
- [EA's $170M "Efficiencies" Line: The 118x Resume Pivot Out of Gaming](https://www.refolk.ai/candidates/blog/ea-170m-efficiencies-game-dev-resume-pivot): EA's $700M post-LBO cost cut hits game devs after 13,800 industry layoffs in 2026. Here's the resume that pivots Unreal and C++ out of gaming.
- [The 61% Resume: Writing Two Jobs, One Title Into Bullets](https://www.refolk.ai/candidates/blog/two-job-job-resume-korn-ferry-61-percent): Korn Ferry says 61% of workers do more than one role. Here is how to put absorbed scope on a resume without sounding desperate or overemployed.
- [The 29,000-Job Stall: A Resume for the Low-Hire, Low-Fire Trap](https://www.refolk.ai/candidates/blog/29000-job-stall-low-hire-low-fire-resume): September 2026's 29,000-job print froze lateral hiring. Here is how a mid-career resume has to change when quits sit at 1.9% and you are stuck.
- [Amentum's 382 in Hanover: The TS/SCI Resume When the Contract Walks](https://www.refolk.ai/candidates/blog/amentum-382-hanover-ts-sci-resume-contract-transition): Amentum filed three WARN notices in six weeks. Here is how cleared workers rewrite the TS/SCI resume when the contract moves but the mission stays.
- [UPS Driver Choice Round 2: A Resume for 28 Years and 7,500 Slots](https://www.refolk.ai/candidates/blog/ups-driver-choice-round-2-resume-playbook): How a long-tenured UPS driver taking the $150K Driver Choice buyout should rewrite a one-employer resume for FedEx, DSPs, and LTL in 2026.
- [Amazon SPS Round 3: The 7:1 Resume Pivot to Shopify, Not AWS](https://www.refolk.ai/candidates/blog/amazon-sps-layoffs-resume-shopify-marketplace-pivot): Amazon's May 2026 SPS cuts leave catalog and account-health PMs with one bad option (AWS transfer) and one good one. Here is the rewrite.
- [Target's 87 Directors in One Day: The Resume Nobody Wants in 2025](https://www.refolk.ai/candidates/blog/target-87-directors-resume-after-layoff): Target laid off 87 directors in one WARN filing. Here is how to rewrite a top-heavy leadership resume for a market deleting your layer.
- [AssistRx Sand Lake Layoff: The CoAssist Resume Pivot Before 137 More Hit](https://www.refolk.ai/candidates/blog/assistrx-coassist-sand-lake-resume-pivot): AssistRx is cutting 86 at Sand Lake on Nov 30, with 137 more by May 2027. How CoAssist and hub-services workers should rewrite their resume now.
- [PayPal's 251 San Jose Cut: The Resume That Quotes the SEC Filing](https://www.refolk.ai/candidates/blog/paypal-251-san-jose-ai-layoff-resume): PayPal's WARN cut 251 senior roles in San Jose. Here is how directors and staff engineers rewrite the resume using PayPal's own AI language, not restructuring.
- [September's 90,787 Floor: The Q4 Resume That Skips Seasonal](https://www.refolk.ai/candidates/blog/september-2026-hiring-low-q4-resume-strategy): September 2026 hiring plans hit a 15-year low at 90,787. Here is where Q4 postings actually sit and how to retarget a resume this week.

## Guides
- [Guide library index (Markdown)](https://www.refolk.ai/guides/index.md): Every guide in one plain-Markdown file, each entry linking the page and its .md mirror.
- [What is a people search engine?](https://www.refolk.ai/guides/what-is-people-search): A plain-English guide to people search engines: what they are, how they work, what they're used for, and how AI changed them.
  - [Markdown](https://www.refolk.ai/guides/what-is-people-search.md)
- [The AI-Inferred Field Standard: Trust, Flag, or Reject](https://www.refolk.ai/guides/ai-inferred-field-standard): A field-by-field pass/fail standard for deciding which AI-inferred CRM fields you can auto-write, which to hold for human review, and which to reject.
  - [Markdown](https://www.refolk.ai/guides/ai-inferred-field-standard.md)
- [The Candidate-Scoring Tool Clearance Standard: Deploy, Restrict, or Hold](https://www.refolk.ai/guides/candidate-scoring-tool-clearance-standard): Grade any AI candidate-ranking tool against NYC, Illinois, Colorado, and EU rules and return a defensible deploy, restrict, or hold verdict before first use.
  - [Markdown](https://www.refolk.ai/guides/candidate-scoring-tool-clearance-standard.md)
- [The First-in-Function Signal: Build a Ranked Greenfield Queue](https://www.refolk.ai/guides/first-in-function-greenfield-queue): Detect when a company stands up a function for the first time, separate it from a backfill or dormant reopen, and build a ranked outreach queue timed to the first 90 days.
  - [Markdown](https://www.refolk.ai/guides/first-in-function-greenfield-queue.md)
- [Sourcing Return-to-Work Candidates From Public Signals](https://www.refolk.ai/guides/sourcing-return-to-work-candidates): A recruiter's procedure for finding, qualifying, and ranking return-to-work candidates from public career-history signals, tied to one open role without penalizing the gap.
  - [Markdown](https://www.refolk.ai/guides/sourcing-return-to-work-candidates.md)
- [The Kaggle Profile Read: Applied Skill, Contest Overfit, or Noise](https://www.refolk.ai/guides/kaggle-profile-read-hiring): Score a data-science candidate's Kaggle profile across its four categories, discount upvote-farmed and overfit tiers, and land a defensible hiring verdict.
  - [Markdown](https://www.refolk.ai/guides/kaggle-profile-read-hiring.md)
- [Sourcing Academic Founders Before They Leave the Lab](https://www.refolk.ai/guides/sourcing-academic-founders-pre-spinout): Turn a target field or lab set into a ranked, contact-ready watchlist of pre-incorporation academic founders, each tagged with its public signal and outreach window.
  - [Markdown](https://www.refolk.ai/guides/sourcing-academic-founders-pre-spinout.md)
- [Reading a Competitor's Next Build From Open Reqs and Exits](https://www.refolk.ai/guides/competitor-next-build-reqs-exits): Carry one competitor from a raw req pull to a dated, evidence-cited hypothesis of its next move, pairing roles coming in with people going out to separate a net-new team from churn.
  - [Markdown](https://www.refolk.ai/guides/competitor-next-build-reqs-exits.md)
- [The Talent Map Playbook: Target Companies to a Named Pool](https://www.refolk.ai/guides/talent-map-playbook-named-pool): Build a reusable talent map for one role family before the req opens: tiered source companies, named candidates, a documented coverage figure, and a refresh cadence.
  - [Markdown](https://www.refolk.ai/guides/talent-map-playbook-named-pool.md)
- [The Jurisdiction Reference for Lawful Sourcing and First Contact](https://www.refolk.ai/guides/jurisdiction-reference-lawful-sourcing): Decide per recipient country whether you may source public data and send a first message, under which lawful basis, with which mandatory elements and penalties.
  - [Markdown](https://www.refolk.ai/guides/jurisdiction-reference-lawful-sourcing.md)
- [The Signup-to-Account Queue: Rolling Scattered PLG Signups Into Ranked PQAs](https://www.refolk.ai/guides/signup-to-account-queue): Turn a raw export of individual free-product signups into a deduplicated, ranked product-qualified-account queue for AEs, with do-not-touch rules that protect self-serve conversion.
  - [Markdown](https://www.refolk.ai/guides/signup-to-account-queue.md)
- [The Retention-Clock Reference: How Long to Keep Each Sourced Record](https://www.refolk.ai/guides/sourced-record-retention-clock-reference): Look up any sourced candidate record by type, lawful basis, and jurisdiction, then set a defensible retention period with a named clock-start event. A reference.
  - [Markdown](https://www.refolk.ai/guides/sourced-record-retention-clock-reference.md)
- [The Competitor Weakness Map: Mining Public Reviews Into Ranked Evidence](https://www.refolk.ai/guides/competitor-weakness-map-from-reviews): A research method to turn scattered public competitor reviews into a ranked, dated, evidence-backed weakness map that retires itself when a changelog fixes it.
  - [Markdown](https://www.refolk.ai/guides/competitor-weakness-map-from-reviews.md)
- [The Deal Qualification Score: Commit, Work the Gaps, or Walk](https://www.refolk.ai/guides/deal-qualification-score): Grade any open deal across eight qualification checks on one evidence scale, verify weak checks against public signals, and reach an auditable forecast verdict.
  - [Markdown](https://www.refolk.ai/guides/deal-qualification-score.md)
- [From Conference Agenda to a Ranked Candidate Shortlist](https://www.refolk.ai/guides/conference-agenda-to-shortlist): A step-by-step method to turn one conference speaker agenda into a deduplicated, seniority-inferred, ranked shortlist with a contact path per person.
  - [Markdown](https://www.refolk.ai/guides/conference-agenda-to-shortlist.md)
- [The Database-Health Metric Reference: Formula, Benchmark, Blind Spot](https://www.refolk.ai/guides/database-health-metric-reference): Define every data-quality metric for a sourced people-and-company database with one formula, a benchmark, and the failure mode that makes the number lie.
  - [Markdown](https://www.refolk.ai/guides/database-health-metric-reference.md)
- [The Vulnerability-Disclosure Read: Deep Skill, Padded, or Noise](https://www.refolk.ai/guides/vulnerability-disclosure-hiring-read): Score a security candidate's CVE credits, advisory acknowledgments, and bug-bounty profile across defined dimensions and land on a defensible hiring verdict.
  - [Markdown](https://www.refolk.ai/guides/vulnerability-disclosure-hiring-read.md)
- [Tracing a Claimed Founder Exit to the Real Outcome](https://www.refolk.ai/guides/tracing-claimed-founder-exit): A forensic trail for turning a founder's "founded X, exited for $Y" deck line into a documented verdict on the real sale, the role, and personal proceeds.
  - [Markdown](https://www.refolk.ai/guides/tracing-claimed-founder-exit.md)
- [The Pre-Call Brief: Booked Meeting to Call-Ready Facts in One Page](https://www.refolk.ai/guides/pre-call-brief-one-page): Turn a booked discovery call into a one-page, source-traced brief in under 15 minutes, with every fact labeled by source and freshness so nothing stale reaches the call.
  - [Markdown](https://www.refolk.ai/guides/pre-call-brief-one-page.md)
- [The LCA Disclosure Field Reference: What Each Record Proves](https://www.refolk.ai/guides/lca-disclosure-field-reference): Read any employer's public H-1B LCA disclosure records field by field, state what each proves about roles, pay, and worksites, and name the biases that mislead.
  - [Markdown](https://www.refolk.ai/guides/lca-disclosure-field-reference.md)
- [The Person Match-Key Reference: What Each Identifier Pins Down](https://www.refolk.ai/guides/person-match-key-reference): A lookup reference grading every person match key on uniqueness, survival through a job change, normalization, and its named false-merge mode. Pick a match rule fast.
  - [Markdown](https://www.refolk.ai/guides/person-match-key-reference.md)
- [The AI Defensibility Read: Durable Moat, Wrapper, or Feature](https://www.refolk.ai/guides/ai-defensibility-read): Score an AI startup on five externally-observable moat dimensions and reach a verdict before the IC, using only public signals the founder never has to hand you.
  - [Markdown](https://www.refolk.ai/guides/ai-defensibility-read.md)
- [Reconciling a Headline Talent-Pool Count to a Defensible Number](https://www.refolk.ai/guides/reconcile-talent-pool-count): Carry one inflated talent-pool count backwards through title, staleness, coverage, and active-share deductions to a defensible addressable number you can hand a stakeholder.
  - [Markdown](https://www.refolk.ai/guides/reconcile-talent-pool-count.md)
- [The AI-Authorship Discount: Reading Whose Skill a Repo Proves](https://www.refolk.ai/guides/ai-authorship-discount-reading-code): Score a candidate's public code on authorship-confidence dimensions and reach a defensible verdict: own skill, AI-assisted, or inflated, before you spend an interview slot.
  - [Markdown](https://www.refolk.ai/guides/ai-authorship-discount-reading-code.md)
- [The Mobilizer Read: Grading One Contact's Power to Move the Deal](https://www.refolk.ai/guides/mobilizer-read-grading-one-contact): Score one engaged contact on power, stake, and action, then decide Back, Test, or Look Past using live tests and public-profile checks before you over-invest.
  - [Markdown](https://www.refolk.ai/guides/mobilizer-read-grading-one-contact.md)
- [The People-Search Query Reference: Patterns, Matches, and Misses](https://www.refolk.ai/guides/people-search-query-reference): A lookup reference for writing candidate search queries that return the right people the first time, with the silent misses each pattern hides on every source.
  - [Markdown](https://www.refolk.ai/guides/people-search-query-reference.md)
- [Sourcing Cleared Candidates From Public Signals Into a Ranked Shortlist](https://www.refolk.ai/guides/sourcing-cleared-candidates-public-signals): A method to infer security clearance level, type, and reactivatable eligibility from public signals and build a lawfully screened, ranked cleared-candidate shortlist.
  - [Markdown](https://www.refolk.ai/guides/sourcing-cleared-candidates-public-signals.md)
- [The Role Fillability Read: Hire as Written, Relax One Constraint, or Rethink](https://www.refolk.ai/guides/role-fillability-read): Score one role brief against public labor-market signals and return a verdict - fillable as written, fillable if one constraint moves, or not fillable - with a ratio.
  - [Markdown](https://www.refolk.ai/guides/role-fillability-read.md)
- [The Co-Investor Syndicate Read: Lean In, Discount, or Pass](https://www.refolk.ai/guides/co-investor-syndicate-read): A scored framework for grading the existing investor syndicate on a round you have been offered allocation in, reaching a defensible Lean In, Discount, or Pass verdict.
  - [Markdown](https://www.refolk.ai/guides/co-investor-syndicate-read.md)
- [Sourcing a Matched Reference Customer for a Deal in Flight](https://www.refolk.ai/guides/sourcing-matched-reference-customer): Turn a late-stage reference request into a ranked shortlist of three to five matched, willing customer advocates the same afternoon, without re-burning your back-pocket three.
  - [Markdown](https://www.refolk.ai/guides/sourcing-matched-reference-customer.md)
- [Reproducing a Repo's Headline Benchmark Before You Trust It](https://www.refolk.ai/guides/reproduce-repo-headline-benchmark): A worked reproduction of one library's speedup claim, from clone to verdict, so you can return holds, hardware-inflated, or unreproducible with evidence attached.
  - [Markdown](https://www.refolk.ai/guides/reproduce-repo-headline-benchmark.md)
- [The Enrichment Waterfall Playbook: Provider Order and Blended Cost](https://www.refolk.ai/guides/enrichment-waterfall-provider-order): A vendor-neutral method to sequence enrichment sources by cost per valid result, gate dead data, govern write-back, and score sources monthly for replacement.
  - [Markdown](https://www.refolk.ai/guides/enrichment-waterfall-provider-order.md)
- [The Lookalike Shortlist Playbook: One Exemplar to 20-30 Ranked Comparables](https://www.refolk.ai/guides/lookalike-shortlist-from-one-exemplar): Turn one great employee into a ranked shortlist of 20 to 30 comparable candidates across GitHub, LinkedIn, and the open web, stress-tested against the clone trap.
  - [Markdown](https://www.refolk.ai/guides/lookalike-shortlist-from-one-exemplar.md)
- [The Hiring Pullback Read: Distress, Pivot, or Normal Slowdown](https://www.refolk.ai/guides/hiring-pullback-read): Score a target or portfolio company's shrinking job board from its public feed, classify the pullback as distress, pivot, or normal slowdown, and decide.
  - [Markdown](https://www.refolk.ai/guides/hiring-pullback-read.md)
- [The Pro-Rata Verdict: Exercise, Waive, or Sell the Follow-On](https://www.refolk.ai/guides/pro-rata-exercise-waive-sell): Score a portfolio company's next-round notice on ownership math, momentum, round quality, and reserves, then land on exercise, waive, or sell before the window closes.
  - [Markdown](https://www.refolk.ai/guides/pro-rata-exercise-waive-sell.md)
- [Re-Opening a Churned Account: From Lost Logo to Ranked Win-Back Queue](https://www.refolk.ai/guides/churned-account-winback-queue): A playbook to turn a book of churned B2B customers into a ranked win-back queue with a current named contact, a reason-to-return, and a cleared-to-send date.
  - [Markdown](https://www.refolk.ai/guides/churned-account-winback-queue.md)
- [The Pull-Request Signal Reference: What Code Really Proves](https://www.refolk.ai/guides/pull-request-signal-reference): A lookup reference for reviewing a candidate's public pull requests: each in-PR signal, what it proves about engineering judgment, and how it misleads you.
  - [Markdown](https://www.refolk.ai/guides/pull-request-signal-reference.md)
- [The Remote-Applicant Authenticity Read: Advance, Verify, or Reject](https://www.refolk.ai/guides/remote-applicant-authenticity-read): Score a remote applicant's public identity signals across GitHub, LinkedIn, and the open web, then return a defensible Advance, Verify, or Reject verdict before interview.
  - [Markdown](https://www.refolk.ai/guides/remote-applicant-authenticity-read.md)
- [The Hugging Face Footprint Read: Real Output, Fork, or Noise](https://www.refolk.ai/guides/hugging-face-footprint-read): Score any machine-learning engineer's Hugging Face profile into interview, thin, or noise by weighting each artifact for what it proves and discounting gamed metrics.
  - [Markdown](https://www.refolk.ai/guides/hugging-face-footprint-read.md)
- [The Job-Change Reconciliation Playbook: Moved Contact to Clean Record](https://www.refolk.ai/guides/job-change-reconciliation-playbook): A CRM-agnostic procedure to turn detected job changes into correct records: new employer, verified email, re-assigned owner, old history intact, zero duplicates.
  - [Markdown](https://www.refolk.ai/guides/job-change-reconciliation-playbook.md)
- [The Competitive Threat Tier: Deep-Monitor, Watch, or Ignore a Rival](https://www.refolk.ai/guides/competitive-threat-tier-rubric): A weighted, public-signal rubric that scores any competitor into a monitoring tier and matching review cadence, so two analysts reach the same verdict.
  - [Markdown](https://www.refolk.ai/guides/competitive-threat-tier-rubric.md)
- [The Capability Gap Map: Benchmarking a Competitor's Team Skill Depth](https://www.refolk.ai/guides/competitor-capability-gap-map): A step-by-step method to score where a named competitor's team is deeper, at parity, or weaker than yours, skill by skill, using only public data.
  - [Markdown](https://www.refolk.ai/guides/competitor-capability-gap-map.md)
- [The Champion-Move Priority Score: Chase Now, Nurture, or Pass](https://www.refolk.ai/guides/champion-move-priority-score): Score a past champion's job change on advocacy, seat authority, account fit, and timing, and reach a chase-now, nurture, or pass verdict in five minutes.
  - [Markdown](https://www.refolk.ai/guides/champion-move-priority-score.md)
- [Recruiting Design Partners for a Developer Tool From Public Signals](https://www.refolk.ai/guides/design-partners-from-public-signals): A start-to-finish method for going from a written pain profile to a ranked shortlist of design partners and the named engineer who owns the pain.
  - [Markdown](https://www.refolk.ai/guides/design-partners-from-public-signals.md)
- [The Openness-Signal Read: Reach Now, Watch, or Skip a Passive Candidate](https://www.refolk.ai/guides/openness-signal-read-passive-candidate): Score a passive candidate's dated public signals and sort your list into reach-now, watch, or skip against a reply-rate cutoff you can defend.
  - [Markdown](https://www.refolk.ai/guides/openness-signal-read-passive-candidate.md)
- [Estimating a Competitor's Attrition Rate From Public Profiles](https://www.refolk.ai/guides/estimate-competitor-attrition-public-profiles): An outside-in method to estimate a competitor's annual attrition rate by function and seniority from public profiles, and decide if it is elevated, normal, or low.
  - [Markdown](https://www.refolk.ai/guides/estimate-competitor-attrition-public-profiles.md)
- [Sourcing Co-Investors to Fill a Round You Are Leading](https://www.refolk.ai/guides/sourcing-co-investors-to-fill-a-round): A staged method for the lead investor to turn an open allocation into a tiered, conflict-screened co-investor shortlist with an intro path mapped for every top name.
  - [Markdown](https://www.refolk.ai/guides/sourcing-co-investors-to-fill-a-round.md)
- [Mapping an Account's Whitespace Into a Ranked Expansion Queue](https://www.refolk.ai/guides/account-whitespace-expansion-queue): Turn one won account into a ranked queue of unpenetrated units and regions, each with named buyers to work this quarter. A full expansion sourcing method.
  - [Markdown](https://www.refolk.ai/guides/account-whitespace-expansion-queue.md)
- [The Back-Channel Customer Check: Sourcing a Startup's Real Users Before You Wire](https://www.refolk.ai/guides/back-channel-customer-check): An investor-side procedure to reconstruct a startup's customer base from public signals, reach real users without the founder, and run calls that surface churn.
  - [Markdown](https://www.refolk.ai/guides/back-channel-customer-check.md)
- [The Email Deliverability Verdict: Send, Verify, or Drop an Address](https://www.refolk.ai/guides/email-deliverability-verdict): A seven-signal rubric to score a single sourced email address and land on a defensible Send, Verify, or Drop verdict with a handling rule.
  - [Markdown](https://www.refolk.ai/guides/email-deliverability-verdict.md)
- [Working the Off-Sheet References on a Finalist](https://www.refolk.ai/guides/off-sheet-references-finalist): Build a ranked list of off-sheet references from a finalist's real work history, clear the consent and current-employer gate, and run calls that surface risk.
  - [Markdown](https://www.refolk.ai/guides/off-sheet-references-finalist.md)
- [Mapping a Competitor's Real Location Footprint, Metro by Metro](https://www.refolk.ai/guides/competitor-location-footprint-map): An outside-in procedure for building a defensible metro-by-function workforce map of a rival, with a remote correction and a confidence flag on every cell.
  - [Markdown](https://www.refolk.ai/guides/competitor-location-footprint-map.md)
- [Turning an Assigned Territory Into a Ranked Book You Can Work](https://www.refolk.ai/guides/territory-to-ranked-account-book): A repeatable method for a new AE or founder to audit an inherited account list, source the ICP accounts nobody assigned, and rank the book into working tiers.
  - [Markdown](https://www.refolk.ai/guides/territory-to-ranked-account-book.md)
- [The Data-Source Onboarding Playbook: Sample Test to Verified Backfill](https://www.refolk.ai/guides/data-source-onboarding-playbook): Onboard a new people-and-company data feed from a controlled sample test through a staged backfill into your system of record without duplicates or unlawful records.
  - [Markdown](https://www.refolk.ai/guides/data-source-onboarding-playbook.md)
- [The Co-Founder Durability Read: Backable, Watch, or Walk](https://www.refolk.ai/guides/co-founder-durability-read): Score a founding pair's relationship durability from public history alone and return a Backable, Watch, or Walk verdict before you take the diligence call.
  - [Markdown](https://www.refolk.ai/guides/co-founder-durability-read.md)
- [The Maintainer Outreach Acceptability Standard: Send, Revise, or Hold](https://www.refolk.ai/guides/maintainer-outreach-acceptability-standard): A gradeable pre-send checklist for messaging open-source maintainers, converting scattered community norms into a Send, Revise, or Hold verdict two teammates share.
  - [Markdown](https://www.refolk.ai/guides/maintainer-outreach-acceptability-standard.md)
- [The Warm-Intro Path to a Passive Candidate: Map, Rank, Ask](https://www.refolk.ai/guides/warm-intro-passive-candidate): Take one passive candidate you cannot cold-reach, map and rank the warm paths to them, and send a double opt-in intro request that converts.
  - [Markdown](https://www.refolk.ai/guides/warm-intro-passive-candidate.md)
- [The Outside-In Revenue-per-Employee Read: Leaner, On-Band, or Bloated](https://www.refolk.ai/guides/outside-in-revenue-per-employee-read): Estimate a private competitor's revenue per employee from public signals, correct the headcount, band the revenue, and defend a leaner or bloated verdict.
  - [Markdown](https://www.refolk.ai/guides/outside-in-revenue-per-employee-read.md)
- [The Dial-Ready List Standard: Cleared to Call, Hold, or Scrub](https://www.refolk.ai/guides/dial-ready-list-standard): A pass/fail rubric for grading an outbound calling list as cleared, hold, or scrub against DNC, consent, calling-window, and audit-trail criteria.
  - [Markdown](https://www.refolk.ai/guides/dial-ready-list-standard.md)
- [Diligencing a Secondary Share Offer Before You Wire](https://www.refolk.ai/guides/diligencing-a-secondary-share-offer): An ordered procedure to vet a secondary share purchase: seller motivation, transfer restrictions, share class, and a defensible price to a wire-or-walk verdict.
  - [Markdown](https://www.refolk.ai/guides/diligencing-a-secondary-share-offer.md)
- [The MCP Server Trust Score: Connect, Sandbox, or Reject](https://www.refolk.ai/guides/mcp-server-trust-score): Score any MCP server across six trust dimensions and reach a defensible connect, sandbox, or reject verdict you can record in a ticket.
  - [Markdown](https://www.refolk.ai/guides/mcp-server-trust-score.md)

## Docs
- [What is Refolk?](https://www.refolk.ai/docs/what-is-refolk): Refolk is an AI agent for headhunting and prospecting: a people search engine you talk to in plain English. What it finds, who it's for, and how it differs from filter-based search.
- [How search works](https://www.refolk.ai/docs/how-search-works): What happens between typing one sentence and getting a ranked shortlist: planning, live source reading, cross-referencing, and per-result reasoning.
- [Where the data comes from](https://www.refolk.ai/docs/data-sources): The public sources behind every result: public GitHub activity, public LinkedIn and Crunchbase records, and live web search. Read at search time, not from a stale export.
- [Published searches](https://www.refolk.ai/docs/published-searches): Real searches users chose to share, published with their full prompt and results. How publishing and unpublishing work.
- [Company and repository lists](https://www.refolk.ai/docs/company-and-repo-lists): How the browsable company lists (by industry, city, stage, investor) and GitHub repository lists (by language, topic) are built and kept fresh.
- [Credits and pricing](https://www.refolk.ai/docs/credits-and-pricing): How credits are priced per search, what the free tier includes, and why an account can never be overdrafted.
- [Privacy and data removal](https://www.refolk.ai/docs/privacy-and-data-removal): What Refolk stores about accounts, how results about third parties are handled, and how to request removal or account deletion.

## API and MCP

> Both searches are available programmatically. Authenticate with `Authorization: Bearer rfk_live_...`; keys are created at https://www.refolk.ai/hire/api and metered in the same credits the app spends.

- [API documentation index](https://www.refolk.ai/developers/index.md): Every reference page as plain Markdown, in one list.
- [OpenAPI document](https://www.refolk.ai/api/v1/openapi.json): The machine-readable specification for every endpoint.
- [MCP endpoint](https://www.refolk.ai/api/mcp): Streamable HTTP. Four tools: search in plain English, search with filters, plan a filter set, check the balance.
- [Quickstart](https://www.refolk.ai/developers/quickstart): Create a key, run your first search, and read what comes back. A working request in under two minutes, in curl, TypeScript, and Python.
  - [Markdown](https://www.refolk.ai/developers/quickstart.md)
- [Authentication](https://www.refolk.ai/developers/authentication): How API keys work: creating one, sending it, rotating it, and what happens when one leaks. Keys are shown once and hashed at rest.
  - [Markdown](https://www.refolk.ai/developers/authentication.md)
- [Credits and limits](https://www.refolk.ai/developers/credits-and-limits): What each call costs, what a failed run is charged, what the rate limits are, and how to check a balance before a long run.
  - [Markdown](https://www.refolk.ai/developers/credits-and-limits.md)
- [Playground](https://www.refolk.ai/developers/playground): Run any endpoint from the browser, signed in, on your own credits. Prefilled examples, the real response, and the equivalent curl for your own code.
  - [Markdown](https://www.refolk.ai/developers/playground.md)
- [Search in plain English](https://www.refolk.ai/developers/agentic-search): POST /v1/search. One sentence in, a ranked shortlist out, with the evidence behind every pick. Blocking or streamed as server-sent events.
  - [Markdown](https://www.refolk.ai/developers/agentic-search.md)
- [Search with filters](https://www.refolk.ai/developers/structured-search): POST /v1/people/search. An exact filter set in, a deterministic page of people out, one flat price a page. Every field, every allowed value, and how to paginate.
  - [Markdown](https://www.refolk.ai/developers/structured-search.md)
- [Errors](https://www.refolk.ai/developers/errors): One error shape for every endpoint, a closed set of types, and which of them are worth retrying. What gets refunded when a call fails.
  - [Markdown](https://www.refolk.ai/developers/errors.md)
- [MCP server](https://www.refolk.ai/developers/mcp): Give Claude, Cursor, VS Code, or any MCP client the ability to search for people mid-conversation. One URL, one header, four tools.
  - [Markdown](https://www.refolk.ai/developers/mcp.md)
- [MCP setup for Claude Code](https://www.refolk.ai/developers/mcp/claude-code): One command. Search for people from the terminal you are already in.
  - [Markdown](https://www.refolk.ai/developers/mcp/claude-code.md)
- [MCP setup for Cursor](https://www.refolk.ai/developers/mcp/cursor): Add it once to mcp.json and every chat in the editor can search.
  - [Markdown](https://www.refolk.ai/developers/mcp/cursor.md)
- [MCP setup for Claude Desktop](https://www.refolk.ai/developers/mcp/claude-desktop): Search for people inside a normal Claude conversation.
  - [Markdown](https://www.refolk.ai/developers/mcp/claude-desktop.md)
- [MCP setup for VS Code](https://www.refolk.ai/developers/mcp/vs-code): Copilot's agent mode gets four tools and a real people index.
  - [Markdown](https://www.refolk.ai/developers/mcp/vs-code.md)
- [MCP setup for Windsurf](https://www.refolk.ai/developers/mcp/windsurf): Cascade can find the people, not just the code.
  - [Markdown](https://www.refolk.ai/developers/mcp/windsurf.md)
- [MCP setup for Cline](https://www.refolk.ai/developers/mcp/cline): Add a remote server from the MCP pane and keep working.
  - [Markdown](https://www.refolk.ai/developers/mcp/cline.md)

## Candidate docs
- [What is Refolk for job seekers?](https://www.refolk.ai/candidates/docs/what-is-refolk-for-job-seekers): Refolk writes your resume from your own history, rewrites it for every job you apply to, drafts the cover letter, and scores the fit. What it does, what it deliberately does not do, and who it suits.
- [How applying works](https://www.refolk.ai/candidates/docs/how-applying-works): The whole path from pasting your history to sending an application: profile, master resume, queued jobs, tailoring, and the three ways a finished draft gets sent.
- [Building your profile](https://www.refolk.ai/candidates/docs/building-your-profile): Three ways in - upload a resume, hand over public links, or type it yourself - and why every guess is shown back to you for correction before anything is written from it.
- [Resumes and versions](https://www.refolk.ai/candidates/docs/resumes-and-versions): How the master resume is written, how versions and the primary resume work, what the screener checks look for, and how to get a resume out as PDF, Markdown, or plain text.
- [How job matches work](https://www.refolk.ai/candidates/docs/job-matches): Where the job feed comes from, how postings are ranked against your profile, and why the match score is not the fit score.
- [Tailoring, fit scores, and cover letters](https://www.refolk.ai/candidates/docs/tailoring-and-fit-scores): What tailoring changes and what it never changes, how the 0 to 100 fit score is produced, and what a good cover letter draft looks like here.
- [The browser extension](https://www.refolk.ai/candidates/docs/the-browser-extension): Refolk AutoApply, the Chrome extension. Two of the four boards only accept an application filled in on your own machine: what it does, what it can see, what it never does, and how to set it up in two presses.
- [Tracking applications](https://www.refolk.ai/candidates/docs/tracking-applications): The statuses an application moves through, how to add jobs in bulk, and how to paste a job description in later to improve a tailoring pass.
- [What it costs](https://www.refolk.ai/candidates/docs/what-it-costs): Nothing to write, research, tailor, or track. The one number to know is the weekly sending limit: 25 applications a week, sent for you, free.
- [The weekly email](https://www.refolk.ai/candidates/docs/the-weekly-email): One email a week, only when there is something to act on: new matches, applications sitting finished, and submissions that have gone quiet. How to turn it off.
- [Privacy and your data](https://www.refolk.ai/candidates/docs/privacy-and-your-data): Your profile, resumes, and applications are never shown to the recruiters on the hiring side. What is stored, what is not, and how to delete it.

## Blog posts
- [HackerRank Chakra Deleted the Recruiter Screen. Sourcing Is Next.](https://www.refolk.ai/blog/hackerrank-chakra-sourcing-bottleneck): HackerRank's Oct 7 2026 Chakra launch collapses three interview rounds into one. Here is what that does to sourcing, and how to find AI fluency now.
- [Oracle's PIP-to-VSP Swap: A 60-Day Shadow Pool Before December](https://www.refolk.ai/blog/oracle-vsp-october-2026-shadow-pool): Oracle expanded its Voluntary Separation Program on Oct 1, 2026. Here is how to source the exit cohort before December layoffs trigger WARN filings.
- [Sourcing the 5% Who Rewrote Their Job Around AI](https://www.refolk.ai/blog/source-ai-fluent-candidates-outside-engineering): Google says 5% of workers are AI-fluent. Here's how to source them in marketing, finance, legal, and ops before the LinkedIn Recruiter crowd does.
- [Retire "Prompt Engineer": Six Boolean Terms to Source in 2026](https://www.refolk.ai/blog/workday-prompting-demand-fell-25-percent-source-these-6-terms): Workday's Oct 2026 report shows prompt-skill demand fell 25% while AI building rose 51%. Six boolean terms to source the 26.9x larger pool.
- [Saffron Grades AI-Fluent Devs. MCP Authors Are the Public Shortlist.](https://www.refolk.ai/blog/saffron-mcp-authors-ai-fluent-engineer-shortlist): Saffron, Contrario, and Cursor lock AI-fluency data inside hiring companies. Here is the public GitHub shortlist that beats them from the outside.
- [HN "Who Wants to Be Hired" Is a Honeypot: Source It Anyway](https://www.refolk.ai/blog/hn-who-wants-to-be-hired-october-2026-spam-honeypot): The October 2026 HN Who Wants to Be Hired thread returned 3 spam emails and 0 real jobs for one poster. How to source it without being email four.
- [Ninja Theory's Cambridge Closure: 8 Named Hellblade Specialists](https://www.refolk.ai/blog/ninja-theory-cambridge-closure-hellblade-sourcing): Ninja Theory's October 2026 redundancy consultation put Hellblade pipeline specialists on LinkedIn. Here is the sourcer's shortlist and expansion plan.
- [Swami's Boomerang List: 2,896 Ex-Amazon ML Engineers to Reach First](https://www.refolk.ai/blog/swami-boomerang-list-amazon-ml-engineers): Amazon's Boomerang Reengagement Initiative named which ex-AI/ML staff it wants back. Here is how to source them before expedited loops close.
- [Cursor's 150-Person Roster vs Hiring Assistant 2: A Poach Map](https://www.refolk.ai/blog/cursor-anysphere-poach-map-hiring-assistant-2): Anysphere runs on ~150 engineers at $2B ARR and bans AI in interviews. Here is how to build a named poach list the agentic sourcers miss.
- [1,100 Companies, 22 Personas: GitHub Tells That Beat the DPRK Funnel](https://www.refolk.ai/blog/dprk-fake-candidates-github-tells-pre-interview-checklist): A pre-interview checklist of GitHub, resume, and metadata signals that catch DPRK IT-worker personas before a hiring manager books the call.
- [Temporal's $550M Lands 4 Miles From 4,501 Amazon SDEs](https://www.refolk.ai/blog/temporal-550m-bellevue-amazon-warn-sourcing): Temporal raised $550M in Bellevue, four miles from Amazon's biggest WARN pool in a decade. The sourcing lane, with real numbers.
- [Uber's 1% Remote Cap Just Named 1,947 Poach Targets](https://www.refolk.ai/blog/uber-1-percent-remote-cap-flight-risk-list): Uber's Sept 2 2026 cut hits 3,300 roles, flattens micro-teams, and caps remote at 1%. Here is the flight-risk shortlist for remote-first hirers.
- [Meta's TBD Labs Runs on 32 Names. Your Niche Is Probably Smaller.](https://www.refolk.ai/blog/meta-tbd-labs-named-target-sourcing-playbook): Meta's TBD Labs playbook is named-target sourcing, not hiring. Copy the identify-research-pitch method without the $100M signing bonus budget.
- [Greenhouse Named hireEZ. Your $12,960 LinkedIn Seat Is the Fuse.](https://www.refolk.ai/blog/greenhouse-hireez-linkedin-restriction-risk-2026): Greenhouse's 2026 AI roundup flagged hireEZ for LinkedIn restriction risk. Here is the dollar math, the ToS mechanism, and how to vet safe tools.
- [Oracle's Abilene Badge-Fail: A 60-Day Window on Stargate Operators](https://www.refolk.ai/blog/oracle-abilene-stargate-layoffs-sourcing-window): Oracle's Sept 14 Abilene Stargate layoffs opened a 60-day poach window on OCI and Customer Hardware Support operators before Crusoe backfills.
- [Google's 4,500-Signature Petition as a Flight-Risk Signal](https://www.refolk.ai/blog/google-4500-petition-flight-risk-list): 4,500 Googlers signed a July 2026 petition demanding layoff protections. Here is how sourcers turn that into a segment without naming names.
- [SeekOut MCP: What Chat-Window Sourcing Actually Replaces](https://www.refolk.ai/blog/seekout-mcp-server-sourcing-in-claude): SeekOut, Greenhouse, and Manatal shipped MCP servers for Claude and ChatGPT. Here is what sourcing in a chat window gains, and what it loses.
- [LinkedIn Recruiter 2026: $12,960 a Seat for 86 Replies](https://www.refolk.ai/blog/linkedin-recruiter-cost-2026-per-reply-math): LinkedIn Recruiter Corporate hit $12,960 a seat for 2026. At a 4.77% software reply rate, that is $151 per reply. Here is the math and the alternative.
- [Juicebox vs LinkedIn Hiring Assistant: 1,282 Rust Devs, 7 Maintainers](https://www.refolk.ai/blog/juicebox-vs-linkedin-hiring-assistant-coverage-gap): Juicebox at $139 and LinkedIn Hiring Assistant inside Recruiter both promise plain English sourcing. Here is what each one structurally cannot see.
- [Amazon Project Dawn 2: Blind Named 4 Orgs Before the WARN Hit](https://www.refolk.ai/blog/amazon-project-dawn-2-blind-pre-warn-sourcing-playbook): A Blind thread named Stores, Prime Video, AWS and PXT before Amazon's 10/1/2026 WARN. Here is the pre-WARN sourcing playbook.
- [HN "Who Wants to Be Hired" Beats Open-to-Work 3,584:1 at Staff Tier](https://www.refolk.ai/blog/november-who-wants-to-be-hired-vs-open-to-work): Why the November 2026 Hacker News "Who wants to be hired?" thread outperforms LinkedIn Open-to-Work for sourcing senior and staff engineers.
- [Ghost Jobs Hit 27.4%. The 400-App Inbox Is the Floor Now.](https://www.refolk.ai/blog/400-applications-inbox-outbound-sourcing-2026): Ghost jobs are 27.4% of LinkedIn listings, apps per role tripled since 2021, and 86% of employers ghost back. The math says outbound is all that is left.
- [The October HN "Who Is Hiring" Thread Is a 400-Row Prospect List](https://www.refolk.ai/blog/hn-who-is-hiring-october-2026-prospect-list): The October 2026 Hacker News hiring thread named 400+ companies with budget, a hiring manager, and a stack. Here is how to parse it in an hour.
- [AGENTS.md as a Sourcing Signal: The 1,013-Repo Shortlist](https://www.refolk.ai/blog/agents-md-claude-md-github-sourcing-signal): AGENTS.md and CLAUDE.md now cover a third of top GitHub repos. Here is the sourcing boolean, the slop filters, and the shortlist that matters.
- [Nike's "Pace" Plan Is Restructure #3. Beaverton Has 15 Months.](https://www.refolk.ai/blog/nike-pace-restructuring-beaverton-tech-sourcing-2027): Nike's Oct 2 "Pace" plan pre-announces 2027 layoffs without naming targets. Here is how to build the Beaverton and Bengaluru poach list now.
- [LinkedIn Hiring Assistant 2 Can't See GitHub. That's 99.81% of Rust.](https://www.refolk.ai/blog/linkedin-hiring-assistant-2-github-blindspot): LinkedIn's Hiring Assistant 2 ships free in November with better reasoning. It still can't see GitHub, which is where the hard hires live.
- [EA's $170M Creditor Slide: Back-Solving a 1,400-Name Poach List](https://www.refolk.ai/blog/ea-170m-creditor-math-1400-name-poach-list): EA went private and killed its 8-K pipeline. The $170M "organizational efficiencies" line briefed to creditors rebuilds the target list for sourcers.
- [Instinct Hit $10B in 33 Days: The 40 Names to Source First](https://www.refolk.ai/blog/instinct-10b-reflexion-sourcing-list): Instinct 4x'd to $10B with 14 employees. Here is the Reflexion co-author tree, Sierra adjacency, and LiveKit squeeze to source before Sequoia's recruiters move.
- [Microsoft's 268 Xbox Cuts: The 10 Redmond Names That Matter](https://www.refolk.ai/blog/microsoft-268-xbox-cuts-redmond-poach-list): Microsoft's 268-person Xbox cut hides a Redmond WARN filing. Here's the named Unreal and C++ pool and the 60-day window to work it.
- [Leidos Just Named 84 Cleared SOC Analysts. That's 37% of the Pool.](https://www.refolk.ai/blog/leidos-cbp-soc-warn-84-cleared-cyber-ashburn): Leidos lost the CBP SOC contract to Accenture Federal. 84 cleared cyber workers hit market Nov 23. Here is how to source them before the window closes.

## Companies by industry
- [AI companies](https://www.refolk.ai/companies/ai): Companies building AI products, foundation models, and applied ML platforms.
- [SaaS companies](https://www.refolk.ai/companies/saas): Software-as-a-service vendors selling subscription cloud software to other businesses.
- [Fintech companies](https://www.refolk.ai/companies/fintech): Companies modernising banking, payments, lending, and financial infrastructure.
- [Developer tools companies](https://www.refolk.ai/companies/developer-tools): IDEs, runtimes, frameworks, and platforms built primarily for engineers.
- [Cybersecurity companies](https://www.refolk.ai/companies/cybersecurity): Companies defending or attacking software, networks, and cloud infrastructure.
- [Data infrastructure companies](https://www.refolk.ai/companies/data-infrastructure): Databases, warehouses, lakes, pipelines, and observability for production data.
- [Biotech companies](https://www.refolk.ai/companies/biotech): Companies applying biology, chemistry, and computation to therapeutics and tooling.
- [Healthtech companies](https://www.refolk.ai/companies/healthtech): Companies building software and devices for clinicians, patients, and payers.
- [Edtech companies](https://www.refolk.ai/companies/edtech): Companies building tools and platforms for K-12, higher-ed, and lifelong learners.
- [Robotics companies](https://www.refolk.ai/companies/robotics): Companies designing autonomous machines, manipulators, and the software that runs them.
- [Climate tech companies](https://www.refolk.ai/companies/climate-tech): Companies decarbonising power, transport, agriculture, and industry.
- [Gaming companies](https://www.refolk.ai/companies/gaming): Studios, engines, tooling, and platforms across console, PC, mobile, and web.
- [Ecommerce companies](https://www.refolk.ai/companies/ecommerce): Marketplaces, brands, and infrastructure for selling online.
- [Media companies](https://www.refolk.ai/companies/media): Companies producing or distributing news, video, audio, and creator tooling.
- [Logistics companies](https://www.refolk.ai/companies/logistics): Companies moving goods through warehouses, fleets, ports, and last-mile networks.
- [Real estate tech companies](https://www.refolk.ai/companies/real-estate-tech): Software, marketplaces, and finance for residential and commercial real estate.
- [Marketing tech companies](https://www.refolk.ai/companies/marketing-tech): Tools for marketers: CRM, attribution, content, ads, growth, and analytics.
- [HR tech companies](https://www.refolk.ai/companies/hr-tech): Software and services for hiring, payroll, performance, and workforce planning.
- [Legal tech companies](https://www.refolk.ai/companies/legal-tech): Companies building software and AI for law firms, in-house teams, and courts.
- [Consumer apps companies](https://www.refolk.ai/companies/consumer-apps): Direct-to-consumer mobile and web apps across social, productivity, and lifestyle.
- [Blockchain companies](https://www.refolk.ai/companies/blockchain): Companies building L1s, L2s, wallets, infra, and apps on public blockchains.
- [Hardware companies](https://www.refolk.ai/companies/hardware): Chips, devices, and physical products designed by venture-backed teams.

## Companies by location
- [Companies in San Francisco](https://www.refolk.ai/companies/in/san-francisco): The world's largest concentration of venture-backed software and AI companies.
- [Companies in New York](https://www.refolk.ai/companies/in/new-york): Home to fintech, media, healthtech, and a fast-growing AI scene.
- [Companies in Los Angeles](https://www.refolk.ai/companies/in/los-angeles): Media, gaming, consumer tech, and a fast-growing aerospace cluster.
- [Companies in Seattle](https://www.refolk.ai/companies/in/seattle): Cloud, ecommerce, gaming, and biotech anchored by Amazon and Microsoft.
- [Companies in Boston](https://www.refolk.ai/companies/in/boston): Biotech, robotics, and enterprise software clustered around MIT and Harvard.
- [Companies in Austin](https://www.refolk.ai/companies/in/austin): A fast-growing hub for software, semiconductors, and crypto.
- [Companies in Chicago](https://www.refolk.ai/companies/in/chicago): Logistics, fintech, and a sizable enterprise SaaS ecosystem.
- [Companies in Miami](https://www.refolk.ai/companies/in/miami): Crypto, fintech, and consumer tech with a strong Latin-American bridge.
- [Companies in Denver](https://www.refolk.ai/companies/in/denver): Aerospace, climate tech, and a growing software ecosystem.
- [Companies in London](https://www.refolk.ai/companies/in/london): Europe's largest fintech and AI hub by capital deployed and exits.
- [Companies in Berlin](https://www.refolk.ai/companies/in/berlin): A magnet for European startups across SaaS, climate tech, and consumer.
- [Companies in Paris](https://www.refolk.ai/companies/in/paris): France's centre of gravity for AI, deeptech, and luxury commerce.
- [Companies in Amsterdam](https://www.refolk.ai/companies/in/amsterdam): Fintech, ecommerce, and developer tools from Booking to Adyen.
- [Companies in Stockholm](https://www.refolk.ai/companies/in/stockholm): Sweden's tech capital - gaming, fintech, music, and climate tech.
- [Companies in Dublin](https://www.refolk.ai/companies/in/dublin): EMEA HQ city for major US tech firms and a growing native ecosystem.
- [Companies in Zurich](https://www.refolk.ai/companies/in/zurich): AI research, robotics, and enterprise software anchored by ETH.
- [Companies in Toronto](https://www.refolk.ai/companies/in/toronto): Canada's largest tech hub and a major AI research centre.
- [Companies in Vancouver](https://www.refolk.ai/companies/in/vancouver): Gaming, climate tech, and a sizable engineering talent pool.
- [Companies in Tel Aviv](https://www.refolk.ai/companies/in/tel-aviv): Israel's startup capital - cybersecurity, defence tech, and AI.
- [Companies in Singapore](https://www.refolk.ai/companies/in/singapore): Southeast Asia's HQ city for fintech, logistics, and Web3.
- [Companies in Tokyo](https://www.refolk.ai/companies/in/tokyo): Robotics, gaming, and enterprise software at scale.
- [Companies in Bangalore](https://www.refolk.ai/companies/in/bangalore): India's tech capital and a major hub for global engineering teams.
- [Companies in Sydney](https://www.refolk.ai/companies/in/sydney): Australia's largest tech hub across SaaS, fintech, and consumer.
- [Companies in São Paulo](https://www.refolk.ai/companies/in/sao-paulo): Latin America's largest tech ecosystem, anchored by fintech.
- [Companies in the United States](https://www.refolk.ai/companies/in/usa): The largest startup ecosystem on the planet by capital and exits.
- [Companies in the United Kingdom](https://www.refolk.ai/companies/in/uk): Europe's biggest tech market, with London the centre of gravity.
- [Companies in Germany](https://www.refolk.ai/companies/in/germany): Europe's industrial powerhouse turning out climate, mobility, and B2B SaaS firms.
- [Companies in France](https://www.refolk.ai/companies/in/france): Strong in AI, deeptech, and luxury - and the home of La French Tech.
- [Companies in the Netherlands](https://www.refolk.ai/companies/in/netherlands): Dense ecosystem of fintech, ecommerce, and developer-tool companies.
- [Companies in Sweden](https://www.refolk.ai/companies/in/sweden): Outsized share of unicorns per capita - gaming, fintech, music, climate.
- [Companies in Canada](https://www.refolk.ai/companies/in/canada): Major AI research hubs in Toronto and Montreal, plus growing SaaS.
- [Companies in Israel](https://www.refolk.ai/companies/in/israel): World leader in cybersecurity and one of the most active startup ecosystems.
- [Companies in India](https://www.refolk.ai/companies/in/india): Huge engineering base and rapidly maturing native startup ecosystem.
- [Companies in Singapore](https://www.refolk.ai/companies/in/singapore-country): Southeast Asia's capital-markets and HQ centre.
- [Companies in Australia](https://www.refolk.ai/companies/in/australia): Sydney and Melbourne anchor a SaaS-heavy startup ecosystem.
- [Companies in Japan](https://www.refolk.ai/companies/in/japan): Robotics, gaming, and a slowly opening enterprise software market.
- [Companies in Brazil](https://www.refolk.ai/companies/in/brazil): The largest tech market in Latin America, anchored by fintech.
- [Companies in Ireland](https://www.refolk.ai/companies/in/ireland): EMEA HQ for many US tech giants and a growing native ecosystem.
- [Companies in Switzerland](https://www.refolk.ai/companies/in/switzerland): Deeptech research, robotics, and enterprise software from ETH and EPFL.

## Companies by funding stage
- [Pre-seed companies](https://www.refolk.ai/companies/series/pre-seed): Companies that have raised friends-and-family or pre-seed capital.
- [Seed companies](https://www.refolk.ai/companies/series/seed): Companies on their seed round, typically the first priced equity raise.
- [Series A companies](https://www.refolk.ai/companies/series/series-a): Companies that have closed a Series A - product-market fit confirmed and scaling.
- [Series B companies](https://www.refolk.ai/companies/series/series-b): Companies that have closed a Series B - proven scaling motion, hiring aggressively.
- [Series C companies](https://www.refolk.ai/companies/series/series-c): Companies that have closed a Series C - growth-stage with significant revenue.
- [Series D companies](https://www.refolk.ai/companies/series/series-d): Late-stage venture: Series D companies often eyeing IPO or large strategic exits.
- [Late-stage venture companies](https://www.refolk.ai/companies/series/late-stage): Series E and beyond - pre-IPO scaleups with hundreds of employees and meaningful revenue.
- [Private equity companies](https://www.refolk.ai/companies/series/private-equity): Companies that have taken private-equity capital or large secondaries.
- [IPO companies](https://www.refolk.ai/companies/series/ipo): Public companies and recent post-IPO follow-on raises.
- [Angel-funded companies](https://www.refolk.ai/companies/series/angel): Companies whose latest disclosed round is an angel investment.
- [Convertible-note companies](https://www.refolk.ai/companies/series/convertible): Companies on convertible notes or debt-style financings.
- [Grant-funded companies](https://www.refolk.ai/companies/series/grant): Companies whose latest disclosed funding is grant or non-dilutive support.

## Companies by investor
- [Companies backed by Y Combinator](https://www.refolk.ai/companies/funded-by/y-combinator): The most prolific seed accelerator in the world, batch class twice a year.
- [Companies backed by Andreessen Horowitz](https://www.refolk.ai/companies/funded-by/a16z): Multi-stage venture firm investing across consumer, enterprise, fintech, and crypto.
- [Companies backed by Sequoia Capital](https://www.refolk.ai/companies/funded-by/sequoia): Storied venture firm backing seed through pre-IPO across software and infrastructure.
- [Companies backed by Accel](https://www.refolk.ai/companies/funded-by/accel): Global venture firm with a strong record in enterprise SaaS, security, and infra.
- [Companies backed by Benchmark](https://www.refolk.ai/companies/funded-by/benchmark): Concentrated, partner-led venture firm focused on Series A consumer and enterprise.
- [Companies backed by Founders Fund](https://www.refolk.ai/companies/funded-by/founders-fund): Contrarian venture firm investing in deeptech, defence, and breakthrough software.
- [Companies backed by Lightspeed Venture Partners](https://www.refolk.ai/companies/funded-by/lightspeed): Multi-stage venture firm with deep practices in enterprise, consumer, and fintech.
- [Companies backed by Kleiner Perkins](https://www.refolk.ai/companies/funded-by/kleiner-perkins): Sand Hill Road institution backing software, climate, and biotech.
- [Companies backed by Greylock](https://www.refolk.ai/companies/funded-by/greylock): Early-stage venture firm with a strong enterprise and AI footprint.
- [Companies backed by Khosla Ventures](https://www.refolk.ai/companies/funded-by/khosla-ventures): Vinod Khosla's firm - deeptech, climate, healthcare, and contrarian software bets.
- [Companies backed by General Catalyst](https://www.refolk.ai/companies/funded-by/general-catalyst): Multi-stage firm with a thesis-driven approach across software and healthcare.
- [Companies backed by Thrive Capital](https://www.refolk.ai/companies/funded-by/thrive-capital): Joshua Kushner's firm investing across consumer, fintech, and enterprise software.
- [Companies backed by Index Ventures](https://www.refolk.ai/companies/funded-by/index-ventures): Transatlantic venture firm with a deep bench of enterprise SaaS and fintech bets.
- [Companies backed by ICONIQ](https://www.refolk.ai/companies/funded-by/iconiq): Growth-stage firm combining venture, growth equity, and family-office capital.
- [Companies backed by Tiger Global](https://www.refolk.ai/companies/funded-by/tiger-global): Crossover firm that became one of the most prolific late-stage venture investors.
- [Companies backed by Bessemer Venture Partners](https://www.refolk.ai/companies/funded-by/bessemer): Long-running venture firm with a defining record in cloud and SaaS.
- [Companies backed by Battery Ventures](https://www.refolk.ai/companies/funded-by/battery-ventures): Multi-stage firm investing across infrastructure, application, and industrial software.
- [Companies backed by Spark Capital](https://www.refolk.ai/companies/funded-by/spark-capital): Boston- and NYC-based firm with a strong consumer and creator-economy footprint.
- [Companies backed by First Round Capital](https://www.refolk.ai/companies/funded-by/first-round): Concentrated seed-stage firm with high-touch portfolio support.
- [Companies backed by Initialized Capital](https://www.refolk.ai/companies/funded-by/initialized): Garry Tan's firm focused on early-stage technical founders.
- [Companies backed by Soma Capital](https://www.refolk.ai/companies/funded-by/soma-capital): Founder-led seed-stage firm investing globally with a strong YC overlap.
- [Companies backed by Felicis](https://www.refolk.ai/companies/funded-by/felicis): Aydin Senkut's firm investing across software, healthcare, and consumer.
- [Companies backed by Redpoint Ventures](https://www.refolk.ai/companies/funded-by/redpoint): Multi-stage firm with strong enterprise SaaS and infrastructure presence.
- [Companies backed by Menlo Ventures](https://www.refolk.ai/companies/funded-by/menlo-ventures): Sand Hill venture firm investing in consumer, enterprise, and infra.
- [Companies backed by Coatue](https://www.refolk.ai/companies/funded-by/coatue): Crossover firm investing across late-stage venture and public technology.
- [Companies backed by Insight Partners](https://www.refolk.ai/companies/funded-by/insight-partners): Growth equity firm with an extensive software and ScaleUp practice.
- [Companies backed by GV (Google Ventures)](https://www.refolk.ai/companies/funded-by/google-ventures): Alphabet's venture arm investing across enterprise, consumer, life sciences, and AI.
- [Companies backed by NEA](https://www.refolk.ai/companies/funded-by/nea): One of the largest US venture firms, multi-stage across software and healthcare.
- [Companies backed by SV Angel](https://www.refolk.ai/companies/funded-by/sv-angel): Ron Conway's network - high-volume seed investments across consumer and enterprise.
- [Companies backed by Techstars](https://www.refolk.ai/companies/funded-by/techstars): Global accelerator with city-based programs and large alumni network.

## Repositories by language
- [Rust repositories](https://www.refolk.ai/repos/lang/rust): Memory-safe systems programming with zero-cost abstractions.
- [Go repositories](https://www.refolk.ai/repos/lang/go): Statically typed, compiled language designed for cloud-native services.
- [TypeScript repositories](https://www.refolk.ai/repos/lang/typescript): JavaScript with a static type system, the lingua franca of modern web apps.
- [Python repositories](https://www.refolk.ai/repos/lang/python): The default language of data science, machine learning, and automation.
- [JavaScript repositories](https://www.refolk.ai/repos/lang/javascript): The browser's native language, also widely used on the server via Node.js.
- [Java repositories](https://www.refolk.ai/repos/lang/java): Enterprise-grade JVM language behind much of the world's backend infrastructure.
- [Kotlin repositories](https://www.refolk.ai/repos/lang/kotlin): Modern JVM language, the preferred way to build for Android.
- [Swift repositories](https://www.refolk.ai/repos/lang/swift): Apple's primary language for iOS, macOS, and server-side applications.
- [C++ repositories](https://www.refolk.ai/repos/lang/cpp): High-performance systems language behind databases, browsers, and game engines.
- [C repositories](https://www.refolk.ai/repos/lang/c): The lingua franca of operating systems, compilers, and embedded devices.
- [C# repositories](https://www.refolk.ai/repos/lang/csharp): Microsoft's flagship .NET language for desktop, web, and game development.
- [Ruby repositories](https://www.refolk.ai/repos/lang/ruby): Developer-friendly dynamic language behind Rails and many indie web apps.
- [PHP repositories](https://www.refolk.ai/repos/lang/php): Powers a substantial fraction of the web, including WordPress and Laravel.
- [Elixir repositories](https://www.refolk.ai/repos/lang/elixir): Functional language on the Erlang VM, prized for fault tolerance and concurrency.
- [Erlang repositories](https://www.refolk.ai/repos/lang/erlang): Battle-tested language for distributed, fault-tolerant telecom systems.
- [Haskell repositories](https://www.refolk.ai/repos/lang/haskell): Pure functional language with a powerful type system.
- [OCaml repositories](https://www.refolk.ai/repos/lang/ocaml): Functional language behind compilers, formal methods, and quantitative finance.
- [Scala repositories](https://www.refolk.ai/repos/lang/scala): JVM language blending object-oriented and functional paradigms.
- [Clojure repositories](https://www.refolk.ai/repos/lang/clojure): Lisp on the JVM, popular for data-centric backend services.
- [Zig repositories](https://www.refolk.ai/repos/lang/zig): Modern systems language aimed at being a better C.
- [Nim repositories](https://www.refolk.ai/repos/lang/nim): Statically typed compiled language with Python-like syntax.
- [Crystal repositories](https://www.refolk.ai/repos/lang/crystal): Statically typed compiled language with Ruby-like ergonomics.
- [Dart repositories](https://www.refolk.ai/repos/lang/dart): Google's language behind Flutter, used for cross-platform apps.
- [Lua repositories](https://www.refolk.ai/repos/lang/lua): Lightweight embeddable scripting language used in games and Neovim.
- [Julia repositories](https://www.refolk.ai/repos/lang/julia): High-performance language for scientific computing and numerical work.
- [R repositories](https://www.refolk.ai/repos/lang/r): Statistical computing language widely used in academia and analytics.
- [Solidity repositories](https://www.refolk.ai/repos/lang/solidity): Smart contract language for the Ethereum Virtual Machine.
- [Shell repositories](https://www.refolk.ai/repos/lang/shell): POSIX shell scripts powering CLIs, dotfiles, and DevOps tooling.
- [Gleam repositories](https://www.refolk.ai/repos/lang/gleam): Type-safe functional language on the BEAM virtual machine.
- [Mojo repositories](https://www.refolk.ai/repos/lang/mojo): Python-superset systems language built for AI workloads.

## Repositories by topic
- [LLM repositories](https://www.refolk.ai/repos/topic/llm): Large language model frameworks, agents, runtimes, and inference servers.
- [AI agents repositories](https://www.refolk.ai/repos/topic/ai-agents): Autonomous and tool-using agent frameworks built around LLMs.
- [RAG repositories](https://www.refolk.ai/repos/topic/rag): Retrieval-augmented generation pipelines, embeddings, and grounding tooling.
- [Vector databases repositories](https://www.refolk.ai/repos/topic/vector-database): Embedding stores and approximate nearest-neighbour search engines.
- [Embeddings repositories](https://www.refolk.ai/repos/topic/embeddings): Models, libraries, and infrastructure for vector representations of text and media.
- [Transformers repositories](https://www.refolk.ai/repos/topic/transformers): Transformer model implementations, training kits, and finetuning tooling.
- [Fine-tuning repositories](https://www.refolk.ai/repos/topic/fine-tuning): Recipes, frameworks, and tools for adapting foundation models.
- [Machine learning repositories](https://www.refolk.ai/repos/topic/machine-learning): Libraries, models, and end-to-end systems for traditional and modern ML.
- [Deep learning repositories](https://www.refolk.ai/repos/topic/deep-learning): Neural network frameworks, training utilities, and model zoos.
- [Computer vision repositories](https://www.refolk.ai/repos/topic/computer-vision): Image and video understanding: detection, segmentation, generation.
- [Natural language processing repositories](https://www.refolk.ai/repos/topic/nlp): Tokenizers, classical NLP, and modern language model tooling.
- [Speech recognition repositories](https://www.refolk.ai/repos/topic/speech-recognition): ASR models and pipelines for converting audio to text.
- [Text-to-speech repositories](https://www.refolk.ai/repos/topic/text-to-speech): TTS models and inference servers for generating natural speech.
- [Kubernetes repositories](https://www.refolk.ai/repos/topic/kubernetes): Operators, controllers, dashboards, and ecosystem tools for Kubernetes.
- [Docker repositories](https://www.refolk.ai/repos/topic/docker): Containers, images, and Docker-adjacent developer tooling.
- [DevOps repositories](https://www.refolk.ai/repos/topic/devops): CI/CD, infrastructure-as-code, observability, and platform engineering.
- [Terraform repositories](https://www.refolk.ai/repos/topic/terraform): Modules, providers, and tooling around HashiCorp Terraform.
- [Observability repositories](https://www.refolk.ai/repos/topic/observability): Tracing, metrics, logs, and debugging tools for production systems.
- [CLI repositories](https://www.refolk.ai/repos/topic/cli): Command-line tools, terminal UIs, and shell utilities.
- [Terminal UI repositories](https://www.refolk.ai/repos/topic/tui): Rich text-based UIs and TUI frameworks for the terminal.
- [Static site generators repositories](https://www.refolk.ai/repos/topic/static-site-generator): Tooling for generating static websites from content sources.
- [Web frameworks repositories](https://www.refolk.ai/repos/topic/web-framework): Server-side and full-stack web application frameworks.
- [GraphQL repositories](https://www.refolk.ai/repos/topic/graphql): GraphQL servers, clients, and developer tooling.
- [REST APIs repositories](https://www.refolk.ai/repos/topic/rest-api): REST API servers, generators, and client libraries.
- [Databases repositories](https://www.refolk.ai/repos/topic/database): Relational, document, key-value, and time-series storage engines.
- [PostgreSQL repositories](https://www.refolk.ai/repos/topic/postgresql): Extensions, drivers, and tooling for the Postgres ecosystem.
- [Blockchain repositories](https://www.refolk.ai/repos/topic/blockchain): Chains, smart contracts, wallets, and on-chain tooling.
- [Ethereum repositories](https://www.refolk.ai/repos/topic/ethereum): Smart contracts, clients, and developer tools for the Ethereum stack.
- [Game engines repositories](https://www.refolk.ai/repos/topic/game-engine): 2D and 3D game engines, runtimes, and authoring tools.
- [Game development repositories](https://www.refolk.ai/repos/topic/game-development): Engines, libraries, sample games, and tools for game makers.
- [Android repositories](https://www.refolk.ai/repos/topic/android): Android apps, libraries, and developer tooling.
- [iOS repositories](https://www.refolk.ai/repos/topic/ios): iOS apps, libraries, and developer tooling.
- [React repositories](https://www.refolk.ai/repos/topic/react): React libraries, hooks, component kits, and developer tools.
- [Next.js repositories](https://www.refolk.ai/repos/topic/nextjs): Next.js apps, starters, and ecosystem libraries.
- [Vue repositories](https://www.refolk.ai/repos/topic/vue): Vue.js component libraries, frameworks, and starters.
- [Svelte repositories](https://www.refolk.ai/repos/topic/svelte): Svelte and SvelteKit component kits, libraries, and apps.
- [Tailwind CSS repositories](https://www.refolk.ai/repos/topic/tailwindcss): Tailwind plugins, component libraries, and design systems.
- [Design systems repositories](https://www.refolk.ai/repos/topic/design-system): Tokens, component libraries, and tooling for cohesive UI.
- [Low-code repositories](https://www.refolk.ai/repos/topic/low-code): Builders and platforms for rapid app development.
- [Automation repositories](https://www.refolk.ai/repos/topic/automation): Workflow automation, RPA, and scripting frameworks.
- [Monitoring repositories](https://www.refolk.ai/repos/topic/monitoring): Tools for monitoring application health, infrastructure, and SLAs.
- [Security repositories](https://www.refolk.ai/repos/topic/security): Offensive and defensive security tools and libraries.
- [Cryptography repositories](https://www.refolk.ai/repos/topic/cryptography): Crypto primitives, protocols, and zero-knowledge tooling.
- [Compilers repositories](https://www.refolk.ai/repos/topic/compiler): Front-ends, back-ends, and language toolchains.
- [Operating systems repositories](https://www.refolk.ai/repos/topic/operating-system): Kernels, microkernels, and OS research projects.
- [Robotics repositories](https://www.refolk.ai/repos/topic/robotics): Control, perception, simulation, and ROS-ecosystem code.
- [Data science repositories](https://www.refolk.ai/repos/topic/data-science): Notebooks, analysis libraries, and data tooling.
- [Data engineering repositories](https://www.refolk.ai/repos/topic/data-engineering): Pipelines, orchestrators, and ELT/ETL tooling.
- [Self-hosted repositories](https://www.refolk.ai/repos/topic/self-hosted): Apps and services designed to be run on your own infrastructure.
- [Open source repositories](https://www.refolk.ai/repos/topic/open-source): Notable open-source projects across every category.

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## Optional
- [Sitemap](https://www.refolk.ai/sitemap.xml): Full URL inventory, including combined industry, stage, location, and investor pages.