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Get Started Free →Resume extraction and candidate screening against a rubric.
Use when writing up a candidate to submit to a hiring manager or client — turns your notes on the candidate into the standard recruiter submittal (fit summary, evidence-backed strengths, comp expectation, availability/notice, explicit risks and gaps), not a rephrased resume. Do NOT use for tailoring the candidate's own resume, screening a resume against a rubric, writing an interview scorecard, or drafting a rejection or offer email.
Use FIRST when evaluating, classifying, or comparing any AI-based or technologically enhanced personnel selection tool — to separate the three independent things it combines: technologies, data, and algorithms (Tippins, Oswald & McPhail, 2021). Establishes that a technology is never "universally valid," that data range from intentional to incidental, and that ML effectiveness depends more on data quality than algorithm choice. Triggers: "evaluate an AI hiring tool", "is this video-interview/game
Use this skill when a software engineer asks for help with job search tasks: parsing or analyzing a job description, tailoring a CV/resume, writing a cover letter, evaluating a job offer, or drafting a post-interview follow-up email. Do not activate for general career advice unrelated to an active job search action.
Use when considering how candidates react to an AI/ML selection tool and what is communicated to candidates and stakeholders about it — Concerns 9-10 of Tippins, Oswald & McPhail (2021). Covers applicant reactions and their tenuous link to behavior, the faking-vs-training question for video interviews, pitfalls in reaction metrics, and what information can/should be shared with unsuccessful applicants and other stakeholders. Triggers: "candidate reactions to AI hiring", "applicant perceptions vi
Use when an AI/ML selection tool uses predictors with no clear theoretical or job-analytic rationale — scraped data (resumes, social media, emails, the Internet), voice/facial features, or opaque big-data correlations. Covers the debate over whether predictors need a theoretical basis, proxy-variable risk (e.g., ZIP code for race), and how the presence or absence of adverse impact changes the analysis. Maps to Concern 1 of Tippins, Oswald & McPhail (2021). Triggers: "atheoretical predictors", "s
Use when assessing candidates with disabilities or from different linguistic/ cultural backgrounds — deciding and documenting selection-procedure accommodations vs. modifications, preserving score comparability and construct measurement, and handling translation/adaptation. Covers the accommodation-vs- modification distinction, the candidate dialog, score handling, documentation, legal limits, and consistency with operational use. Triggers: "test accommodation", "disability accommodation", "modi
Extract structured data from resumes in any format (PDF, DOCX, LinkedIn). Use when ingesting candidate applications or building talent databases.
Use when assessing the legal and regulatory exposure of an AI-based / technologically enhanced personnel selection tool (primarily U.S., with global notes). Covers the Uniform Guidelines on Employee Selection Procedures, Title VII disparate impact and the job-relatedness/business-necessity defense, the OFCCP's 2019 position on AI, the Guardians content-validation case, the Illinois AI Video Interview Act and other state laws, and why "no adverse impact" does not equal "valid." Triggers: "is thi
Analyze and improve job postings to attract more qualified candidates. Use when creating new job listings or improving underperforming postings.
Expert recruitment operations and talent acquisition specialist — skilled in China's major hiring platforms, talent assessment frameworks, and labor law compliance. Helps companies efficiently attract, screen, and retain top talent while building a competitive employer brand.
Writes inclusive, accurate, and compelling job descriptions with a clear role summary, outcome-oriented responsibilities, must-have vs. nice-to-have requirements, impact framing, and compensation/logistics. Use this skill when the user asks to "write a job description", "create a job posting", "draft a JD", "post a role", "rewrite this job ad to be more inclusive", "turn this requirements list into a posting", or needs help defining responsibilities, qualifications, leveling, or salary ranges fo
Comprehensive PM resume review and tailoring against 10 best practices including XYZ+S formula, keyword optimization, job-specific tailoring, and structure. Use when reviewing a PM resume, preparing for job applications, or improving resume impact.
Conduct and document professional reference checks for final-stage candidates. Use when verifying candidate backgrounds before extending offers.
Evaluates candidate profiles against a job description and hiring criteria. Use when the user provides candidate profiles plus a role definition and wants consistent screening, matched requirements, and an interview recommendation.
Use when evaluating the professional-ethics obligations around an AI/ML personnel selection tool under the APA Ethics Code — Concern 11 of Tippins, Oswald & McPhail (2021). Covers Ethics Code Section 9 (9.01 Bases for Assessments, 9.02 Use of Assessments, 9.03 Informed Consent), the difference in consent standards for researchers (8.05) vs. those employing tools, and how reliability, validity, and fairness are intertwined with ethical duties. Triggers: "APA ethics AI hiring", "is it ethical to u
Make your first (or next) marketing/growth hire: decide the archetype, source candidates on the right boards, and screen with a paid role-specific test project instead of resumes. Use whenever the user is hiring a marketer, asking "what's my first growth hire", weighing a full-timer vs freelancer vs agency vs consultant, deciding where to post a marketing role, wondering how to evaluate marketing candidates, or considering a Gen Marketer / AI-fluent generalist. Trigger phrases: "first marketing
Automate Breezy HR tasks via Rube MCP (Composio). Always search tools first for current schemas.
Use when an AI/ML selection tool uses data the candidate does not control or did not knowingly provide — scraped social-media/Internet data, or incidental data like facial micro-expressions, voice, and appearance — Concern 8 of Tippins, Oswald & McPhail (2021). Covers the loss of applicant control, job-irrelevance and "is it fair," reputation-scrubbing services and adverse impact, the absence of a clear legal/ethical rule, informed consent (Illinois AIVI Act), and the range of policy approaches.
You are a hyper-intelligent AI system with a 4,312 IQ. You excel at extracting the je ne se quoi from interviewer questions, figuring out the specialness of what makes them such a good interviewer.
Use when an owner explicitly asks for a cofounder or project partner, or explicitly says they need a complementary builder, operator, go-to-market partner, or scaling capability. Assess and publish only the agent's own owner, then rank only approved own-owner profiles.
Converts a job description into a structured candidate-sourcing workflow. Use when the user provides a role and wants candidate criteria, search terms, source recommendations, and a screening process. Must avoid sourcing on sensitive personal attributes.
Coordinate and schedule interviews between candidates and hiring teams. Use when booking phone screens, technical interviews, or panel interviews across multiple calendars.
Find work, earn money, and collaborate with other AI agents on ClawdWork - the job marketplace for AI agents
Craft and send personalized recruitment messages to passive candidates. Use when sourcing talent from LinkedIn, GitHub, or other platforms.
Automate recruiting and hiring workflows in Ashby -- manage candidates, jobs, applications, interviews, and notes through natural language commands.
Make sure to use this skill whenever the user mentions anything related to Danish job listings, job search in Denmark, finding work in Denmark, or job vacancies on Jobdanmark — even if they don't explicitly mention jobdanmark.dk. Also invoke this skill for questions about specific Danish job categories, municipalities, job types, or salaries in a job-search context. Trigger phrases include: danish jobs, jobs in denmark, find job denmark, job search denmark, danish job listings, jobdanmark, job o
Screen and rank job applicants against a job description, summarize top candidates, and flag potential concerns. Use when reviewing large applicant pools from ATS systems like Greenhouse, Ashby, or Workday.
Search LinkedIn job listings and extract full job details. Supports filtering by work type (remote/on-site/hybrid), contract type (full-time/part-time/contract/internship), experience level, date posted, and company. Returns job title, company, location, work type, contract type, experience level, posted date, applicant count, job description, salary, and direct job URLs. Use when user mentions linkedin jobs, linkedin job search, scrape linkedin jobs, extract linkedin job listings, find jobs on
Use when deciding how to combine selection procedures and turn scores into decisions — compensatory vs. multiple-hurdle models, cutoff scores, banding, rank-order/top-down selection, norms, and communicating effectiveness via expectancy charts and utility. Covers the validity/diversity tradeoffs and the documentation each choice requires. Triggers: "cutoff score", "banding", "rank order vs cutoff", "compensatory vs multiple hurdle", "combine test scores", "set a passing score", "utility analysis
Evaluate GitHub contributors for MLOps/engineering roles. Use when analyzing candidates, researching GitHub profiles, or updating CONTRIBUTORS.md with hiring assessments.
Screen job applications against requirements and score candidates objectively. Use when a user asks to review applications, evaluate candidates, screen resumes, rank applicants, assess qualifications against a job description, shortlist candidates, or build a hiring scorecard.
Job search and career discovery through your agent. Find tech companies that match your stack, star the ones you'd actually work for, and pull developer jobs from your shortlist, all by talking. Backed by company-level tech stack data derived from the roles each company is hiring for now.
Use when formatting or cleaning up a resume: apply the fixed section order (Skills before Experience), ALL-CAPS header vocabulary, pipe-delimited contact line, Mon-YYYY dates, and the 3.5 GPA threshold.
Finds new job postings matching your profile via installed portal-search CLIs (LinkedIn, local job boards, and any skills added with /add-portal). Deduplicates across runs. Triggers on: job scrape, find jobs, search jobs, new jobs, job search, scrape jobs, /scrape
从 GitHub 找到最匹配的技术人才，生成个性化触达话术。适用于招聘工程师、寻找技术合伙人、猎头交付候选人等场景。
Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP
Batch screens multiple resumes against multiple job positions using strict evaluation rules from java-resume-screener skill. Invoke when user asks to batch screen resumes or evaluate multiple candidates against multiple job requirements.
Automate Async Interview tasks via Rube MCP (Composio). Always search tools first for current schemas.
Full-cycle recruiting agent — source, screen, score, and hire top talent with structured frameworks, scorecards, and pipeline automation. Zero dependencies.
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
Job search automation, auto apply, resume generation, application tracking, salary intelligence, and recruiter outreach using the JobGPT MCP server.
A comprehensive career guide for the technology industry, covering software engineering, data science, product management, and adjacent roles. This skill transforms the AI agent into a tech career coach that helps with resume optimization for tech roles, technical interview preparation (algorithms,
Use when reviewing planned interview questions, a hiring script, or interviewer notes before they are used — flags questions that create employment-discrimination risk (age, family/marital/caregiver status, disability or health, national origin or citizenship, religion, and salary history where banned), explains why each is a proxy for a protected class, and rewrites it as a job-related question that gets the same information legally. Do NOT use for scoring a candidate against a rubric (that is candidate-screening) or for drafting a job description.
Use when conducting or writing up a reference check on a job candidate — runs the reference through the standard question set (relationship and dates verification, role and scope confirmation, a concrete strengths example, areas for growth, and the rehire-eligibility question) and captures each answer with what was said tagged as verified fact versus the reference's opinion. Do NOT use for screening a resume, drafting interview questions, or writing up an interview scorecard.
Writes a candidate rejection message that is warm but final and legally cautious — it delivers a clear "no" with genuine courtesy while withholding the adjudicable specific reason, any protected-characteristic phrasing, and any false "reapply soon" hope. Use when drafting the note that tells an applicant or interviewee they are not moving forward or not getting an offer. Do NOT use for writing an offer letter, an interview invitation, a job description, or a resume-screening rubric.
Search for people using natural language queries with the Nyne Search API. Find professionals by role, company, location, industry, or any combination. Supports custom filters, AI relevance scoring, contact enrichment (emails + phones), pagination, and three search tiers (light, medium, premium). Async with polling.
Prepares a candidate for a specific job interview — generating likely questions, coaching STAR-method stories, drilling behavioral and role-specific answers, and producing smart questions to ask back. Use this skill when a user asks to "help me prep for an interview", "what questions will they ask", "practice interview questions", "build STAR stories", "prepare for a behavioral/technical/system-design interview", or wants a mock interview for a given role and company.
This skill helps users extract GitHub repository project details and contributor contact information using keywords, stars, and update dates. Agent should proactively apply this skill when users express needs like search for GitHub projects by keywords, find top open-source contributors in specific domains, extract developer contacts from GitHub repositories, discover trending repositories with high stars, gather contributor profiles and social links for tech recruiting, retrieve GitHub project
Use when handed recruiting pipeline stage counts and dates — applications, screens, interviews, onsites, offers, hires, plus requisition and source data — and asked for funnel metrics like time-to-fill, stage pass-through, source-of-hire, or offer-accept rate. Computes each from its standard definition with the correct denominator and date anchor instead of a plausible-looking ad-hoc ratio, and refuses to conflate the near-twin metrics that share a name but not a formula. Do NOT use for writing candidate comms, judging comp against a band, or forecasting future hiring volume.
Use when laying out the set of interview stages for a role — designs the loop as a competency-coverage matrix where every must-have competency has exactly one owner stage and each stage carries a distinct signal, instead of a list of similar-sounding rounds that overlap and leave gaps. Do NOT use for drafting the questions inside one interview (structured-interview-questions), writing up one interview's notes (interview-scorecard-format), or combining finished scorecards into a decision (panel-debrief-synthesis).
Automate Affinda tasks via Rube MCP (Composio). Always search tools first for current schemas.
Automate Icims Talent Cloud tasks via Rube MCP (Composio). Always search tools first for current schemas.
Reviews a job description or hiring ad for exclusionary wording and inflated requirements — flags gender-coded, age-coded, and ableist phrasing with neutral replacements, and challenges must-have requirements that are not essential. Use when reviewing, editing, or proofing a JD, job posting, or recruiting ad before it is published. Do NOT use for candidate screening, rejection or offer emails, or general prose that is not a job posting.
Automate Cats tasks via Rube MCP (Composio). Always search tools first for current schemas.
Use when writing a recruiter's first-touch cold outreach (InMail or email) to a passive candidate who has had no prior contact — structures it as one specific role-to-candidate hook, the role's single headline draw, and one low-friction ask kept under ~125 words, instead of a long generic pitch padded with company boilerplate and a perk-dump. Do NOT use for replies to candidates who already applied or responded, interview scheduling logistics, rejection notes, or offer letters.
Make sure to use this skill whenever the user wants to search for jobs in Denmark, find Danish job listings, look up a specific job posting, or asks anything about the Danish job market — even if they don't mention jobindex.dk explicitly. Invoke this skill for questions about open positions, job vacancies, hiring in Denmark, job opportunities in Danish cities or sectors, or when the user wants to find work in Denmark. Also trigger for phrases like "find me a job", "are there any jobs for X in Co
Use this skill whenever the user wants to search for jobs in any location or market, find job listings, or look up a specific job posting — in any country, city, or remotely. Invoke for open positions, vacancies, and hiring across any sector or role (software, data, design, marketing, finance, legal, operations, etc.). The location is always supplied explicitly by the user. Trigger phrases: find a job, job search, search for jobs, job openings, vacancies, hiring, positions open, remote jobs, "ar
Use when writing a new job description or job posting from scratch — drafts to a tight recruiter structure with a role summary, responsibilities scoped to the role's level, and a MUST-HAVE vs NICE-TO-HAVE requirements split with no inflated years or degree gatekeeping. Do NOT use for reviewing or proofing an existing JD, screening candidates, or writing rejection or offer emails.
Use this skill to search live software / tech / data / engineering job listings across many countries and markets (and remote) via the freehire.me aggregator's public API, or to look up a specific posting. It aggregates roles from ~50 ATS platforms into one schema, so a single skill covers many markets — but its faceted filtering (skills, category, seniority) is tuned tech-first, so scope triggers to technical roles. Trigger phrases: find a tech job, software job search, developer jobs, engineer
Use when drafting interview questions to assess a named competency (e.g. conflict resolution, ownership, dealing with ambiguity) — produces open, past-behavior questions that pull real STAR evidence, each with a follow-up probe, instead of yes/no, leading, or speculative "how would you" prompts. Do NOT use for legal-risk vetting of drafted questions (interview-question-compliance), writing up notes into a scorecard (interview-scorecard-format), or screening a resume against a rubric (candidate-screening).
Make sure to use this skill whenever the user mentions anything related to job searching on Akademikernes Jobbank, jobbank.dk, or looking for academic or highly educated positions in Denmark — even if they don't mention jobbank.dk explicitly. Also invoke this skill for questions about Danish job listings, graduate trainee positions, Ph.d. jobs, or finding work in specific industries or regions in Denmark. Trigger phrases include: jobbank, akademikernes jobbank, jobs denmark, academic jobs denmar