Headhunter Pro is an AI-assisted, end-to-end recruitment operating system for talent mapping, candidate evaluation, outreach, hiring analytics, and post-hire support.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install headhunter-pro-link
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install headhunter-pro-link using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Headhunter Pro?
Headhunter Pro v17.0 packages a complete recruiter workflow into a structured skill for OpenClaw: diagnose talent gaps, define success profiles, build talent maps, source candidates, screen resumes, validate evidence, write recommendation reports, manage outreach, support interviews, negotiate offers, and track onboarding. Its guiding principle is AI for longlists and human judgment for shortlists.
The skill is designed for executive search, technical recruiting, talent advisory, and Chinese-market recruitment workflows. It combines JTIF job-to-talent analysis, nine-dimension scoring, BEI/STAR interviews, GitHub proof-of-work validation, PMCC outreach, pipeline state management, Silver Medalist re-engagement, hiring-signal monitoring, ROI reporting, and six-month onboarding follow-up. Openclaw Skills users gain reusable templates and decision checkpoints without treating AI output as a substitute for professional judgment.
Headhunter Pro Use Cases
- Analyze a hiring manager's business need before accepting or rewriting a job description.
- Build industry talent maps with Tier 1, Tier 2, and Tier 3 target companies.
- Generate candidate personas covering hard skills, soft skills, motivations, communication style, and career stage.
- Batch-screen resumes against a job description with nine-dimension scoring and A/B/C prioritization.
- Validate technical candidates through GitHub repositories, commits, pull requests, collaboration patterns, and proof of work.
- Create structured recommendation reports with JD alignment, career highlights, motivation analysis, compensation context, risks, and interview guidance.
- Plan personalized cold outreach, warm introductions, follow-ups, and low-pressure 10–15 minute calls.
- Maintain candidate records, communication history, job-search status, next follow-up dates, and referral potential.
- Re-engage dormant ATS candidates and Silver Medalists when new roles or trigger events appear.
- Conduct BEI/STAR interviews, work-sample assessments, reference checks, and leadership-risk reviews.
- Design total-compensation packages covering base pay, bonus, equity, benefits, notice periods, and non-compete considerations.
- Track pipeline conversion, time-to-fill, offer acceptance, retention, channel ROI, and candidate experience.
- Support 30/60/90-day and six-month onboarding follow-up with risk alerts and retention signals.
How Headhunter Pro Works
- Diagnose the role: Extract the business objective, organizational bottleneck, role necessity, budget, timeline, and success definition before relying on the JD.
- Define the success profile: Separate minimal requirements from preferred requirements and document hard skills, soft skills, motivations, exclusions, target companies, and communication preferences.
- Map the market: Build a talent map across direct competitors, adjacent industries, transferable talent pools, technical ecosystems, and referral networks.
- Prioritize sourcing: Check the existing candidate database first, then select channels such as ATS records, recruitment platforms, Boolean search, referrals, LinkedIn, industry communities, or GitHub.
- Build the longlist: Use AI-assisted search and batch resume triage to identify candidates, while cross-checking relevant information across available sources.
- Score and validate: Apply the nine-dimension evaluation model, add technical or AI-native capability where relevant, verify evidence, and identify gaps or risk signals.
- Create the shortlist: Keep the shortlist focused, generally within the recommended 5–12 candidate range, and require a clear explanation for why each person is recommended.
- Generate the recommendation report: Produce the five-part report with JD comparison, career stories, motivation depth, compensation, scorecard, risks, interview questions, and market context.
- Engage candidates: Select a PMCC communication strategy—Probe, Match, Confirm, Close—then use personalized, value-first messaging and a scheduled multi-touch follow-up sequence.
- Manage interviews and offers: Coordinate interviews, BEI/STAR evaluation, work samples, references, feedback SLAs, offer analysis, compensation design, and candidate expectation management.
- Close the loop: Start onboarding support immediately after acceptance, monitor 30/60/90-day and six-month signals, and escalate culture, leadership, performance, or expectation risks.
- Learn from the pipeline: Update candidate records, classify Warm Keep and Silver Medalist candidates, measure conversion and ROI, and refresh talent maps on weekly, monthly, quarterly, or event-driven schedules.
Headhunter Pro Setup
Compatibility
- OpenClaw 1.x+
- Claude Code and Cursor-compatible SKILL.md format
- Python 3.10+ recommended for optional voice-processing workflows
- The core skill uses file operations and text generation; the metadata states that it does not require external network calls.
Install the skill
Place the skill directory and its SKILL.md file in a personal or project-level skills directory:
mkdir -p ~/.openclaw/skills/headhunter-pro
# Copy SKILL.md and any reference files into ~/.openclaw/skills/headhunter-pro/
For a project-scoped installation:
mkdir -p ~/.agents/skills/headhunter-pro
# Copy SKILL.md and reference files into ~/.agents/skills/headhunter-pro/
Restart or reload the agent runtime, then invoke the skill with a specific task, for example:
Batch-screen these resumes against the following JD and return a CSV with nine-dimension scores.
Optional GitHub validation
GitHub sourcing is an optional workflow and requires separate authentication and permission review:
gh auth login
export GITHUB_TOKEN="your_personal_access_token"
Use only authorized, publicly available information and follow applicable platform terms, privacy requirements, and consent rules. GitHub commands such as gh search repos, gh search commits, and gh search prs can support technical proof-of-work validation, but they should not replace human review.
Optional voice workflow
For local VibeVoice experiments, the source document recommends Python 3.10+ and Transformers 4.50.0 or later:
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade transformers torch torchaudio soundfile
Validate the workflow in an authorized local or hosted environment before processing sensitive interview recordings.
Headhunter Pro Data Schema & Taxonomy
Candidate and pipeline records
| Entity or file | Purpose | Typical fields |
|---|---|---|
profile.md |
Canonical candidate profile | Identity, career history, skills, motivations, career plan, communication style, job-search status, persona, Silver Medalist status |
follow-ups.md |
Interaction and follow-up log | Contact date, channel, touch count, response, candidate language, next action, next follow-up date, SLA status |
recommendation.md |
Candidate recommendation and decision record | JD alignment, career highlights, motivation analysis, compensation, nine-dimension score, risks, interview advice, negotiation notes |
nine-dimension.md |
Scoring rubric reference | Education, experience, skill overlap, industry relevance, management fit, culture fit, stability risk, compensation fit, diversity or domain insight |
recommendation-report-v3.md |
Report structure reference | Five-part recommendation format, evidence, market context, interview recommendations, and risk forecast |
crm-engagement-scoring.md |
Relationship health model | Communication frequency, trust depth, delivery quality, commercial value, information access, and engagement score |
brief-drift-detection.md |
Requirement-change monitoring | Original brief, changed requirements, source of change, impact, and corrective action |
executive-6d-deep.md |
Executive assessment | Decision style, conflict management, team enablement, change leadership, cultural sensitivity, resilience, and self-awareness |
onboarding-90day-deep.md |
Post-hire follow-up | 30/60/90-day checkpoints, retention signals, expectation gaps, culture fit, leadership relationship, and escalation status |
talent-pool-activation.md |
Dormant and Silver Medalist operations | Re-engagement date, matching role, prior outcome, next touch, referral request, and trigger event |
Pipeline taxonomy
Identified → Contacted → Responded → Interested → Screening → Submitted → Interview → Offer → Closed
Important side paths include No response → Warm Keep and Not hired after strong interview → Silver Medalist. Candidate records may also use relationship grades A, B, C, D, and Silver, plus activity states such as active, passive, observing, or locked.
Operational metadata
- Candidate type: high-cold, high-knowledge, high-defense, open, or observing.
- Candidate status: active, passive, observing, locked, or Silver Medalist.
- Evidence sources: resume, LinkedIn or equivalent profile, GitHub, references, work sample, interview transcript, and compensation discussion.
- Timing metadata: last contact, touch count, next contact, response SLA, interview feedback SLA, offer decision window, and onboarding checkpoint.
- Trigger events: funding, IPO, executive change, restructuring, product launch, technology change, competitor expansion, policy change, promotion, or project completion.
- Reporting outputs: CSV triage tables, Markdown profiles, recommendation reports, market intelligence briefs, pipeline dashboards, ROI comparisons, and onboarding evaluations.
Headhunter Pro Advanced Features
- Talent Gap Analysis: Uses the JTIF model—Job, Talent, Interview, Follow-up—to translate business problems into a realistic hiring profile.
- Multi-source validation: Combines resumes, professional profiles, GitHub activity, references, work samples, and interview evidence rather than relying on keyword matching alone.
- Technical ecosystem sourcing: Maps technologies, dependencies, frameworks, communities, maintainers, and contributors before searching for candidates.
- AI-native capability assessment: Adds L1–L4 evaluation for AI tool users, AI application developers, AI systems engineers, and AI architects.
- Three-persona collaboration: Sourcer creates the longlist, Coordinator maintains records and follow-ups, and Coach reviews outreach and interview preparation before human final decisions.
- Anti-Rationalization controls: Checklists prevent skipped steps such as motivation discovery, compensation confirmation, reference validation, JD alignment, and candidate-status updates.
- Pipeline state machine: Every stage has defined actions, deliverables, SLAs, and transition rules for measurable recruiting operations.
- Dormant-candidate activation: Automatically identifies candidates inactive for more than 90 days, matches them to new roles, and prioritizes Silver Medalists.
- Event-driven recruiting: Converts company funding, leadership changes, restructuring, product launches, and technology signals into timely sourcing recommendations.
- Outreach orchestration: Supports warm introductions, cold calls, email, LinkedIn, messaging apps, value-first content, 3-touch sequences, and long-term Warm Keep relationships.
- Candidate experience measurement: Tracks response speed, personalization, transparency, respect, feedback timeliness, and overall experience scores.
- Offer architecture: Models base salary, bonuses, equity, benefits, signing compensation, notice periods, non-compete constraints, and total-package trade-offs.
- Onboarding risk monitoring: Extends support beyond placement with six-month integration tracking, red-yellow-green indicators, and escalation rules.
- Recruiting analytics: Measures funnel conversion, hitting rate, time-to-fill, channel ROI, offer acceptance, retention, quality of hire, and cost per successful hire.
- Human-in-the-loop governance: Openclaw Skills automation drafts, ranks, reminds, and organizes; the recruiter retains responsibility for shortlist decisions, consent, compliance, fairness, and final recommendations.
SKILL.md
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