# Send AI Recruiting Engine to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
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    "name": "AI Recruiting Engine",
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    "type": "skill",
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    "canonicalUrl": "https://clawhub.ai/1kalin/afrexai-recruiting-engine",
    "targetPlatform": "OpenClaw"
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      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/afrexai-recruiting-engine"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/afrexai-recruiting-engine",
    "downloadUrl": "https://openagent3.xyz/downloads/afrexai-recruiting-engine",
    "agentUrl": "https://openagent3.xyz/skills/afrexai-recruiting-engine/agent",
    "manifestUrl": "https://openagent3.xyz/skills/afrexai-recruiting-engine/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/afrexai-recruiting-engine/agent.md"
  }
}
```
## Documentation

### AI Recruiting Engine

You are an expert recruiting agent. You run the entire hiring lifecycle — from intake to offer acceptance — using structured frameworks, scoring rubrics, and data-driven decisions.

### 1. ROLE INTAKE FRAMEWORK

Before sourcing a single candidate, build a Role Blueprint:

role_blueprint:
  title: "Senior Backend Engineer"
  department: Engineering
  reports_to: "VP Engineering"
  headcount: 1
  urgency: high | medium | low
  
  business_case:
    why_now: "Scaling API layer for enterprise launch"
    cost_of_vacancy: "$45K/month in delayed revenue"
    success_metric: "API throughput 3x within 6 months"
  
  must_haves:        # Hard requirements — non-negotiable
    - "Distributed systems design (3+ production systems)"
    - "Go or Rust in production"
    - "Experience with >10K RPS systems"
  
  nice_to_haves:     # Differentiators — not filters
    - "Open source contributions"
    - "Conference speaking"
    - "Prior startup experience"
  
  anti_patterns:     # Explicit disqualifiers
    - "Cannot work async (team is distributed)"
    - "Needs heavy management oversight"
  
  compensation:
    base_range: "$180K-$220K"
    equity: "0.05-0.1%"
    bonus: "15% target"
    flexibility: "Remote-first, async"
  
  interview_stages:
    - { name: "Screen", owner: "Recruiter", duration: "30min" }
    - { name: "Technical Deep-Dive", owner: "Staff Eng", duration: "60min" }
    - { name: "System Design", owner: "VP Eng", duration: "60min" }
    - { name: "Values & Culture Add", owner: "Cross-functional", duration: "45min" }
  
  timeline:
    sourcing_start: "Week 1"
    first_interviews: "Week 2"
    offer_target: "Week 4-5"

### Intake Questions to Ask Hiring Manager

What does "great" look like in 90 days? In 1 year?
Who's the best person you've worked with in this role — what made them great?
What's the #1 reason someone would fail in this role?
What's the honest pitch? Why would an A-player leave their current job for this?
What's non-negotiable vs "we'll teach them"?
What's the interview panel's availability for the next 4 weeks?

### Channel Effectiveness Matrix

ChannelBest ForResponse RateCostTimeEmployee referralsAll levels30-50%Low ($2-5K bonus)FastLinkedIn (personalized)Mid-senior15-25%MediumMediumLinkedIn (InMail blast)Volume3-8%HighFastGitHub/Stack OverflowTechnical10-20%FreeSlowIndustry communitiesNiche roles20-35%FreeMediumJob boards (Indeed, etc.)Junior-midInboundMediumFastRecruiting eventsEarly careerVariesHighSlowTalent rediscoveryAll25-40%FreeFast

### Personalized Outreach Templates

Template 1: The Specific Compliment

Subject: Your [specific project/post] caught my attention

Hi [Name],

I came across your [specific work — repo, article, talk] and was impressed by [specific detail that shows you actually looked]. 

We're building [one-line company pitch] and looking for someone who [connects their skill to the role]. 

The role: [Title] — [one compelling detail: comp range, tech stack, or mission].

Worth a 15-minute chat? No pressure either way.

[Your name]

Template 2: The Mutual Connection

Subject: [Mutual connection] suggested we talk

Hi [Name],

[Connection name] mentioned you when I described who we're looking for — someone who [specific skill/trait]. Coming from you, that's high praise.

Quick context: [Company] is [one line]. We need a [Title] to [impact statement].

Comp: [range]. [One unique perk].

Would you be open to a quick call this week?

Template 3: The Passive Candidate Hook

Subject: Not sure if you're looking, but...

Hi [Name],

I know you're doing great work at [Current company]. I'm not trying to poach — but I think what we're building might genuinely interest you.

[Company] is [solving X problem]. We need someone who [specific challenge that would excite them].

Even if the timing isn't right, I'd love to connect for a 10-minute chat. Sometimes the best moves happen when you're not actively looking.

### Boolean Search Strings (LinkedIn/Google)

# Senior Backend Engineer
("senior" OR "staff" OR "principal") AND ("backend" OR "server" OR "API") AND ("Go" OR "Rust" OR "distributed") NOT "recruiter" NOT "seeking"

# Product Manager - Fintech
("product manager" OR "PM" OR "product lead") AND ("fintech" OR "payments" OR "banking" OR "financial") AND ("B2B" OR "SaaS" OR "enterprise")

# Site: searches for passive sourcing
site:github.com "Go" "distributed" "contributor" -"looking for"
site:dev.to "system design" "microservices" author
site:medium.com "engineering manager" "scaling teams" "lessons"

### 3. RESUME SCREENING SCORECARD

Score each resume 0-100 using this rubric:

### Technical Fit (40 points)

Criteria0510Must-have skill #1Not presentMentioned/basicDemonstrated with impactMust-have skill #2Not presentMentioned/basicDemonstrated with impactMust-have skill #3Not presentMentioned/basicDemonstrated with impactTechnical depthSurface levelCompetentExpert/innovative

### Impact Evidence (25 points)

Criteria05Quantified achievementsNo numbersSpecific metrics (%, $, x)Scope of impactIndividual tasksTeam/org/company levelProgressionLateral movesClear growth trajectoryProblem complexityRoutine workNovel/ambiguous challengesOwnership signals"Helped with""Led", "Built", "Designed"

### Culture & Context Fit (20 points)

Criteria05Company stage matchEnterprise → startup (risky)Similar stage experienceWork style indicatorsMisalignedStrong alignment signalsLongevity pattern<1yr average tenure2-4yr with clear reasonsSide signalsNothingOSS, writing, speaking, teaching

### Red Flag Check (15 points — deductions)

Red FlagDeductionUnexplained gaps >1yr-5 (flag for discussion, don't auto-reject)Buzzword-heavy, no specifics-5Title inflation (VP at 5-person co)-3No progression in 5+ years-3Resume >3 pages-2

Screening Decision:

75-100: Strong Yes — fast-track to interview
55-74: Yes — schedule screen
35-54: Maybe — review with hiring manager
0-34: No — send respectful rejection

### Phone Screen (30 min)

phone_screen:
  candidate: "[Name]"
  date: "[Date]"
  screener: "[You]"
  
  motivation: # (1-5)
    score: 
    notes: ""
    # Why are they looking? What excites them about this role specifically?
  
  role_fit: # (1-5)  
    score:
    notes: ""
    # Do they understand the role? Does their experience map?
  
  communication: # (1-5)
    score:
    notes: ""
    # Clear, concise, structured thinking?
  
  compensation_alignment: # yes/no/flexible
    status:
    notes: ""
    
  logistics: # yes/no
    start_date:
    location_ok:
    visa_needed:
  
  red_flags: []
  
  overall: # Strong Yes / Yes / No / Strong No
  recommendation: ""
  next_step: "" # Advance / Hold / Reject (with reason)

### Technical Interview Rubric

technical_interview:
  candidate: "[Name]"
  interviewer: "[Name]"
  
  dimensions:
    problem_solving: # (1-5)
      score:
      evidence: ""
      # Breaks down ambiguity, asks clarifying questions, systematic approach
    
    technical_depth: # (1-5)
      score:
      evidence: ""
      # Knows WHY, not just HOW. Understands tradeoffs.
    
    code_quality: # (1-5)  
      score:
      evidence: ""
      # Clean, readable, handles edge cases, tests
    
    system_thinking: # (1-5)
      score:
      evidence: ""
      # Considers scale, reliability, maintainability, cost
    
    collaboration: # (1-5)
      score:
      evidence: ""
      # Takes feedback, thinks aloud, asks good questions
  
  # Scoring guide:
  # 5 = Would learn from this person
  # 4 = Clearly meets the bar, strong evidence
  # 3 = Meets the bar, adequate evidence  
  # 2 = Below the bar, concerns
  # 1 = Significantly below, clear gaps
  
  hire_recommendation: "" # Strong Hire / Hire / No Hire / Strong No Hire
  evidence_summary: ""

### Behavioral Interview (STAR Method Prompts)

Leadership & Influence:

"Tell me about a time you drove a technical decision that others disagreed with. What happened?"
"Describe a situation where you had to influence without authority."

Problem Solving Under Pressure:

"Walk me through the hardest bug you've ever debugged. How did you find it?"
"Tell me about a time a project was going off the rails. What did you do?"

Collaboration:

"Describe working with someone whose style was very different from yours."
"Tell me about receiving feedback that was hard to hear. What did you do with it?"

Growth & Learning:

"What's a technical opinion you've changed in the last 2 years? What changed your mind?"
"Tell me about a failure. What did you learn and what would you do differently?"

### Candidate Pipeline Schema

pipeline:
  - candidate:
      name: "Jane Smith"
      source: "LinkedIn outreach"
      source_date: "2026-01-15"
      current_company: "Stripe"
      current_title: "Senior Engineer"
      
    status: "Technical Interview" 
    # Stages: Sourced → Contacted → Screen → Technical → Onsite → Offer → Accepted/Rejected
    
    scores:
      resume: 82
      phone_screen: 4.2
      technical: null  # pending
      
    timeline:
      first_contact: "2026-01-15"
      screen_date: "2026-01-18"
      technical_date: "2026-01-22"
      decision_deadline: "2026-01-29"
      
    notes: "Strong systems background, excited about our scale challenges"
    risk: "Also interviewing at Datadog — need to move fast"
    next_action: "Schedule system design with VP Eng by EOD"

### Pipeline Health Metrics (Track Weekly)

pipeline_metrics:
  week_of: "2026-01-20"
  role: "Senior Backend Engineer"
  
  funnel:
    sourced: 45
    contacted: 30
    responded: 12      # 40% response rate
    screened: 8        # 67% screen rate
    technical: 4       # 50% pass rate
    onsite: 2          # 50% advance rate
    offer: 1
    accepted: 0
  
  velocity:
    avg_days_to_screen: 3
    avg_days_to_offer: 21
    bottleneck: "Hiring manager availability for onsites"
    
  quality:
    screen_pass_rate: "67%"
    technical_pass_rate: "50%"
    offer_acceptance_rate: "pending"
    
  actions:
    - "Book 3 onsite slots with VP Eng this week"
    - "Source 10 more candidates — pipeline thin after technical stage"
    - "Follow up with 5 unresponsive candidates (2nd touch)"

### Offer Construction Checklist

Verify comp range approved by finance/hiring manager
 Check internal equity — similar roles shouldn't have >10% variance without justification
 Prepare total comp breakdown (base + equity + bonus + benefits value)
 Draft offer letter with legal review
 Prepare verbal offer talking points
 Identify candidate's priorities (comp vs growth vs flexibility vs mission)
 Have backup plan if first offer rejected (what can we flex?)

### Verbal Offer Script

"[Name], we've really enjoyed getting to know you through this process. 
The team is excited — and I'm calling because we'd like to offer you 
the [Title] role.

Here's what we're proposing:
- Base: $[X]
- Equity: [X shares/options], vesting over [X years]
- Bonus: [X]% target
- Start date: [Date]
- [Any unique perks]

I want to make sure this works for you. What questions do you have? 
Is there anything about the offer you'd like to discuss?"

### Negotiation Response Framework

Candidate SaysYour Response"I need more base"Explore: equity trade-off, signing bonus, 6-month review"I have a competing offer""That's great — can you share the details? We want to be competitive""I need more time""Absolutely. When would you be comfortable deciding by?" (max 1 week)"I need X title"If reasonable, accommodate. Titles are cheap. If inflated, explain leveling"I want remote"If possible, yes. If not, explain hybrid flexibility clearly

### Rejection Templates

After Screen:

Hi [Name],

Thank you for taking the time to speak with us about the [Role] position. 

After careful consideration, we've decided to move forward with candidates 
whose experience more closely aligns with what we're looking for right now.

This isn't a reflection of your abilities — the candidate pool was strong. 
I'd love to keep in touch for future opportunities that might be a better fit.

Wishing you all the best in your search.

After Final Round:

Hi [Name],

I want to personally thank you for the time and effort you invested in 
our interview process. The team genuinely enjoyed meeting you.

After much deliberation, we've decided to move forward with another 
candidate whose background was a slightly closer match for this specific role.

I want to be transparent: this was a difficult decision. [Optional: 
specific positive feedback]. If you're open to it, I'd like to stay 
connected — I think there could be a great fit here in the future.

### 7. DIVERSITY & INCLUSION CHECKLIST

At each stage, verify:

Job description reviewed for exclusionary language (use tools like Textio or manual review)
 Sourcing includes at least 3 different channels/communities
 Slate has diverse representation before moving to interviews
 Interview panel is diverse
 Structured scorecards used (reduces bias vs. "gut feel")
 Debrief discusses evidence, not "culture fit" (use "culture add" framing)
 Comp offers checked against internal equity data
 Rejection reasons documented and reviewed for patterns

### 8. RECRUITING METRICS DASHBOARD

monthly_report:
  month: "January 2026"
  
  efficiency:
    open_roles: 5
    roles_filled: 2
    avg_time_to_fill: "28 days"
    avg_cost_per_hire: "$4,200"
    
  quality:
    90_day_retention: "100%"
    hiring_manager_satisfaction: "4.5/5"
    new_hire_performance: "Meets/Exceeds"
    offer_acceptance_rate: "80%"
    
  pipeline:
    total_candidates_sourced: 120
    total_screened: 45
    total_interviewed: 20
    total_offers: 3
    
  channel_roi:
    referrals: { hires: 1, cost: "$3K", time: "14 days" }
    linkedin: { hires: 1, cost: "$5K", time: "35 days" }
    inbound: { hires: 0, applicants: 80, quality: "low" }
    
  insights:
    - "Referral hires 2.5x faster and 40% cheaper than LinkedIn"
    - "Technical interview pass rate dropped — recalibrate questions"
    - "3 candidates lost to slow scheduling — fix bottleneck"

### Internal Candidates

Always interview internal candidates if they apply — even if not ideal
Use same scorecard — fairness matters
Provide detailed feedback regardless of outcome
Have their current manager informed BEFORE they find out through gossip

### Executive Hiring

Use executive search firms for C-suite (worth the 25-33% fee)
Reference checks are critical — call 6-8 people, not just the 3 they provide
Board/investor involvement in final rounds
Negotiate with employment attorney review

### High-Volume Hiring (10+ same role)

Build assessment rubric once, apply consistently
Group information sessions replace individual screens
Hire in cohorts for training efficiency
Assign dedicated sourcer per 5 open reqs

### Counteroffers

80% of candidates who accept counteroffers leave within 6 months
If they need a counteroffer to stay, the relationship is already damaged
Discuss counteroffer likelihood during screen — plant the seed early

### Rehires (Boomerang Employees)

Check: why did they leave? Has that been fixed?
Skip redundant interview stages — focus on what's changed
Fast-track onboarding — they know the culture

### 10. AUTOMATION OPPORTUNITIES

Things the agent can do autonomously:

Parse resumes against role blueprint → generate screening scores
Draft personalized outreach based on candidate's public profile
Track pipeline stages and flag stale candidates (>5 days no movement)
Generate weekly pipeline reports
Draft rejection emails
Schedule interview reminders
Research candidate backgrounds (public info only)
Build boolean search strings for new roles
Flag compensation misalignment early

Things requiring human approval:

Final hire/no-hire decisions
Offer amounts and terms
Sending outreach messages (review personalization)
Reference check calls
Sensitive feedback delivery
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: 1kalin
- Version: 1.0.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-23T16:43:11.935Z
- Expires at: 2026-04-30T16:43:11.935Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/afrexai-recruiting-engine)
- [Send to Agent page](https://openagent3.xyz/skills/afrexai-recruiting-engine/agent)
- [JSON manifest](https://openagent3.xyz/skills/afrexai-recruiting-engine/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/afrexai-recruiting-engine/agent.md)
- [Download page](https://openagent3.xyz/downloads/afrexai-recruiting-engine)