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Job Hunter

Assist with finding, evaluating, and applying to jobs using multi-source searches, fit scoring, application support, interview prep, and status tracking.

skill openclawclawhub Free
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High Signal

Assist with finding, evaluating, and applying to jobs using multi-source searches, fit scoring, application support, interview prep, and status tracking.

โฌ‡ 0 downloads โ˜… 0 stars Unverified but indexed

Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, references/cover-letter-guide.md, references/interview-prep.md, references/profile-template.json, references/search-strategies.md, scripts/analyze_fit.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

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. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 11 sections Open source page

Job Hunter

End-to-end job search assistant โ€” from finding opportunities to landing interviews.

1. Set up candidate profile

Create a profile JSON for the user. Use the template at {baseDir}/references/profile-template.json as a starting point. Ask the user about: Target roles and seniority level Key skills and tools Location preferences (cities + remote) Salary expectations Dealbreakers and excluded companies Preferred industries/domains Save as profile.json in the workspace.

2. Search for jobs

Use the web_search tool with multiple queries to cast a wide net: site:linkedin.com/jobs "[role]" "[city]" site:indeed.com "[role]" "[city]" site:glassdoor.com/job "[role]" "[city]" "[role]" "[city]" hiring 2025 2026 Expand keywords โ€” don't just search one title. See {baseDir}/references/search-strategies.md for keyword expansion patterns. Alternative: run the search script if Brave API is available: {baseDir}/scripts/search_jobs.sh "CX Manager" --location "Amsterdam" --days 7

3. Evaluate fit

For each job found, run fit analysis: python3 {baseDir}/scripts/analyze_fit.py --profile profile.json --jobs jobs.json --threshold 50 Or evaluate manually using this framework: Skill match (40%): Does user have 60%+ of required skills? Seniority match (25%): Right level โ€” not over/under qualified? Location match (15%): Compatible location or remote? Domain match (10%): Preferred industry/domain? Red flags (10%): Excluded companies? Dealbreakers? Score: ๐ŸŸข 75+ great | ๐ŸŸก 55-74 good | ๐ŸŸ  40-54 stretch | ๐Ÿ”ด <40 skip

4. Present results

For each job, present: Role & Company with direct link Fit score with color indicator Why it's a match (top 3 skill matches) Gaps to address (missing skills to highlight as "eager to learn") Salary estimate if available Recommendation: Apply / Maybe / Skip

Cover letters

Read {baseDir}/references/cover-letter-guide.md for structure and tone guidelines. Generate tailored cover letters that: Reference specific company details (not generic) Map user's experience to top 2-3 job requirements Include quantified achievements Stay under 350 words

Interview prep

Read {baseDir}/references/interview-prep.md for complete preparation framework. Help with: Company research summaries STAR stories for key requirements Tailored "tell me about yourself" script Salary negotiation talking points Questions to ask the interviewer

Salary research

bash {baseDir}/scripts/salary_research.sh "Job Title" "Location" Cross-reference 3+ sources. In the Netherlands: factor in 8% holiday allowance, possible 13th month, pension.

Daily Brief Format

When running as a scheduled job search brief: New opportunities โ€” jobs found in last 24h with fit scores and direct links Application status โ€” updates on pending applications Action items โ€” what to apply to today, follow-ups due Market intel โ€” industry trends, salary movements, hiring patterns

Tracking

Maintain a job tracker with: Company, role, date found, source URL Fit score and recommendation Status: new โ†’ applied โ†’ screening โ†’ interview โ†’ offer/rejected/ghosted Applied/skipped with reason Contact info and follow-up dates

Tips for Agents

Never apply on behalf of the user โ€” present opportunities, let them decide Don't overwhelm โ€” 3-5 quality matches beat 20 mediocre ones Track excluded companies โ€” never suggest the same company twice after rejection Be honest about fit โ€” stretches are okay to flag, but don't oversell poor matches Respect dealbreakers โ€” if user said no customer service, don't suggest it even if "it's a great company" Update the profile โ€” as you learn user preferences, refine the profile Celebrate wins โ€” applied to a job? Got an interview? Acknowledge it

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
4 Docs1 Scripts1 Config
  • SKILL.md Primary doc
  • references/cover-letter-guide.md Docs
  • references/interview-prep.md Docs
  • references/search-strategies.md Docs
  • scripts/analyze_fit.py Scripts
  • references/profile-template.json Config