he-yufeng/findjobs-agent
Grade a repo

82

/ 100

GradeB

Polished and well engineered. Punching above its star count.

Top 22% of 5,156 graded repos

LLM-powered toolkit for skill analysis, AI interviews, resume scoring, and job structuring. Automates professional skill taxonomy and interview processes with adaptive difficulty.

Documentation85
Engineering78
Health100
Python240MIT1mo ago

Top fixes

Highest-impact changes first, ranked by point weight

8 to address
  1. 1
    Tests18pt

    Wire your tests to a documented command (e.g. a test script in your build config) so the suite is reproducible.

  2. 2
    Install and run instructions9pt

    Add a .env.example listing all required environment variables so contributors know what to set up.

  3. 3
    Reproducibility6pt

    Add .github/dependabot.yml with at least one package-ecosystem entry so dependencies are updated automatically.

  4. 4
    Issue and PR templates6pt

    Add .github/ISSUE_TEMPLATE/ with bug_report.md and feature_request.md to guide contributors. It dramatically improves issue quality.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

85

Contributing guide5pt25

Contributing guidance is in the README, not a dedicated CONTRIBUTING.md (−20 pts).

→ Moving it to a CONTRIBUTING.md makes it easier to find and keeps the README focused. A dedicated file earns +47 pts base.

Install and run instructions9pt90

README documents how to install the project.

README12pt100

README is present.

License6pt100

Licensed under MIT.

Engineering

78

Issue and PR templates6pt0

No issue or PR templates found (−100 pts).

→ Add .github/ISSUE_TEMPLATE/ with bug_report.md and feature_request.md to guide contributors. It dramatically improves issue quality.

Tests18pt80

Test files detected (tests).

Reproducibility6pt80

Lockfile present (requirements.txt). Installs are reproducible.

CI/CD14pt100

CI is configured (.github/workflows/ci.yml).

Linting and formatting5pt100

Linter or formatter configured (FrontEnd/eslint.config.js).

Project health

100

Dependency manifest6pt100

Dependency manifest found (requirements.txt).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Housekeeping3pt100

.gitignore present.

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • 11 / 19
    Commits (30d / 90d)
  • 25
    Forks
  • 0
    Releases

Community

  • 42% - Weak
    Community health
  • -
    authors own >50% of commits
  • 240
    Watchers

Responsiveness

  • 6d 12h
    Median issue response
  • <1h
    Median PR merge time
  • 0
    Open issues
Repository files36 root entries
  • .github
    Good: CI is configured (.github/workflows/ci.yml).
  • docs
  • FrontEnd
    Good: Linter or formatter configured (FrontEnd/eslint.config.js).
  • scripts
  • tests
    Good: Test files detected (tests).
  • .dockerignore
  • .gitignore
    Good: .gitignore present.
  • add_tags.py
  • AI_interviewer.py
  • ai_user_tags.csv
  • api_server.py
  • app.py
  • Dockerfile
    Good: Environment pinned via Dockerfile.
  • interview_agent.py
  • job_agent.py
  • job_crawler_selenium.py
  • job_crawler_v2.py
  • job_crawler.py
  • job_matcher.py
  • LICENSE
    Good: Licensed under MIT.
  • llm_client.py
  • llm_config_openai.json
  • llm_config.json
  • llm_utils.py
  • md_to_pdf.py
  • ms_deploy.example.json
  • pipeline.py
  • README_API.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • README_CN.md
  • README.md
  • requirements.txt
    Good: Lockfile present (requirements.txt). Installs are reproducible.
    Good: Dependency manifest found (requirements.txt).
  • resume_parser.py
  • tag_rate.py
  • tech_taxonomy.json
  • update_jobs.py
  • 项目说明文档.md
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