RRepoGEO

REPOGEO REPORT · LITE

Chachamaru127/claude-code-harness

Default branch main · commit ef79f618 · scanned 6/23/2026, 5:21:23 PM

GitHub: 2,852 stars · 274 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Chachamaru127/claude-code-harness, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    llm-development, claude-ai, code-generation, ai-workflow, testing-harness, autonomous-agents, code-review, devops-tools
  • highreadme#2
    Reposition the README's opening to clearly state the tool's type

    Why:

    CURRENT
    Claude Code Harness

Plan. Work. Review. Ship.
A disciplined delivery loop for Claude Code, with bounded paths for Codex and OpenCode.

Claude Code is powerful, but raw agent work drifts: plans live in chat, tests become optional, review happens too late, and release evidence gets rebuilt by memory. Harness turns that into one repeatable operating path.
    COPY-PASTE FIX
    Claude Code Harness is a **disciplined workflow framework and testing harness** for AI-generated code, specifically designed for Claude Code, with bounded paths for Codex and OpenCode.

Plan. Work. Review. Ship.
A disciplined delivery loop for Claude Code, with bounded paths for Codex and OpenCode.

Claude Code is powerful, but raw agent work drifts: plans live in chat, tests become optional, review happens too late, and release evidence gets rebuilt by memory. Harness turns that into one repeatable operating path.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/Chachamaru127/claude-code-harness

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface Chachamaru127/claude-code-harness
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot Enterprise
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot Enterprise · recommended 2×
  2. GitHub Copilot Business · recommended 2×
  3. OpenAI API · recommended 2×
  4. Azure DevOps · recommended 2×
  5. GitHub Actions · recommended 2×
  • CATEGORY QUERY
    How to improve the quality and reliability of AI-generated code development workflows?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. GitHub Copilot Business
    3. OpenAI API
    4. Hugging Face Transformers Library (huggingface/transformers)
    5. SonarQube
    6. SonarCloud
    7. Jira
    8. Azure DevOps
    9. Trello
    10. GitHub Actions
    11. GitLab CI/CD
    12. Jenkins
    13. Pytest (pytest-dev/pytest)
    14. JUnit
    15. NUnit

    AI recommended 15 alternatives but never named Chachamaru127/claude-code-harness. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for disciplined AI code generation, including automated planning, testing, and review processes?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. GitHub Copilot Business
    3. GitHub Actions
    4. Azure DevOps
    5. OpenAI's GPT-4
    6. Azure OpenAI Service
    7. MLflow (mlflow/mlflow)
    8. GitLab
    9. OpenAI
    10. Hugging Face models
    11. GitLab CI/CD
    12. Cursor IDE
    13. Jenkins
    14. CircleCI
    15. OpenAI API
    16. CodiumAI

    AI recommended 16 alternatives but never named Chachamaru127/claude-code-harness. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of Chachamaru127/claude-code-harness?
    pass
    AI named Chachamaru127/claude-code-harness explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Chachamaru127/claude-code-harness in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Chachamaru127/claude-code-harness explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo Chachamaru127/claude-code-harness solve, and who is the primary audience?
    pass
    AI named Chachamaru127/claude-code-harness explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Chachamaru127/claude-code-harness — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite