RRepoGEO

REPOGEO REPORT · LITE

wquguru/harness-books

Default branch main · commit fbf2b43e · scanned 5/22/2026, 3:48:01 AM

GitHub: 2,178 stars · 255 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)

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

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 wquguru/harness-books, 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
  • highreadme#1
    Reposition README H1 and opening paragraph

    Why:

    CURRENT
    # Harness Books

Two books on harness engineering. They pursue the same engineering question: once a code-writing model is placed inside terminals, repositories, permission systems, and team workflows, what keeps the overall system bounded, continuous, and accountable for consequences?
    COPY-PASTE FIX
    # Harness Books: Design Guides for Integrating AI Code Generation Safely

These two books provide comprehensive design guides for "harness engineering," focusing on the safe, bounded, and accountable integration of AI code-writing models into existing software development workflows, including terminals, repositories, permission systems, and team processes.
  • highabout#2
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Design guides and philosophies for safely integrating AI code-writing models into software development workflows and team environments.
  • hightopics#3
    Add relevant topics for discoverability

    Why:

    COPY-PASTE FIX
    ai-code-generation, llm-engineering, harness-engineering, software-development, design-guides, responsible-ai, developer-tools, workflow-integration, engineering-management

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 wquguru/harness-books
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amazon CodeWhisperer
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amazon CodeWhisperer · recommended 2×
  2. GitHub Pull Requests · recommended 2×
  3. GitLab Merge Requests · recommended 2×
  4. Bitbucket Pull Requests · recommended 2×
  5. Confluence · recommended 2×
  • CATEGORY QUERY
    How to integrate AI code generation safely into existing software development workflows?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. GitLab Duo Code Suggestions
    3. Amazon CodeWhisperer
    4. OpenAI API
    5. SonarQube
    6. Snyk Code
    7. Checkmarx SAST
    8. OWASP ZAP
    9. Burp Suite
    10. Invicti
    11. GitHub Pull Requests
    12. GitLab Merge Requests
    13. Bitbucket Pull Requests

    AI recommended 13 alternatives but never named wquguru/harness-books. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for managing AI code assistants in a team development environment?
    you: not recommended
    AI recommended (in order):
    1. Confluence
    2. Notion
    3. GitHub Wiki
    4. GitHub Copilot
    5. Amazon CodeWhisperer
    6. Tabnine
    7. GitHub Pull Requests
    8. GitLab Merge Requests
    9. Bitbucket Pull Requests
    10. Lessonly
    11. TalentLMS
    12. Jira
    13. LinearB
    14. Pluralsight Flow
    15. Confluence
    16. Notion
    17. Microsoft Teams
    18. Slack Channels
    19. GitHub Copilot Business
    20. Amazon CodeWhisperer Professional Tier

    AI recommended 20 alternatives but never named wquguru/harness-books. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 wquguru/harness-books?
    pass
    AI named wquguru/harness-books explicitly

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

  • If a team adopts wquguru/harness-books in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wquguru/harness-books 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 wquguru/harness-books solve, and who is the primary audience?
    pass
    AI did not name wquguru/harness-books — likely talking about a different project

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

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  • Brand-free category queries5 vs 2 in Lite
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