RRepoGEO

REPOGEO REPORT · LITE

colbymchenry/codegraph

Default branch main · commit 4aa2752e · scanned 6/20/2026, 6:12:01 AM

GitHub: 52,096 stars · 3,170 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
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 colbymchenry/codegraph, 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

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

OVERALL DIRECTION
  • highreadme#1
    Add a clear tagline under the main README title

    Why:

    CURRENT
    # CodeGraph
    COPY-PASTE FIX
    # CodeGraph

A local, pre-indexed code knowledge graph for LLM code assistants.
  • mediumreadme#2
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison to IDEs and Other Tools

CodeGraph provides a unique approach to semantic code intelligence, distinct from traditional IDE features or general LLM frameworks. While IDEs offer basic navigation, CodeGraph builds a comprehensive, pre-indexed knowledge graph specifically optimized for LLM code assistants, enabling deeper understanding and more efficient interactions.

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 colbymchenry/codegraph
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 1×
  2. LM Studio · recommended 1×
  3. Hugging Face Transformers · recommended 1×
  4. bitsandbytes · recommended 1×
  5. auto-gptq · recommended 1×
  • CATEGORY QUERY
    How can I optimize LLM code assistant performance and reduce costs locally?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. Hugging Face Transformers
    4. bitsandbytes
    5. auto-gptq
    6. Llama.cpp
    7. ExLlamaV2
    8. MLC LLM

    AI recommended 8 alternatives but never named colbymchenry/codegraph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for semantic code intelligence in development workflows?
    you: not recommended
    AI recommended (in order):
    1. VS Code (microsoft/vscode)
    2. Eclipse IDE
    3. Sublime Text
    4. rust-analyzer (rust-lang/rust-analyzer)
    5. pyright (microsoft/pyright)
    6. gopls (golang/tools)
    7. typescript-language-server (typescript-language-server/typescript-language-server)
    8. Sourcegraph (sourcegraph/sourcegraph)
    9. GitHub Copilot
    10. GitLab Duo Code Suggestions
    11. AWS CodeWhisperer
    12. SonarQube (SonarSource/sonarqube)
    13. SonarCloud
    14. IntelliJ IDEA Ultimate
    15. PyCharm Professional
    16. WebStorm
    17. GoLand
    18. CLion
    19. CodeQL (github/codeql)
    20. Cody (sourcegraph/cody)

    AI recommended 20 alternatives but never named colbymchenry/codegraph. 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 colbymchenry/codegraph?
    pass
    AI named colbymchenry/codegraph explicitly

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

  • If a team adopts colbymchenry/codegraph in production, what risks or prerequisites should they evaluate first?
    pass
    AI named colbymchenry/codegraph 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 colbymchenry/codegraph solve, and who is the primary audience?
    pass
    AI named colbymchenry/codegraph explicitly

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

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colbymchenry/codegraph — 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