RRepoGEO

REPOGEO REPORT · LITE

bartolli/codanna

Default branch main · commit cb2c095c · scanned 6/15/2026, 5:36:51 AM

GitHub: 695 stars · 61 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 bartolli/codanna, 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 the README's opening paragraph to explicitly state its core function

    Why:

    CURRENT
    X-ray vision for your agent. Give your code assistant the ability to see through your codebase—understanding functions, tracing relationships, and finding implementations with surgical precision. Context-first coding. No grep-and-hope loops. No endless back-and-forth. Just smarter engineering in fewer keystrokes. Built for rapid R&D and pair programming—instant answers when LSP is too slow. Learn more
    COPY-PASTE FIX
    Codanna is a local code intelligence MCP server and CLI, providing X-ray vision for your AI coding agent. It gives your code assistant the ability to see through your codebase—understanding functions, tracing relationships, and finding implementations with surgical precision. Context-first coding. No grep-and-hope loops. No endless back-and-forth. Just smarter engineering in fewer keystrokes. Built for rapid R&D and pair programming—instant answers when LSP is too slow.
  • mediumtopics#2
    Add more specific topics to clarify its niche for AI agents

    Why:

    CURRENT
    ai-agents, call-graph-analysis, code-indexing, code-intelligence, code-search, coding-agents, developer-tools-ai-agent, local-first, mcp, mcp-server, mcp-tools, rag, rust-cli, semantic-code-search, static-analysis, symbol-search
    COPY-PASTE FIX
    Add the following topics: local-code-intelligence, ai-agent-server, code-context-for-llms
  • mediumreadme#3
    Add a 'Why Codanna?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Why Codanna?' or 'Comparison to Alternatives,' explaining how Codanna provides local, agent-specific code intelligence distinct from general code search tools (like Sourcegraph/OpenGrok), LSP servers, or AI agent frameworks (like LlamaIndex/LangChain) that don't offer deep, local code understanding. Emphasize its focus on instant answers for AI agents rather than human IDE interaction or broad code coverage analysis.

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 bartolli/codanna
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 1×
  2. LangChain · recommended 1×
  3. GitHub Copilot Chat · recommended 1×
  4. Cursor · recommended 1×
  5. Sourcegraph · recommended 1×
  • CATEGORY QUERY
    How can I give my AI coding agent better context for complex codebases?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. GitHub Copilot Chat
    4. Cursor
    5. Sourcegraph
    6. Git
    7. Confluence
    8. Notion
    9. OpenTelemetry
    10. Prometheus
    11. Grafana

    AI recommended 11 alternatives but never named bartolli/codanna. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What local code intelligence server helps AI agents understand code faster than LSP?
    you: not recommended
    AI recommended (in order):
    1. Tree-sitter (tree-sitter/tree-sitter)
    2. Sourcegraph's Cody (sourcegraph/cody)
    3. OpenGrok (oracle/opengrok)
    4. Universal Ctags (universal-ctags/ctags)
    5. Neo4j (neo4j/neo4j)
    6. Soufflé Datalog (souffle-lang/souffle)
    7. Faiss (facebookresearch/faiss)
    8. Milvus (milvus-io/milvus)

    AI recommended 8 alternatives but never named bartolli/codanna. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 bartolli/codanna?
    pass
    AI named bartolli/codanna explicitly

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

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

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

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bartolli/codanna — 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