RRepoGEO

REPOGEO REPORT · LITE

parcadei/llm-tldr

Default branch main · commit c6494afd · scanned 5/9/2026, 5:48:03 PM

GitHub: 1,153 stars · 111 forks

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 parcadei/llm-tldr, 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
    Reposition the README's opening paragraph to clarify its unique approach

    Why:

    CURRENT
    **Give LLMs exactly the code they need. Nothing more.**

Your codebase is 100K lines. Claude's context window is 200K tokens. Raw code won't fit—and even if it did, the LLM would drown in irrelevant details.

TLDR extracts *structure* instead of dumping *text*. The result: **95% fewer tokens** while preserving everything needed to understand and edit code correctly.
    COPY-PASTE FIX
    **TLDR is a code analysis engine built specifically for AI agents.** It gives LLMs exactly the code they need, nothing more. Unlike generic context providers or vector databases, TLDR extracts *structure* instead of dumping *text*. The result: **95% fewer tokens** while preserving everything needed to understand and edit code correctly.

Your codebase is 100K lines. Claude's context window is 200K tokens. Raw code won't fit—and even if it did, the LLM would drown in irrelevant details.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://pypi.org/project/llm-tldr/

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 parcadei/llm-tldr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tree-sitter
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Tree-sitter · recommended 2×
  2. Faiss · recommended 1×
  3. Weaviate · recommended 1×
  4. Pinecone · recommended 1×
  5. ast module · recommended 1×
  • CATEGORY QUERY
    How to provide AI assistants with relevant code context while minimizing token usage?
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Weaviate
    3. Pinecone
    4. Tree-sitter
    5. ast module
    6. pygls
    7. rust-analyzer
    8. Neo4j
    9. ArangoDB
    10. grep
    11. rg (ripgrep)

    AI recommended 11 alternatives but never named parcadei/llm-tldr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool for AI agents to understand code structure, dependencies, and data flow?
    you: not recommended
    AI recommended (in order):
    1. Understand (SciTools Understand)
    2. LSIF (Language Server Index Format)
    3. Language Servers
    4. CodeQL (GitHub CodeQL)
    5. Sourcegraph
    6. Tree-sitter
    7. ANLTR (Another Tool for Language Recognition)

    AI recommended 7 alternatives but never named parcadei/llm-tldr. 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 parcadei/llm-tldr?
    pass
    AI named parcadei/llm-tldr explicitly

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

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

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

Embed your GEO score

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parcadei/llm-tldr — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite