RRepoGEO

REPOGEO REPORT · LITE

parcadei/llm-tldr

Default branch main · commit c6494afd · scanned 6/19/2026, 3:03:03 PM

GitHub: 1,171 stars · 113 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
28 /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
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 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

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

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-tools, code-analysis, ai-agents, context-window, code-understanding, program-analysis, static-analysis
  • highreadme#2
    Refine the README's opening paragraph for clearer positioning

    Why:

    CURRENT
    Give LLMs exactly the code they need. Nothing more.
    COPY-PASTE FIX
    TLDR is a **code analysis engine specifically for AI agents and LLMs.** Unlike vector databases or raw code dumps, TLDR extracts *actionable code structure and dependencies*, not just text. This means **95% fewer tokens** while giving LLMs *exactly* what they need to understand, edit, and generate code correctly.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/parcadei/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
OpenAI Embeddings
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Embeddings · recommended 1×
  2. Sentence-BERT · recommended 1×
  3. FAISS · recommended 1×
  4. Pinecone · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How to provide relevant code snippets to LLMs without exceeding context limits?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Embeddings
    2. Sentence-BERT
    3. FAISS
    4. Pinecone
    5. Weaviate
    6. Tree-sitter
    7. ANTLR
    8. spaCy
    9. NLTK
    10. CodeT5
    11. PLBART
    12. LangChain
    13. LlamaIndex
    14. ctags
    15. LSIF

    AI recommended 15 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 codebase structure and dependencies efficiently?
    you: not recommended
    AI recommended (in order):
    1. Understand
    2. Lattix Architect
    3. CodeSee Map
    4. Sourcegraph
    5. SonarQube
    6. Dependency-Track
    7. Graphviz

    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 did not name parcadei/llm-tldr — 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?

  • 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?

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parcadei/llm-tldr — 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