RRepoGEO

REPOGEO REPORT · LITE

manojmallick/sigmap

Default branch main · commit 5cc77207 · scanned 6/10/2026, 11:31:25 PM

GitHub: 509 stars · 33 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
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 manojmallick/sigmap, 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 H1 and tagline to explicitly state its purpose for LLM code context

    Why:

    CURRENT
    # ⚡ SigMap
**SigMap finds the right files before your AI answers.**
    COPY-PASTE FIX
    # ⚡ SigMap: 97% Token Reduction for AI Coding Sessions
**SigMap intelligently feeds relevant code context to your LLM, not the whole repo.**
  • mediumreadme#2
    Add a section to the README clarifying SigMap's role in the LLM ecosystem

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'SigMap in the LLM Ecosystem' or 'How SigMap Complements Other Tools,' explaining that SigMap is a *context provider* for LLMs, not an LLM itself, nor a general-purpose vector database, and how it works *with* models like Code Llama or tools like LlamaIndex.
  • lowabout#3
    Refine the 'About' description for immediate clarity and keyword density

    Why:

    CURRENT
    97% token reduction for AI coding sessions — zero deps, 31 languages, MCP server
    COPY-PASTE FIX
    Intelligent code context for LLMs: SigMap reduces AI coding session tokens by 97% by feeding only relevant files, supporting 31 languages with zero dependencies.

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 manojmallick/sigmap
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama 7B
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama 7B · recommended 1×
  2. StarCoderBase-7B · recommended 1×
  3. DeepSeek Coder 1.3B · recommended 1×
  4. LlamaIndex · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    How can I reduce token usage when using LLMs for code assistance?
    you: not recommended
    AI recommended (in order):
    1. Code Llama 7B
    2. StarCoderBase-7B
    3. DeepSeek Coder 1.3B
    4. LlamaIndex
    5. LangChain
    6. LangChain's ConversationSummaryBufferMemory
    7. Code Llama 7B Instruct
    8. Phi-2
    9. tiktoken

    AI recommended 9 alternatives but never named manojmallick/sigmap. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools to provide relevant code context to LLMs without sending entire repository?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Embeddings
    2. Pinecone
    3. Weaviate (weaviate/weaviate)
    4. ChromaDB (chroma-core/chroma)
    5. text-embedding-ada-002

    AI recommended 5 alternatives but never named manojmallick/sigmap. 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 manojmallick/sigmap?
    pass
    AI named manojmallick/sigmap explicitly

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

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

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

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manojmallick/sigmap — 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