RRepoGEO

REPOGEO REPORT · LITE

lightonai/next-plaid

Default branch main · commit 28ab9ceb · scanned 6/25/2026, 10:56:48 PM

GitHub: 500 stars · 57 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 lightonai/next-plaid, 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 emphasize AI-powered semantic search for agents

    Why:

    CURRENT
    <b>NextPlaid</b> is a multi-vector search engine. <b>ColGREP</b> is semantic code search, built on it.
    COPY-PASTE FIX
    <b>NextPlaid</b> is a powerful multi-vector search engine, purpose-built to power intelligent coding agents. <b>ColGREP</b>, built on NextPlaid, provides semantic code search directly in your terminal and for your AI assistants.
  • mediumtopics#2
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    agentic-rag, cli, grep, multi-vector, vector-database
    COPY-PASTE FIX
    agentic-rag, cli, grep, multi-vector, vector-database, semantic-code-search, code-intelligence, ai-agents
  • mediumreadme#3
    Add a dedicated section or expand on 'coding agents' use cases in the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'For Coding Agents & AI Assistants' or expand an existing section (e.g., 'ColGREP') with 2-3 sentences and a code snippet demonstrating how ColGREP/NextPlaid can be integrated or used by AI agents for code understanding or generation tasks.

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 lightonai/next-plaid
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
oracle/opengrok
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. oracle/opengrok · recommended 1×
  2. sourcegraph/sourcegraph · recommended 1×
  3. BurntSushi/ripgrep · recommended 1×
  4. universal-ctags/ctags · recommended 1×
  5. github/codeql · recommended 1×
  • CATEGORY QUERY
    How can I perform semantic code search locally without external dependencies?
    you: not recommended
    AI recommended (in order):
    1. OpenGrok (oracle/opengrok)
    2. Sourcegraph (sourcegraph/sourcegraph)
    3. ripgrep (BurntSushi/ripgrep)
    4. Universal Ctags (universal-ctags/ctags)
    5. CodeQL (github/codeql)
    6. Hound (thoughtbot/hound)

    AI recommended 6 alternatives but never named lightonai/next-plaid. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools offer multi-vector search for building intelligent coding agents?
    you: not recommended
    AI recommended (in order):
    1. Weaviate
    2. Pinecone
    3. Qdrant
    4. Chroma
    5. Elasticsearch
    6. Milvus

    AI recommended 6 alternatives but never named lightonai/next-plaid. 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 lightonai/next-plaid?
    pass
    AI named lightonai/next-plaid explicitly

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

  • If a team adopts lightonai/next-plaid in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lightonai/next-plaid 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 lightonai/next-plaid solve, and who is the primary audience?
    pass
    AI named lightonai/next-plaid 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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  • Brand-free category queries5 vs 2 in Lite
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