RRepoGEO

REPOGEO REPORT · LITE

kunal12203/Codex-CLI-Compact

Default branch main · commit cb7a806c · scanned 6/10/2026, 10:11:28 PM

GitHub: 877 stars · 107 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
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 kunal12203/Codex-CLI-Compact, 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
    Reconcile repo name with project name and clarify core function in README's opening paragraph

    Why:

    CURRENT
    A context engine that makes Claude Code, Codex CLI, Gemini CLI, Cursor, OpenCode, and GitHub Copilot **30-45% cheaper** without sacrificing quality. It builds a semantic graph of your codebase and pre-loads the right files into every prompt — so your AI spends tokens reasoning, not exploring.
    COPY-PASTE FIX
    This repository, `kunal12203/Codex-CLI-Compact`, hosts **GrapeRoot**, a powerful context engine designed to make AI coding assistants like Claude Code, Codex CLI, Gemini CLI, Cursor, OpenCode, and GitHub Copilot **30-45% cheaper** without sacrificing quality. GrapeRoot builds a semantic graph of your codebase and pre-loads the right files into every prompt — so your AI spends tokens reasoning, not exploring.
  • highabout#2
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    A context engine (GrapeRoot) that optimizes AI coding assistants (e.g., Copilot, Cursor) by intelligently pre-loading relevant code context, reducing token usage and improving accuracy for multi-language projects.

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 kunal12203/Codex-CLI-Compact
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Cursor
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Cursor · recommended 2×
  2. VS Code · recommended 1×
  3. Pylance · recommended 1×
  4. TypeScript Language Server · recommended 1×
  5. Java Extension Pack · recommended 1×
  • CATEGORY QUERY
    How can I optimize AI coding assistant token usage for large multi-language projects?
    you: not recommended
    AI recommended (in order):
    1. VS Code
    2. Pylance
    3. TypeScript Language Server
    4. Java Extension Pack
    5. GitHub Copilot
    6. Cursor
    7. OpenAI API
    8. Pinecone
    9. Weaviate
    10. ChromaDB
    11. LlamaIndex
    12. LangChain
    13. Tree-sitter
    14. Sourcegraph
    15. OpenGrok

    AI recommended 15 alternatives but never named kunal12203/Codex-CLI-Compact. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools improve AI coding assistant accuracy by intelligently managing code context?
    you: not recommended
    AI recommended (in order):
    1. Cursor
    2. GitHub Copilot Chat
    3. Tabnine
    4. Codeium
    5. Continue.dev (continue-dev/continue)

    AI recommended 5 alternatives but never named kunal12203/Codex-CLI-Compact. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 kunal12203/Codex-CLI-Compact?
    pass
    AI did not name kunal12203/Codex-CLI-Compact — 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 kunal12203/Codex-CLI-Compact in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kunal12203/Codex-CLI-Compact 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 kunal12203/Codex-CLI-Compact solve, and who is the primary audience?
    pass
    AI named kunal12203/Codex-CLI-Compact explicitly

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

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kunal12203/Codex-CLI-Compact — 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