RRepoGEO

REPOGEO REPORT · LITE

mufeedvh/code2prompt

Default branch main · commit b1cb9b8e · scanned 5/29/2026, 7:47:10 AM

GitHub: 7,373 stars · 425 forks

AI VISIBILITY SCORE
33 /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
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 mufeedvh/code2prompt, 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 README opening to clarify unique value proposition

    Why:

    CURRENT
    **Code2Prompt** is a powerful context engineering tool designed to ingest codebases and format them for Large Language Models. Whether you are manually copying context for ChatGPT, building AI agents via Python, or running a MCP server, Code2Prompt streamlines the context preparation process.
    COPY-PASTE FIX
    **Code2Prompt** is a powerful **CLI tool** that transforms your entire codebase into a **structured, LLM-ready prompt**, complete with **source tree context, token counting, and customizable templates**. Unlike simple file concatenation, it intelligently formats code with metadata (filename, language) to ensure optimal context for Large Language Models, whether for ChatGPT, AI agents, or local LLMs.
  • mediumreadme#2
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## 💡 Why Code2Prompt? (vs. `grep`, `find`, or simple concatenation)
    
    While basic tools like `grep` or `find` can locate files, and simple scripts can concatenate them, **Code2Prompt** offers a specialized, intelligent approach for LLM context engineering:
    
    - **Structured Output:** Automatically formats code with file paths, language identifiers, and other metadata, ensuring LLMs understand the context.
    - **Token Awareness:** Provides accurate token counts and allows for intelligent truncation or splitting to fit context windows.
    - **Prompt Templating:** Use flexible templates to define how your codebase context is presented to the LLM.
    - **Source Tree Visualization:** Includes a representation of your project's structure for better contextual understanding.
    - **Cross-Platform CLI:** A robust, fast command-line interface for seamless integration into your workflow.
  • lowtopics#3
    Add `context-engineering` to the repository topics

    Why:

    CURRENT
    ai, chatgpt, claude, cli, command-line, command-line-tool, gpt, llm, prompt, prompt-engineering, prompt-generator, prompt-toolkit, rust
    COPY-PASTE FIX
    ai, chatgpt, claude, cli, command-line, command-line-tool, context-engineering, gpt, llm, prompt, prompt-engineering, prompt-generator, prompt-toolkit, rust

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 mufeedvh/code2prompt
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
grep
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. grep · recommended 2×
  2. find · recommended 2×
  3. Tree-sitter · recommended 1×
  4. ast module · recommended 1×
  5. go/ast · recommended 1×
  • CATEGORY QUERY
    How can I prepare my entire project's code for an LLM context window?
    you: not recommended
    AI recommended (in order):
    1. Tree-sitter
    2. ast module
    3. go/ast
    4. ts-morph
    5. Linguist
    6. cloc
    7. git log
    8. git blame
    9. DocFX
    10. Sphinx
    11. Javadoc
    12. Doxygen
    13. ripgrep
    14. grep
    15. find
    16. ack
    17. Bash
    18. Zsh
    19. PowerShell

    AI recommended 19 alternatives but never named mufeedvh/code2prompt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What command-line tool helps summarize a codebase into a single prompt for AI?
    you: not recommended
    AI recommended (in order):
    1. tree
    2. find
    3. xargs
    4. cat
    5. grep
    6. git ls-files
    7. cloc (AlDanial/cloc)
    8. ripgrep (BurntSushi/ripgrep)
    9. Python
    10. Node.js
    11. ast
    12. babel (babel/babel)

    AI recommended 12 alternatives but never named mufeedvh/code2prompt. 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 mufeedvh/code2prompt?
    pass
    AI did not name mufeedvh/code2prompt — 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 mufeedvh/code2prompt in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mufeedvh/code2prompt 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 mufeedvh/code2prompt solve, and who is the primary audience?
    pass
    AI named mufeedvh/code2prompt explicitly

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

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mufeedvh/code2prompt — 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