RRepoGEO

REPOGEO REPORT · LITE

dyoshikawa/rulesync

Default branch main · commit 95b419a1 · scanned 5/13/2026, 6:22:07 PM

GitHub: 1,090 stars · 114 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 dyoshikawa/rulesync, 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
    Move core description to the top of the README

    Why:

    CURRENT
    The current README excerpt shows the description "A Node.js CLI tool..." appearing after several badges, links, and a "Documentation | npm" line.
    COPY-PASTE FIX
    Move the sentence "A Node.js CLI tool that automatically generates configuration files for various AI development tools from unified AI rule files. Features selective generation, comprehensive import/export capabilities, and supports major AI development tools with rules, commands, MCP, ignore files, subagents and skills." to immediately follow the "# Rulesync" heading.
  • highabout#2
    Expand the GitHub 'About' description for clarity

    Why:

    CURRENT
    "A Utility CLI for AI Coding Agents"
    COPY-PASTE FIX
    "A Node.js CLI tool that automatically generates configuration files for various AI development tools from unified AI rule files, supporting rules, commands, MCP, ignore files, subagents, and skills."
  • mediumreadme#3
    Emphasize the problem Rulesync solves for AI agents in the README

    Why:

    CURRENT
    The current README description focuses on what the tool does, but not explicitly on the problem it solves for AI agents.
    COPY-PASTE FIX
    Insert the sentence "AI agents often require complex, disparate configurations for rules, commands, and skills across different platforms; Rulesync simplifies this by providing a unified approach to manage and generate these configurations automatically." after the first sentence of the main description in the README.

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 dyoshikawa/rulesync
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hydra
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hydra · recommended 1×
  2. Pydantic Settings · recommended 1×
  3. ConfigArgParse · recommended 1×
  4. YAML/JSON with a Custom Loader/Parser · recommended 1×
  5. python-dotenv · recommended 1×
  • CATEGORY QUERY
    How to unify configuration files for various AI coding agents and LLM development tools?
    you: not recommended
    AI recommended (in order):
    1. Hydra
    2. Pydantic Settings
    3. ConfigArgParse
    4. YAML/JSON with a Custom Loader/Parser
    5. python-dotenv
    6. Consul
    7. Vault

    AI recommended 7 alternatives but never named dyoshikawa/rulesync. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help generate consistent rules and skills across multiple AI coding agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Function Calling
    5. Anthropic's tool use
    6. Git/GitHub
    7. GitLab
    8. Bitbucket
    9. ANTLR
    10. PLY

    AI recommended 10 alternatives but never named dyoshikawa/rulesync. 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 dyoshikawa/rulesync?
    pass
    AI named dyoshikawa/rulesync explicitly

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

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

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

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dyoshikawa/rulesync — 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