RRepoGEO

REPOGEO REPORT · LITE

poshan0126/dotclaude

Default branch main · commit c3e5ceac · scanned 6/6/2026, 3:32:29 AM

GitHub: 594 stars · 127 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 poshan0126/dotclaude, 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
    Reposition README's opening sentence to clarify Claude AI focus

    Why:

    CURRENT
    A lean `.claude/` setup for daily development. Five reviewer agents, nine workflow skills, six modular rules, and a few safety hooks. No bloat, no model assignments, no opinions you can't override.
    COPY-PASTE FIX
    A lean, opinionated `.claude/` setup for daily development with Claude AI, providing a standardized project structure, agents, skills, and rules. It's designed to quickly configure your codebase for advanced Claude 3 features like tool use and custom workflows, without bloat or rigid model assignments.
  • mediumreadme#2
    Add a 'What it is (and isn't)' section to differentiate from competitors

    Why:

    COPY-PASTE FIX
    ### What dotclaude is (and isn't)
`dotclaude` provides a standardized `.claude/` folder structure and pre-configured agents, skills, and rules specifically for development within the Claude Code environment. It is *not* a generic project templating tool like Cookiecutter or PyScaffold, nor is it an AI orchestration framework like LangChain or LlamaIndex. Instead, it's a focused boilerplate designed to jumpstart your AI-native development with Anthropic's Claude, ensuring a consistent and optimized setup for your project's AI assistant.

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 poshan0126/dotclaude
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Cookiecutter
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Cookiecutter · recommended 1×
  2. PyScaffold · recommended 1×
  3. Poetry · recommended 1×
  4. FastAPI · recommended 1×
  5. fastapi-mvc · recommended 1×
  • CATEGORY QUERY
    How to quickly configure an AI assistant's project structure for daily development?
    you: not recommended
    AI recommended (in order):
    1. Cookiecutter
    2. PyScaffold
    3. Poetry
    4. FastAPI
    5. fastapi-mvc
    6. Hugging Face Transformers `Trainer`
    7. Hugging Face Transformers `Pipeline`
    8. MLflow

    AI recommended 8 alternatives but never named poshan0126/dotclaude. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a boilerplate for integrating AI agents and custom workflow skills into my codebase.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Microsoft Semantic Kernel
    4. Haystack
    5. OpenAI Assistants API
    6. CrewAI

    AI recommended 6 alternatives but never named poshan0126/dotclaude. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 poshan0126/dotclaude?
    pass
    AI named poshan0126/dotclaude explicitly

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

  • If a team adopts poshan0126/dotclaude in production, what risks or prerequisites should they evaluate first?
    pass
    AI named poshan0126/dotclaude 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 poshan0126/dotclaude solve, and who is the primary audience?
    pass
    AI named poshan0126/dotclaude explicitly

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

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poshan0126/dotclaude — 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