RRepoGEO

REPOGEO REPORT · LITE

0xfurai/claude-code-subagents

Default branch main · commit 9236d107 · scanned 6/2/2026, 5:53:29 PM

GitHub: 917 stars · 171 forks

AI VISIBILITY SCORE
22 /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
1 / 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 0xfurai/claude-code-subagents, 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
    Clarify repo's role as a collection of agent definitions

    Why:

    CURRENT
    A comprehensive collection of specialized AI subagents for Claude Code, designed to enhance development workflows with domain-specific expertise.
    COPY-PASTE FIX
    This repository provides a comprehensive, ready-to-use collection of specialized AI subagent *definitions* for Claude Code, designed to enhance development workflows with domain-specific expertise. It serves as a library of pre-configured agents for integration into Claude-powered applications, distinct from direct IDE plugins or standalone coding assistants.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["claude", "ai-agents", "llm-agents", "code-generation", "developer-tools", "anthropic", "agentic-ai", "subagents", "python-agents", "javascript-agents"]
  • mediumreadme#3
    Add a comparison section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## How is this different from generic AI coding assistants?

Unlike general-purpose AI coding assistants (e.g., GitHub Copilot, Tabnine) that integrate directly into IDEs, `claude-code-subagents` is a pre-defined, specialized collection of multi-agent *definitions* for the software development lifecycle (SDLC). It is explicitly designed and optimized to leverage Claude models (especially Claude 3 Opus) for advanced code generation, analysis, and review tasks, providing a modular resource for your Claude-powered applications.

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 0xfurai/claude-code-subagents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot · recommended 2×
  2. Tabnine · recommended 2×
  3. JetBrains AI Assistant · recommended 2×
  4. Google Gemini · recommended 2×
  5. Codeium · recommended 1×
  • CATEGORY QUERY
    What AI agents are available to improve my development workflow across different languages?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Tabnine
    3. Codeium
    4. Amazon CodeWhisperer
    5. JetBrains AI Assistant
    6. Cursor
    7. Google Gemini

    AI recommended 7 alternatives but never named 0xfurai/claude-code-subagents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI coding assistant with specialized knowledge for multiple programming languages.
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Tabnine
    3. CodeWhisperer (Amazon Q Developer)
    4. JetBrains AI Assistant
    5. Google Gemini

    AI recommended 5 alternatives but never named 0xfurai/claude-code-subagents. 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 0xfurai/claude-code-subagents?
    pass
    AI did not name 0xfurai/claude-code-subagents — 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 0xfurai/claude-code-subagents in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 0xfurai/claude-code-subagents 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 0xfurai/claude-code-subagents solve, and who is the primary audience?
    pass
    AI did not name 0xfurai/claude-code-subagents — 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?

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0xfurai/claude-code-subagents — 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