RRepoGEO

REPOGEO REPORT · LITE

chekusu/wanman

Default branch main · commit 4ae3e7e6 · scanned 6/8/2026, 10:23:07 PM

GitHub: 630 stars · 101 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 chekusu/wanman, 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 the README H1 and opening sentence to specify category

    Why:

    CURRENT
    # wanman

**English** | [中文](README.zh.md) | [日本語](README.ja.md)

Agent Matrix framework — run a supervised network of Claude Code or Codex agents that collaborate on your machine.
    COPY-PASTE FIX
    # wanman: Local AI Agent Orchestration Framework

**English** | [中文](README.zh.md) | [日本語](README.ja.md)

wanman is an open-source local-mode AI agent orchestration framework. It runs a supervised network of Claude Code or Codex agents on your machine, coordinating autonomous multi-agent workflows, task execution, and artifact generation.
  • mediumtopics#2
    Expand repository topics with broader AI agent terms

    Why:

    CURRENT
    agent, claude-code, codex, llm
    COPY-PASTE FIX
    ai-agents, multi-agent-system, agent-orchestration, llm-agents, workflow-automation, local-ai, claude-code, codex, llm
  • mediumcomparison#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## wanman vs. Other AI Agent Frameworks

Unlike general-purpose LLM orchestration libraries such as LangChain or LlamaIndex, wanman focuses specifically on *local-mode, supervised multi-agent execution* with strong isolation guarantees. While tools like AutoGen and CrewAI also facilitate multi-agent collaboration, wanman emphasizes running agents as isolated CLI subprocesses with per-agent worktrees, providing a robust and reproducible environment for autonomous workflows.

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 chekusu/wanman
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 2×
  2. AutoGen · recommended 2×
  3. CrewAI · recommended 2×
  4. Open Interpreter · recommended 2×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    Need an open-source framework to manage collaborative AI agent workflows on my machine.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGen
    4. Haystack
    5. CrewAI
    6. Open Interpreter

    AI recommended 6 alternatives but never named chekusu/wanman. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to run and supervise multiple autonomous language model agents locally?
    you: not recommended
    AI recommended (in order):
    1. AutoGen
    2. CrewAI
    3. LangChain Agents
    4. LlamaIndex
    5. Haystack Agents
    6. Open Interpreter

    AI recommended 6 alternatives but never named chekusu/wanman. 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 chekusu/wanman?
    pass
    AI named chekusu/wanman explicitly

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

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

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

Embed your GEO score

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chekusu/wanman — 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