RRepoGEO

REPOGEO REPORT · LITE

puaclaw/PUAClaw

Default branch main · commit c2e525d9 · scanned 6/27/2026, 5:57:47 AM

GitHub: 2,688 stars · 248 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 puaclaw/PUAClaw, 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 technical domain

    Why:

    COPY-PASTE FIX
    # PUAClaw: A Framework for Persuasion and Unconventional Tactics in Large Language Models

PUAClaw is an open-source framework designed for developing and experimenting with autonomous AI agents that explore advanced prompt engineering, social engineering, and unconventional interaction patterns for Large Language Models (LLMs). It provides tools and techniques to analyze and implement persuasive communication strategies within AI systems, pushing the boundaries of agent behavior.
  • mediumtopics#2
    Add more descriptive topics

    Why:

    CURRENT
    agent, openclaw
    COPY-PASTE FIX
    agent, openclaw, llm-agents, ai-agents, prompt-engineering, large-language-models, social-engineering, persuasion-tactics
  • lowabout#3
    Update repository description for clarity

    Why:

    CURRENT
    Claw 们终将接管世界，PUAClaw is All You Need
    COPY-PASTE FIX
    An open-source framework for developing AI agents that explore persuasion and unconventional interaction patterns in Large Language Models (LLMs).

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 puaclaw/PUAClaw
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AutoGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AutoGPT · recommended 1×
  2. BabyAGI · recommended 1×
  3. LangChain · recommended 1×
  4. AgentVerse · recommended 1×
  5. Open Interpreter · recommended 1×
  • CATEGORY QUERY
    What are some open-source frameworks for developing and experimenting with autonomous AI agents?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. BabyAGI
    3. LangChain
    4. AgentVerse
    5. Open Interpreter
    6. MetaGPT

    AI recommended 6 alternatives but never named puaclaw/PUAClaw. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools or techniques to explore unconventional interaction patterns for AI agent behavior.
    you: not recommended
    AI recommended (in order):
    1. Unity ML-Agents Toolkit (Unity-Technologies/ml-agents)
    2. OpenAI Gym (openai/gym)
    3. Baselines3 (DLR-RM/stable-baselines3)
    4. DeepMind Lab (deepmind/lab)
    5. Godot Engine (godotengine/godot)
    6. NetLogo (NetLogo/NetLogo)
    7. Lenia (Chakazul/Lenia)

    AI recommended 7 alternatives but never named puaclaw/PUAClaw. 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 puaclaw/PUAClaw?
    pass
    AI did not name puaclaw/PUAClaw — 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 puaclaw/PUAClaw in production, what risks or prerequisites should they evaluate first?
    pass
    AI named puaclaw/PUAClaw 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 puaclaw/PUAClaw solve, and who is the primary audience?
    pass
    AI named puaclaw/PUAClaw 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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MARKDOWN (README)
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puaclaw/PUAClaw — 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