RRepoGEO

REPOGEO REPORT · LITE

zscole/adversarial-spec

Default branch main · commit f90cf0c3 · scanned 6/1/2026, 11:03:09 AM

GitHub: 548 stars · 47 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 zscole/adversarial-spec, 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's first sentence to emphasize its LLM application category and unique value

    Why:

    CURRENT
    A Claude Code plugin that iteratively refines product specifications through multi-model debate until consensus is reached.
    COPY-PASTE FIX
    This Claude Code plugin is an LLM-powered application designed to rigorously refine product specifications by orchestrating a multi-model debate until all participating LLMs reach consensus. This unique adversarial review process catches gaps, challenges assumptions, and surfaces edge cases that any single model would overlook.
  • hightopics#2
    Add problem-domain and architectural topics

    Why:

    CURRENT
    anthropic, claude-ai, claude-code, claude-code-plugin, claude-skills, llm, orchestration
    COPY-PASTE FIX
    anthropic, claude-ai, claude-code, claude-code-plugin, claude-skills, llm, orchestration, product-management, specification, software-design, requirements-engineering, ai-agents, multi-agent-systems
  • mediumhomepage#3
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/zscole/adversarial-spec

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 zscole/adversarial-spec
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Validio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Validio · recommended 1×
  2. Prowler.io · recommended 1×
  3. Gherkin · recommended 1×
  4. Avo.app · recommended 1×
  5. Testim.io · recommended 1×
  • CATEGORY QUERY
    What tools help improve product specifications by identifying gaps and edge cases with AI?
    you: not recommended
    AI recommended (in order):
    1. Validio
    2. Prowler.io
    3. Gherkin
    4. Avo.app
    5. Testim.io
    6. ChatGPT / GPT-4

    AI recommended 6 alternatives but never named zscole/adversarial-spec. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to use AI models to rigorously debate and achieve consensus on technical designs?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT
    2. Claude
    3. Gemini
    4. LangChain (langchain-ai/langchain)
    5. LlamaIndex (run-llama/llama_index)
    6. Perplexity AI
    7. Otter.ai
    8. Fathom

    AI recommended 8 alternatives but never named zscole/adversarial-spec. 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 zscole/adversarial-spec?
    pass
    AI named zscole/adversarial-spec explicitly

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

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

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

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zscole/adversarial-spec — 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