RRepoGEO

REPOGEO REPORT · LITE

zhu1090093659/spec_driven_develop

Default branch main · commit 0f72e593 · scanned 6/8/2026, 5:04:01 AM

GitHub: 895 stars · 93 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 zhu1090093659/spec_driven_develop, 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 opening sentence to clarify its specific category

    Why:

    CURRENT
    An architecture-first workflow plugin for AI coding agents. Pure Markdown. Claude Code, Codex, Cursor, and any agent that reads custom skills.
    COPY-PASTE FIX
    Spec-Driven Develop is a complete, architecture-first development workflow and methodology designed specifically for AI coding agents. It uses pure Markdown and is compatible with Claude Code, Codex, Cursor, and any agent that reads custom skills.
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/zhu1090093659/spec_driven_develop
  • mediumreadme#3
    Enhance the 'LLM-Friendly Summary' section for clarity and differentiation

    Why:

    COPY-PASTE FIX
    Add a sentence to the 'LLM-Friendly Summary' that explicitly clarifies Spec-Driven Develop is a workflow *for AI coding agents* and not a generic planning, diagramming, or note-taking tool. For example: "Unlike generic planning or diagramming tools, Spec-Driven Develop provides a complete, Markdown-based workflow specifically for AI coding agents, enabling structured task decomposition and adaptive control."

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 zhu1090093659/spec_driven_develop
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Notion
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Notion · recommended 2×
  2. Miro · recommended 1×
  3. Lucidchart · recommended 1×
  4. PlantUML · recommended 1×
  5. Mermaid · recommended 1×
  • CATEGORY QUERY
    How to implement an architecture-first development workflow for AI coding agents?
    you: not recommended
    AI recommended (in order):
    1. Miro
    2. Lucidchart
    3. PlantUML
    4. Mermaid
    5. Confluence
    6. Notion
    7. OpenAPI
    8. Protocol Buffers
    9. Apache Avro
    10. Visual Paradigm
    11. Enterprise Architect
    12. LangChain (langchain-ai/langchain)
    13. LlamaIndex (run-llama/llama_index)
    14. AutoGen (microsoft/autogen)
    15. Haystack (deepset-ai/haystack)
    16. CrewAI (joaomdmoura/crewai)
    17. Docker
    18. Kubernetes (kubernetes/kubernetes)
    19. AWS Lambda
    20. Google Cloud Functions
    21. Azure Functions
    22. MLflow (mlflow/mlflow)
    23. Weights & Biases (wandb/wandb)
    24. Pytest (pytest-dev/pytest)
    25. unittest
    26. Great Expectations (great-expectations/great_expectations)
    27. Git
    28. GitHub
    29. GitLab
    30. Bitbucket
    31. GitHub Actions
    32. GitLab CI/CD
    33. Jenkins (jenkinsci/jenkins)

    AI recommended 33 alternatives but never named zhu1090093659/spec_driven_develop. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a structured planning tool for LLM-driven development with task decomposition and Markdown.
    you: not recommended
    AI recommended (in order):
    1. Obsidian
    2. Logseq (logseq/logseq)
    3. Notion
    4. Joplin (laurent22/joplin)
    5. GitHub Issues/Projects
    6. TiddlyWiki (TiddlyWiki/TiddlyWiki5)

    AI recommended 6 alternatives but never named zhu1090093659/spec_driven_develop. 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 zhu1090093659/spec_driven_develop?
    pass
    AI did not name zhu1090093659/spec_driven_develop — 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 zhu1090093659/spec_driven_develop in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zhu1090093659/spec_driven_develop 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 zhu1090093659/spec_driven_develop solve, and who is the primary audience?
    pass
    AI did not name zhu1090093659/spec_driven_develop — 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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zhu1090093659/spec_driven_develop — 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
zhu1090093659/spec_driven_develop — RepoGEO report