RRepoGEO

REPOGEO REPORT · LITE

sashiko-dev/sashiko

Default branch main · commit d5b6fd1f · scanned 6/1/2026, 6:34:19 AM

GitHub: 766 stars · 141 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 sashiko-dev/sashiko, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    linux-kernel, code-review, llm, ai-agent, patch-review, kernel-development, generative-ai
  • highreadme#2
    Reposition the README H1 to clearly state its purpose

    Why:

    CURRENT
    # Sashiko
    COPY-PASTE FIX
    # Sashiko: Agentic Linux Kernel Code Review
  • mediumreadme#3
    Add a 'Key Features' section to highlight core differentiators

    Why:

    COPY-PASTE FIX
    ## Key Features

*   **Agentic LLM-powered Review:** Utilizes advanced AI agents and large language models for intelligent code analysis.
*   **Linux Kernel Specific:** Tailored with kernel-specific prompts and protocols for accurate patch review.
*   **High Bug Detection:** Proven to identify a significant percentage of bugs that pass human review.
*   **Self-Contained & Flexible:** Operates independently without external CLI tools and supports various LLM providers.

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 sashiko-dev/sashiko
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
getpatchwork/patchwork
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. getpatchwork/patchwork · recommended 1×
  2. GitLab CI · recommended 1×
  3. GitHub Actions · recommended 1×
  4. Jenkins · recommended 1×
  5. Buildbot · recommended 1×
  • CATEGORY QUERY
    How can I automate the review process for Linux kernel patch submissions?
    you: not recommended
    AI recommended (in order):
    1. Patchwork (getpatchwork/patchwork)
    2. GitLab CI
    3. GitHub Actions
    4. Jenkins
    5. Buildbot
    6. checkpatch.pl
    7. Sparse
    8. Coccinelle (coccinelle/coccinelle)
    9. git-email
    10. git-send-email

    AI recommended 10 alternatives but never named sashiko-dev/sashiko. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI-powered tools exist for intelligent code review of Linux kernel contributions?
    you: not recommended
    AI recommended (in order):
    1. Snyk Code
    2. CodeGuru Reviewer
    3. SonarQube
    4. Coverity
    5. PVS-Studio
    6. GitHub Copilot
    7. OpenAI GPT-4
    8. Llama 3

    AI recommended 8 alternatives but never named sashiko-dev/sashiko. 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 sashiko-dev/sashiko?
    pass
    AI named sashiko-dev/sashiko explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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