RRepoGEO

REPOGEO REPORT · LITE

backnotprop/plannotator

Default branch main · commit 90bc8f8d · scanned 6/20/2026, 12:36:41 AM

GitHub: 6,346 stars · 448 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)

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

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 backnotprop/plannotator, 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 primary value proposition to the very top

    Why:

    CURRENT
    <strong>Everything you need to annotate and stay in the loop with your agents</strong>
    COPY-PASTE FIX
    <strong>Plannotator: Your dedicated, local review surface for AI coding agents.</strong>
  • mediumtopics#2
    Add broader, more descriptive topics for better categorization

    Why:

    CURRENT
    agents, claude-code, code-review, codex, obsidian, opencode, pi-mono, plan-mode, skills
    COPY-PASTE FIX
    agents, claude-code, code-review, codex, obsidian, opencode, pi-mono, plan-mode, skills, ai-development, agent-workflow, llm-ops, code-annotation, visual-review
  • lowreadme#3
    Clarify the specific types of 'plans' and 'artifacts' Plannotator reviews

    Why:

    CURRENT
    <sub>Annotate plans, specs, markdown, and HTML before implementation. Review diffs and PRs. Send feedback to your agent.</sub>
    COPY-PASTE FIX
    <sub>Annotate AI agent-generated coding plans, technical specifications, markdown, and HTML artifacts before implementation. Review code diffs and pull requests. Send direct feedback to your agent.</sub>

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 backnotprop/plannotator
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Figma
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Figma · recommended 2×
  2. GitHub · recommended 2×
  3. GitLab · recommended 2×
  4. Mermaid.js · recommended 1×
  5. PlantUML · recommended 1×
  • CATEGORY QUERY
    How can I visually review AI agent generated code plans and provide feedback?
    you: not recommended
    AI recommended (in order):
    1. Mermaid.js
    2. PlantUML
    3. Draw.io
    4. Draw.io Integration
    5. Mermaid Preview
    6. Figma
    7. Miro
    8. GitHub
    9. GitLab
    10. D3.js
    11. React Flow

    AI recommended 11 alternatives but never named backnotprop/plannotator. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to annotate code diffs, markdown, and HTML artifacts for team collaboration?
    you: not recommended
    AI recommended (in order):
    1. GitHub
    2. GitLab
    3. Bitbucket
    4. Review Board
    5. Figma
    6. Jira
    7. Fisheye
    8. Crucible
    9. VS Code Live Share
    10. Annotate.co
    11. Hypothesis

    AI recommended 11 alternatives but never named backnotprop/plannotator. 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 backnotprop/plannotator?
    pass
    AI named backnotprop/plannotator explicitly

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

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

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

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backnotprop/plannotator — 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