RRepoGEO

REPOGEO REPORT · LITE

cased/kit

Default branch main · commit 80009db2 · scanned 5/21/2026, 10:37:08 PM

GitHub: 1,291 stars · 77 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
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 cased/kit, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Add a clarifying sentence to the README's opening

    Why:

    COPY-PASTE FIX
    Add this sentence to the README's opening paragraph: "Note: This `kit` repository is distinct from Cased.com's audit logging and access control products; it is solely focused on code intelligence for AI development."
  • mediumreadme#2
    Refine README opening to emphasize LLM/AI devtools

    Why:

    CURRENT
    kit 🛠️ Code Intelligence Toolkit

`kit` is a production-ready toolkit for codebase mapping, symbol extraction, code search, and building LLM-powered developer tools, agents, and workflows.
    COPY-PASTE FIX
    kit 🛠️ Code Intelligence Toolkit for LLM-Powered Devtools

`kit` is a production-ready toolkit for **AI devtools context engineering**, enabling you to build LLM-powered developer tools, agents, and workflows. It provides essential capabilities like codebase mapping, symbol extraction, and advanced code search to give your AI the right code context.

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 cased/kit
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tree-sitter
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Tree-sitter · recommended 2×
  2. pylsp · recommended 1×
  3. rust-analyzer · recommended 1×
  4. tsserver · recommended 1×
  5. Python's `ast` module · recommended 1×
  • CATEGORY QUERY
    How to provide accurate code context to LLMs for building developer tools?
    you: not recommended
    AI recommended (in order):
    1. Tree-sitter
    2. pylsp
    3. rust-analyzer
    4. tsserver
    5. Python's `ast` module
    6. Acorn
    7. Babel
    8. JDT (Eclipse JDT Core)
    9. syn crate
    10. OpenGrok
    11. Sourcegraph
    12. ctags
    13. etags
    14. OpenAI Embeddings
    15. Sentence-BERT
    16. Regular Expressions (Regex)

    AI recommended 16 alternatives but never named cased/kit. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What libraries help with codebase mapping and symbol extraction for AI-driven code analysis?
    you: not recommended
    AI recommended (in order):
    1. Tree-sitter
    2. LSP (Language Server Protocol) Implementations
    3. ANTLR (ANother Tool for Language Recognition)
    4. Clang
    5. JDT (Java Development Tools) Core
    6. Roslyn
    7. Esprima

    AI recommended 7 alternatives but never named cased/kit. 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 cased/kit?
    pass
    AI named cased/kit explicitly

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

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

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

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cased/kit — 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