REPOGEO REPORT · LITE

yvgude/lean-ctx

Default branch main · commit 1cc3dd42 · scanned 6/25/2026, 9:26:49 PM

GitHub: 2,929 stars · 283 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)

3 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 yvgude/lean-ctx, 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

Add explicit disclaimer to README's opening to prevent Lean 4 miscategorization

Why:

CURRENT

### **Control what your AI can see.LeanCTX — Lean Context Engineering for AI agents**

LeanCTX — short for **Lean Context** — is the context engineering layer for AI agents.

COPY-PASTE FIX

### **Control what your AI can see. LeanCTX — Lean Context Engineering for AI agents**

**Note: LeanCTX is a Rust-based context intelligence layer for AI agents, NOT a Lean 4 library.**

LeanCTX — short for **Lean Context** — is the context engineering layer for AI agents.

mediumreadme#2

Add a comparison section to the README

Why:

COPY-PASTE FIX

Add a new section to the README, for example, 'Why LeanCTX? (Compared to LangChain, LlamaIndex, etc.)', detailing how LeanCTX differentiates itself (e.g., local-first, token reduction, context intelligence layer, security, verifiable savings ledger) from popular AI agent frameworks.

lowtopics#3

Add 'lean-ctx' to repository topics

Why:

CURRENT

agentic-coding, ai, ai-agents, ai-coding, claude-code, context-engineering, context-intelligence, context-layer, copilot, cursor, developer-tools, gemini-cli, lean-context, llm, mcp, mcp-server, reduce-token-costs, rust, token-optimization

COPY-PASTE FIX

agentic-coding, ai, ai-agents, ai-coding, claude-code, context-engineering, context-intelligence, context-layer, copilot, cursor, developer-tools, gemini-cli, lean-context, lean-ctx, llm, mcp, mcp-server, reduce-token-costs, rust, token-optimization

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 yvgude/lean-ctx

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LangChain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

LangChain · recommended 1×
LlamaIndex · recommended 1×
OpenAI API · recommended 1×
Cohere · recommended 1×
Haystack · recommended 1×

CATEGORY QUERY
How to reduce LLM token costs and manage AI agent context effectively?
you: not recommended
AI recommended (in order):
1. LangChain
2. LlamaIndex
3. OpenAI API
4. Cohere
5. Haystack
6. Deepinfra
7. LiteLLM
AI recommended 7 alternatives but never named yvgude/lean-ctx. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Local-first context intelligence layer for AI agents to control data access?
you: not recommended
AI recommended (in order):
1. Chroma
2. LanceDB
3. DuckDB
4. SQLite
5. FAISS
6. HNSWlib
7. Qdrant
8. Milvus Lite
AI recommended 8 alternatives but never named yvgude/lean-ctx. 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 yvgude/lean-ctx?
pass
AI named yvgude/lean-ctx explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts yvgude/lean-ctx in production, what risks or prerequisites should they evaluate first?
pass
AI named yvgude/lean-ctx 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 yvgude/lean-ctx solve, and who is the primary audience?
pass
AI named yvgude/lean-ctx explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of yvgude/lean-ctx. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/yvgude/lean-ctx.svg)](https://repogeo.com/en/r/yvgude/lean-ctx)

HTML

<a href="https://repogeo.com/en/r/yvgude/lean-ctx"><img src="https://repogeo.com/badge/yvgude/lean-ctx.svg" alt="RepoGEO" /></a>

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yvgude/lean-ctx — 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