Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/sbdk-dev/local-ai-analyst/claude-mdgit clone --depth 1 https://github.com/sbdk-dev/local-ai-analystWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/sbdk-dev/local-ai-analyst/claude-md)<a href="https://agentmods.dev/instructions/sbdk-dev/local-ai-analyst/claude-md"><img src="https://agentmods.dev/badge/instructions/sbdk-dev/local-ai-analyst/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.02076 | $0.02076 |
| Opus 5 | $0.01038 | $0.01038 |
| Sonnet 5 | $0.00415 | $0.00415 |
| Haiku 4.5 | $0.00208 | $0.00208 |
Grade C, and why
local-ai-analyst CLAUDE.md scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -LsSf https://astral.sh/uv/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -LsSf https://astral.sh/uv/install.sh | sh How it starts
The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Analyst System - Semantic Layer Integration
Project Overview
Goal: Build a semantic layer-powered AI analyst that connects to Claude Desktop and ChatGPT Desktop via MCP (Model Context Protocol), enabling natural language data analysis with statistical rigor and incremental exploration.
Status: v1.0 Production Ready | 100% Test Pass Rate | 23 MCP Tools
Architecture
┌─────────────────────────────────────────────────────────┐
│ Claude Desktop / ChatGPT Desktop │
└────────────────────┬────────────────────────────────────┘
│ MCP Protocol (23 Tools)
┌────────────────────▼────────────────────────────────────┐
│ FastMCP Server │
│ ┌─────────────────────────────────────────────────┐ │
│ │ Multi-Query Workflow Engine │ │
│ │ • Dependency Resolution & Parallel Execution │ │
│ │ • 3 Built-in Analytical Workflows │ │
│ └─────────────────┬───────────────────────────────┘ │
│ │ │
│ ┌─────────────────▼───────────────────────────────┐ │
│ │ Query Optimization Engine │ │
│ │ • Intelligent Caching (95% hit rate) │ │
│ │ • Performance Learning │ │
│ └─────────────────┬───────────────────────────────┘ │
│ │ │
│ ┌─────────────────▼───────────────────────────────┐ │
│ │ Conversation Memory │ │
│ │ • 24-hour Context Window │ │
│ │ • Pattern Recognition │ │
│ └─────────────────┬───────────────────────────────┘ │
│ │ │
│ ┌─────────────────▼───────────────────────────────┐ │
│ │ Intelligence Layer │ │
│ │ • Statistical Testing │ │
│ │ • Natural Language Generation │ │
│ └─────────────────┬───────────────────────────────┘ │
│ │ │
│ ┌─────────────────▼───────────────────────────────┐ │
│ │ Semantic Layer (Ibis + DuckDB) │ │
│ │ • Product Analytics Models │ │
│ │ • Business Logic & Metrics │ │
│ └─────────────────┬───────────────────────────────┘ │
└────────────────────┼────────────────────────────────────┘
│
┌─────▼──────┐
│ DuckDB │
└────────────┘
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 293 lines · 2,076 tokens per session scan C 51bbc0e83861
local-ai-analyst CLAUDE.md is an instructions file published in the GitHub repository sbdk-dev/local-ai-analyst (1 stars, last pushed 9mo ago), licensed MIT. It adds 2,076 tokens to every session, about $0.0104 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
dbt_duckdb_demo_public CLAUDE.md
Instructions for edwinweber/dbt_duckdb_demo_public, covering claude.md — project context for ai assistants, project overview, tech stack, architecture and directory structure.
evidence AGENTS.md
AGENTS.md instructions for evidence-dev/evidence, covering agents.md, this repo is a mirror, layout and scripts.
evidence CLAUDE.md
Claude Code instructions for evidence-dev/evidence, a project described as: Business intelligence as code: build fast, interactive data visualizations in SQL and markdown.
Financial-API AGENTS.md
Instructions for HiThink-Tech/Financial-API, covering agents.md, 必读顺序, monorepo 边界, 选择接入方式 and api key.
chunkhound AGENTS.md
AGENTS.md instructions for chunkhound/chunkhound, covering chunkhound llm context, projectidentity, modificationrules, keycommands and development.
apple-health-mcp AGENTS.md
Instructions for neiltron/apple-health-mcp, covering repository guidance, project, validate changes, code map and invariants.