Borrowing it
Nothing to install: this file belongs to maciek-O-digiaidev/CodeRAG. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/maciek-O-digiaidev/CodeRAG/main/CLAUDE.mdgit clone --depth 1 https://github.com/maciek-O-digiaidev/CodeRAGWrote 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/maciek-o-digiaidev/coderag/claude-md)<a href="https://agentmods.dev/instructions/maciek-o-digiaidev/coderag/claude-md"><img src="https://agentmods.dev/badge/instructions/maciek-o-digiaidev/coderag/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 5.1 | $0.01123 | $0.01123 |
| Opus 5 | $0.00562 | $0.00562 |
| Sonnet 5 | $0.00225 | $0.00225 |
| Haiku 4.5 | $0.00112 | $0.00112 |
Grade A, and why
CodeRAG CLAUDE.md scanned grade A with 0 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 6d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeRAG — Project Context for AI Agents
What is CodeRAG?
CodeRAG is an intelligent codebase context engine for AI coding agents. It creates a semantic vector database (RAG) from source code, documentation, and project backlog, then exposes it as MCP tools that give AI agents deep understanding of the entire codebase.
Architecture
Sources (Git, Jira, Confluence, MD)
→ Ingestion Pipeline (Tree-sitter AST, NL enrichment, metadata)
→ Embedding & Storage (LanceDB, BM25 index, dependency graph)
→ Retrieval Engine (hybrid search, graph expansion, re-ranking, token budget)
→ Agent Interface (MCP Server: coderag_search, coderag_context, coderag_status)
Tech Stack
- Language: TypeScript (Node.js, ESM)
- Code parsing: Tree-sitter (WASM bindings)
- Embedding (local): Ollama + nomic-embed-text
- Embedding (API): voyage-code-3, OpenAI text-embedding-3-small
- Vector DB: LanceDB (embedded, zero-infra)
- Keyword search: MiniSearch (BM25)
- NL Summarization: Ollama (qwen2.5-coder / llama3.2)
- MCP Server: @modelcontextprotocol/sdk
- CLI: Commander.js
- Testing: Vitest with coverage
- Package manager: pnpm workspaces
Project Structure
coderag/
├── packages/
│ ├── core/ # Core library: ingestion, embedding, retrieval
│ │ ├── src/
│ │ │ ├── ingestion/ # Tree-sitter parser, chunking, NL enrichment
│ │ │ ├── embedding/ # Provider abstraction, LanceDB, BM25
│ │ │ ├── retrieval/ # Hybrid search, graph expansion, context assembly
│ │ │ ├── config/ # .coderag.yaml parser
│ │ │ └── types/ # Shared TypeScript types
│ │ └── tests/
│ ├── cli/ # CLI tool (coderag init/index/search/serve/status)
│ │ ├── src/
│ │ └── tests/
│ ├── mcp-server/ # MCP server (stdio + SSE transport)
│ │ ├── src/
│ │ └── tests/
│ └── benchmarks/ # Benchmark suite
│ ├── datasets/
│ └── src/
├── .coderag.yaml # Project config (dogfooding!)
├── CLAUDE.md # This file
├── pnpm-workspace.yaml
└── tsconfig.base.json
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.
- 6d ago First seen · 87 lines · 1,123 tokens per session scan A 8e808069fb01
CodeRAG CLAUDE.md is an instructions file published in the GitHub repository maciek-O-digiaidev/CodeRAG (5 stars, last pushed 6mo ago), licensed MIT. It adds 1,123 tokens to every session, about $0.0056 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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