Borrowing it
Nothing to install: this file belongs to MutharasuArchunan13/codebase-intel. 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/MutharasuArchunan13/codebase-intel/main/CLAUDE.mdgit clone --depth 1 https://github.com/MutharasuArchunan13/codebase-intelWrote 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/mutharasuarchunan13/codebase-intel/claude-md)<a href="https://agentmods.dev/instructions/mutharasuarchunan13/codebase-intel/claude-md"><img src="https://agentmods.dev/badge/instructions/mutharasuarchunan13/codebase-intel/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/mutharasuarchunan13/codebase-intel/claude-md"><img src="https://agentmods.dev/badge/instructions/mutharasuarchunan13/codebase-intel/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.01248 | $0.01248 |
| Opus 5.5 | $0.00499 | $0.00499 |
| Sonnet 5.5 | $0.00250 | $0.00250 |
| Haiku 4.5 | $0.00125 | $0.00125 |
Grade A, and why
codebase-intel 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 2mo 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Intel — Project CLAUDE.md
Project Overview
Codebase Intelligence Platform: an open-source, agent-agnostic system that provides AI coding agents with structured context, decision provenance, and quality contracts. Solves the three biggest gaps in AI-assisted development: context/memory, judgment/business context, and quality assurance.
Tech Stack
- Language: Python 3.11+
- Type System: Pydantic v2 for all models, mypy strict mode
- Storage: SQLite via aiosqlite (zero-dependency, portable)
- Parsing: tree-sitter for language-agnostic AST analysis
- Agent Interface: MCP (Model Context Protocol) server
- CLI: Typer + Rich
- Git Integration: GitPython
- Token Counting: tiktoken
- Hashing: xxhash for content fingerprinting
Architecture
Layered system with five core modules + two interface layers:
AI Agent (any) → MCP Server / CLI
↓
Context Orchestrator
↙ ↓ ↘
Code Graph Decisions Contracts
↘ ↓ ↙
Drift Detector
↓
Codebase (git)
Module Responsibilities:
- core/ — Shared types, config, exceptions. No business logic.
- graph/ — Semantic code graph: AST parsing, dependency mapping, impact analysis, SQLite storage
- decisions/ — Decision journal: structured records, git mining, code linking, temporal validation
- contracts/ — Quality contracts: architectural rules, pattern libraries, evaluation engine
- orchestrator/ — Context assembly: budget management, freshness scoring, conflict detection
- drift/ — Drift detection: staleness, pattern violations, knowledge decay
- mcp/ — MCP server: exposes all modules as queryable tools for AI agents
- cli/ — CLI interface: init, analyze, query, serve commands
Project Flow
codebase-intel init→ scans repo, builds initial code graph, generates starter configs- Git hooks keep graph updated incrementally on each commit
- AI agent connects via MCP → sends task description
- Orchestrator assembles relevant context (files, decisions, contracts) within token budget
- Agent receives structured context, writes code
- Drift detector flags violations post-commit
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.
- 2mo ago First seen · 104 lines · 1,248 tokens per session scan A 26e3ecac54dd
codebase-intel CLAUDE.md is an instructions file published in the GitHub repository MutharasuArchunan13/codebase-intel (5 stars, last pushed 2mo ago), licensed MIT. It adds 1,248 tokens to every session, about $0.0050 per session on Opus 5.5. 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.