Borrowing it
Nothing to install: this file belongs to wellwelwel/lagune. 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/wellwelwel/lagune/main/CLAUDE.mdgit clone --depth 1 https://github.com/wellwelwel/laguneWrote 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/wellwelwel/lagune/claude-md)<a href="https://agentmods.dev/instructions/wellwelwel/lagune/claude-md"><img src="https://agentmods.dev/badge/instructions/wellwelwel/lagune/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 | $0.02619 | $0.02619 |
| Opus 5 | $0.01309 | $0.01309 |
| Sonnet 5 | $0.00524 | $0.00524 |
| Haiku 4.5 | $0.00262 | $0.00262 |
Grade A, and why
lagune 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 8d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SDH (Security-Driven Hardening): Lagune
This file orients any AI agent (and human) working in this repository. Read it fully before making changes. It describes what Lagune is, who it is for, how it is built, and how to work in this codebase. For the file/folder layout and concrete structure, invoke the internal
/architectureskill, for the toolchain, code conventions, and build path, the/engineeringskill, and for the language conventions and how to write Lagune's prose, the/writerskill.
1. What this workspace is
This workspace is the development environment for Lagune.
Lagune is the practice of Security-Driven Hardening (SDH): a structured, AI-driven security workflow. Lagune turns a codebase into a more secure one, driving the work from a spec the agent runs rather than from ad-hoc fixes.
The project stands in the tradition of Blue Teams: the defenders in security. Lagune is about defense, hardening, and verification, never offense.
The problem it exists to solve
Software is increasingly shipped by people, and AI agents, who cannot reliably recognize an insecure pattern: a leaked secret, a missing authorization check, an injectable query. AI coding assistants made this acute by letting non-developers ship real software, but the gap is broader than any one audience. Most projects never get a security pass that is specific to what they actually do. The ecosystem becomes more fragile with every "it works, ship it" moment.
Lagune's mission is to put a defensive, security-first workflow within reach of any user, by making the AI agent do the heavy lifting: detecting what a system actually is, and guiding it toward the security practices that matter for that system, in a safe-by-default way.
What Lagune actually ships
Lagune is a collection of templates and agent commands, not a heavy framework. Its value is the workflow the AI agent runs: detecting what the system actually does (login, uploads, payments, and so on), mapping the vulnerabilities that matter for that context, then proposing, applying, and validating the right fixes. The context detection is what makes the rest specific instead of generic.
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.
- 8d ago First seen · 96 lines · 2,619 tokens per session scan A 90bac24c7a62
lagune CLAUDE.md is an instructions file published in the GitHub repository wellwelwel/lagune (147 stars, last pushed 8d ago), licensed MIT. It adds 2,619 tokens to every session, about $0.0131 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 2026-08-30.
Other instructions, from other repositories
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.