Borrowing it
Nothing to install: this file belongs to b1rdmania/legalise. 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/b1rdmania/legalise/master/AGENTS.mdgit clone --depth 1 https://github.com/b1rdmania/legaliseWrote 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/b1rdmania/legalise/agents-md)<a href="https://agentmods.dev/instructions/b1rdmania/legalise/agents-md"><img src="https://agentmods.dev/badge/instructions/b1rdmania/legalise/agents-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/b1rdmania/legalise/agents-md"><img src="https://agentmods.dev/badge/instructions/b1rdmania/legalise/agents-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 | $0.06083 | $0.06083 |
| Opus 5 | $0.03041 | $0.03041 |
| Sonnet 5 | $0.01217 | $0.01217 |
| Haiku 4.5 | $0.00608 | $0.00608 |
Grade A, and why
legalise AGENTS.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 9d 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 — 460 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Legalise — Agent Context (AGENTS.md)
This is the agent context file for Legalise. Coding agents pick it up automatically when working in the repo; you can also drop it into any AI agent or paste it into a chat to talk about Legalise — what it is, how it's built, and what it does and does not claim. It is a self-contained snapshot synthesised from the project's own docs (
README.md,docs/ARCHITECTURE.md,docs/TRUST.md,docs/THREAT_MODEL.md). The house rule throughout, the same one the codebase holds itself to: a capability is only described as live if the code implements it. Anything deferred, dormant, or unmounted is named as such.Repo: https://github.com/b1rdmania/legalise · Licence: Apache 2.0 · Status: open-source evaluation release, not for live client matters.
1. The one-paragraph version
Legalise is an open-source governance layer for legal AI: human sign-off plus a tamper-evident audit trail for AI-assisted legal work, built for England & Wales solicitor practice. It runs locally, you bring your own model key, and it is an evaluation release — not a regulated legal service. The whole system exists to make one loop legible:
draft → cite → sign-off → audit
AI prepares an output inside a matter, cites the documents it used, a named solicitor reviews and signs it (the signature pins the exact output by hash), and every step writes to an audit log the application cannot edit or delete. AI is preparation, not the deliverable. The audit trail makes the work inspectable; the signature makes a human accountable. The thesis is deliberately narrow: the machine signs its own record; the human signs the work — and the two are kept separate everywhere.
It's an early-stage, mostly solo project shared in the open — a working exploration of how this could be done, not a finished or proven product. Treat the claims below as "this is what the code does today", not "this is solved".
2. What it's built to answer (the four questions)
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.
- 9d ago First seen · 460 lines · 6,083 tokens per session scan A 1609b758e681
legalise AGENTS.md is an instructions file published in the GitHub repository b1rdmania/legalise (24 stars, last pushed 6d ago), licensed MIT. It adds 6,083 tokens to every session, about $0.0304 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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.