Borrowing it
Nothing to install: this file belongs to LegalQuants/Donna. 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/LegalQuants/Donna/main/CLAUDE.mdgit clone --depth 1 https://github.com/LegalQuants/DonnaWrote 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/legalquants/donna/claude-md)<a href="https://agentmods.dev/instructions/legalquants/donna/claude-md"><img src="https://agentmods.dev/badge/instructions/legalquants/donna/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/legalquants/donna/claude-md"><img src="https://agentmods.dev/badge/instructions/legalquants/donna/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 | $0.03770 | $0.03770 |
| Opus 5 | $0.01885 | $0.01885 |
| Sonnet 5 | $0.00754 | $0.00754 |
| Haiku 4.5 | $0.00377 | $0.00377 |
Grade A, and why
Donna CLAUDE.md scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
it; raw `curl` doesn't, so a hand-forged `curl` login will 403/404. Test login via Playwright. How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — engineering guide for Donna
This file orients a coding co-pilot — a human developer or another AI agent (Claude Code reads it automatically on session start) — so you can understand the whole project and pick up the roadmap from where it stands. Read it once, top to bottom, before your first change.
For what the product is and why, read docs/PRODUCT.md first. For how to run it, README.md. This file is how to build in it well.
1. What Donna is, in one breath
Donna is a standalone SvelteKit app — a friendly, document-forward frontend for the LQ.AI legal-AI backend. Donna implements no legal-AI logic itself: retrieval, the citation engine, anonymization, skills, playbooks, tabular review, and the autonomous runtime all live in lq-ai. Donna's job is to make that power usable, transparent, and controllable through a clean reading-first UI.
Donna talks to lq-ai only through its published API, and vendors that backend as a pinned
git submodule (vendor/lq-ai) so the whole product runs from one compose file.
2. The cardinal rules (violate these and you'll break the project's model)
- Never edit
vendor/lq-ai. It is a pinned submodule, not our code. If you need backend behavior that doesn't exist, that's an upstream request (§8), not a local patch. - Consume the contract; never hand-fork it. API types are generated from lq-ai's OpenAPI into
src/lib/api/backend.d.tsvianpm run gen:api. Derive types from there. (Where the backend types a field loosely —additionalProperties— hand-type it in a small parser and say so in a comment; see theparseTabularResults/parseFindingListprecedents.) - The bar is green, not "no worse."
npm run check= 0 errors / 0 warnings;npm run lint= prettier + eslint fully clean; the unit suite passes. Keep it that way. - Merge PRs with a MERGE COMMIT. A squash would orphan the two one-time-format SHAs in
.git-blame-ignore-revs. Never squash tomain. - Evidence before claims. "It works" requires a run you can point to — a passing test, a live e2e, an actual page load. Report failures faithfully.
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.
- 10d ago First seen · 231 lines · 3,770 tokens per session scan A d3d687a77a42
Donna CLAUDE.md is an instructions file published in the GitHub repository LegalQuants/Donna (24 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 3,770 tokens to every session, about $0.0188 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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