lambs: Instructions file for Codex

AGENTS.md

lambs AGENTS.md is an instructions file for Codex, OpenCode from dcroote/lambs. It costs 1,793 tokens per session, scanned A, original, Apache-2.0.

A guide for using LAMBS, a browser-based tool that analyzes antibody sequences and returns structured reports. Antibodies are proteins used by the immune system and in some medicines.

In plain words
What is it for?
Use it to analyze antibody heavy- and light-chain sequences, including checks for liabilities and likely ancestral gene segments.
Why use it?
It tells agents how to run the analysis and interpret validation errors without editing the project or copying its algorithms.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is dcroote/lambs's own configuration. It tells Codex and OpenCode how to work on lambs itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything lambs configures →

Reuse

Borrowing it

Nothing to install: this file belongs to dcroote/lambs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/dcroote/lambs/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/dcroote/lambs

Made for: Codex, OpenCode.

Wrote 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.

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README.md
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Per session 1,793 This file is loaded in full into every session.
When invoked 1,793 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01793 $0.01793
Opus 5.5 $0.00717 $0.00717
Sonnet 5.5 $0.00359 $0.00359
Haiku 4.5 $0.00179 $0.00179

Measured 2mo ago against content hash 1ceb5ad6b619, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lambs 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 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.

AGENTS.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LAMBS — guide for AI agents

This file serves two audiences. Jump to the section that matches the task.

If you are… Read
Using LAMBS to analyze antibody sequences (VH/VL, basket, liabilities, germline) Using LAMBS (analysis agents)
Changing LAMBS (bugs, features, tests, germline DB, UI in index.html) Developing LAMBS (contributor agents)

Product rule (both audiences): end users and analysis agents rely on one offline index.html. Do not introduce a second runtime artifact, npm install for users, or a parallel analysis implementation.


Using LAMBS (analysis agents)

Your job is to run analysis and consume structured results, not to edit the repo or reimplement algorithms.

How to run analysis

  1. Open index.html in a browser (file URL or static server).
  2. Prefer window.LAMBS over scraping the DOM.
Method Returns
LAMBS.analyzeMabReportFromRaw(vhRaw, vlRaw) { ok, report? | errors? } — preferred
LAMBS.analyzeSingle(vhRaw, vlRaw) Report object, or { ok: false, errors } on validation failure
LAMBS.analyzeMabReport(vhSeq, vlSeq) Report from cleaned AA strings
LAMBS.buildChainReport(varSeq, 'VH' | 'VL') Variable-region chain report
LAMBS.buildClusterReport(basket, threshold, filterNames) Cluster report
LAMBS.getHumanIgGEuNumbers(isotype) Eu index array for IGHG1–IGHG4, else null (IMGT Hu_IGHGnber)
LAMBS.mapEuOntoConstantAlignment(aligned2, species, isotype) Per-column Eu numbers for a CH alignment, or null
LAMBS.lambsReportToJSON(report) JSON string (no _constMatch / alignment blobs)
LAMBS.lastReport Last single-tab report after Analyze
LAMBS.lastClusterReport Last cluster report after Cluster & Analyze

Playwright / browser MCP:

await page.goto('file:///path/to/index.html');
const result = await page.evaluate((vh, vl) => LAMBS.analyzeMabReportFromRaw(vh, vl), vhRaw, vlRaw);

Read the full file on GitHub · 155 lines

Changes

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.

  1. 2mo ago First seen · 155 lines · 1,793 tokens per session scan A 1ceb5ad6b619

Subscribe to this mod's changes

lambs AGENTS.md is an instructions file published in the GitHub repository dcroote/lambs (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 1,793 tokens to every session, about $0.0072 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 2026-08-30.

Related

lambs AGENTS.md compared with instructions from other repositories

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