Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/grayboxtech/weightslab/agents-mdgit clone --depth 1 https://github.com/GrayboxTech/weightslabWhat 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 | $0.04324 | $0.04324 |
| Opus 5 | $0.02162 | $0.02162 |
| Sonnet 5 | $0.00865 | $0.00865 |
| Haiku 4.5 | $0.00432 | $0.00432 |
Grade A, and why
weightslab 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 2d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WeightsLab — agent context for users & debugging
This file is a portable context for AI coding agents (Claude Code, etc.) and the humans driving them. Its job is to let you — or an agent helping you — install, configure, run, and debug WeightsLab and Weights Studio without having to reverse-engineer the system first.
It deliberately covers only the two shipped repositories:
- weightslab — the Python backend / core (training instrumentation, data ledger, gRPC service, the shared proto).
- weights_studio — the browser frontend (the studio UI that inspects and edits a running experiment).
File/line references drift as the code evolves — treat them as starting points and verify against the current source before relying on them. Environment variable names and defaults are the most stable thing here; when in doubt the authoritative reference is
weightslab/docs/configuration.rst.
0. How to load this guide into Claude Code
So an agent actually has this context when you ask it for help:
-
Working inside a checkout of the repo (
git clone): this guide is committed asAGENTS.md; the repo keeps a gitignoredCLAUDE.mdcopy of it at the root so Claude Code auto-loads it every session. Nothing to do. (Claude Code also loads~/.claude/CLAUDE.mdglobal memory and any parent-dirCLAUDE.md.) -
You only ran
pip install weightslab(no checkout — the package lives insite-packages): absolute@importpaths are fragile because the path changes per venv/OS. The robust pattern is a small skill that locates the installed file at runtime. Create~/.claude/skills/weightslab/SKILL.md:--- name: weightslab description: Load the WeightsLab debugging & configuration guide when helping with weightslab or weights_studio problems (connection, TLS, env vars, training hangs, rendering). --- !`python -c "import weightslab, os; print(open(os.path.join(os.path.dirname(weightslab.__file__), 'AGENTS.md')).read())"` Use the guide above to diagnose the user's weightslab / weights_studio issue.
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.
- 2d ago First seen · 311 lines · 4,324 tokens per session scan A b231b33207b5
weightslab AGENTS.md is an instructions file published in the GitHub repository GrayboxTech/weightslab (167 stars, last pushed 4d ago), licensed Apache-2.0. It adds 4,324 tokens to every session, about $0.0216 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
zero-to-ai snyk_rules.instructions.md
Snyk Security At Inception.
opsml CLAUDE.md
Claude Code instructions for demml/opsml, covering claude.md and claude code notes.
opsml AGENTS.md
AGENTS.md instructions for demml/opsml, covering agents.md, what opsml is, common commands, task runner and rust.
streamlit copilot-instructions.md
Copilot instructions for streamlit/streamlit, covering streamlit repo overview, tech stack, folder structure, shell & build policy and make commands.
skypilot AGENTS.md
Instructions for skypilot-org/skypilot, covering claude.md - skypilot development guide, project overview, repository structure, development setup and environment setup.
zenml CLAUDE.md
Instructions for zenml-io/zenml, covering zenml claude code guidelines, project structure, use zenml docs via mcp, code style & quality standards and commenting policy — explain why, not what.