What is weightslab AGENTS.md?

Agent context for WeightsLab, a Python backend for recording machine-learning training data, and Weights Studio, a browser interface for inspecting and editing running experiments.

Use it when installing, configuring, running, inspecting, editing, or debugging WeightsLab and Weights Studio experiments.

It gives agents and developers installation, configuration, architecture, and debugging context without requiring them to reconstruct the system from the source.

How GrayboxTech/weightslab configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to GrayboxTech/weightslab. 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/GrayboxTech/weightslab/main/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/GrayboxTech/weightslab

Made for: Claude Code, 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/grayboxtech/weightslab/agents-md/github.svg)](https://agentmods.dev/instructions/grayboxtech/weightslab/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/grayboxtech/weightslab/agents-md"><img src="https://agentmods.dev/badge/instructions/grayboxtech/weightslab/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.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/grayboxtech/weightslab/agents-md"><img src="https://agentmods.dev/badge/instructions/grayboxtech/weightslab/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 4,997 This file is loaded in full into every session.

When invoked 4,997 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.

Model	Per session	Once invoked
Fable 5.1	$0.04997	$0.04997
Opus 5.5	$0.01999	$0.01999
Sonnet 5.5	$0.00999	$0.00999
Haiku 4.5	$0.00500	$0.00500

Measured 17d ago against content hash 604aad317fc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 17d 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 · 338 lines

How it starts

The opening of the file, as written. The whole thing — 338 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 as AGENTS.md; the repo keeps a gitignored CLAUDE.md copy of it at the root so Claude Code auto-loads it every session. Nothing to do. (Claude Code also loads ~/.claude/CLAUDE.md global memory and any parent-dir CLAUDE.md.)

You only ran pip install weightslab (no checkout — the package lives in site-packages): absolute @import paths 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.

Read the full file on GitHub · 338 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.

17d ago Changed · +13 lines · +316 tokens per session 604aad317fc5
1mo ago Changed · +14 lines · +357 tokens per session 920008c1a26c
2mo ago First seen · 311 lines · 4,324 tokens per session scan A b231b33207b5

Subscribe to this mod's changes

weightslab AGENTS.md is an instructions file published in the GitHub repository GrayboxTech/weightslab (175 stars, last pushed 7d ago), licensed Apache-2.0. It adds 4,997 tokens to every session, about $0.0200 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.

Data and AI Languages MLOps Model Debugging Python deep-learning machine-learning model-training open-source

weightslab AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
weightslab AGENTS.mdGrayboxTech/weightslab	Instructions file	175	7d ago	Apache-2.0	A	4,997	Claude Code, Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	9,719	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	yesterday	MIT	A	4,680	Codex, OpenCode
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	5,516	GitHub Copilot
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	yesterday	MIT	A	3,093	GitHub Copilot
deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness	Instructions file	274k	2d ago	MIT	A	4,313	Codex, OpenCode

weightslab: Instructions file for Claude Code