lab

A command for designing a small, learning-focused practice project that produces a sample artifact.

In plain words
What is it for?
It is for planning a toy workflow, fictional dataset, or sanitized artifact with milestones, recall checks, reflection, and a suggested follow-up review.
Why use it?
It gives learners a contained way to practise without operating on their real programme or work.

Command

Install

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.

agentmods
npx agentmods add commands/grcengineering/companion/lab
Clone the repo
git clone --depth 1 https://github.com/grcengineering/companion
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 154 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00016 $0.00154
Opus 5 $0.00008 $0.00077
Sonnet 5 $0.00003 $0.00031
Haiku 4.5 $0.00002 $0.00015

Measured 2d ago against content hash 26a1953cc01e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lab 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.

commands/lab.md · 27 lines

What it actually says

Lab Builder Command

Use when the learner wants to practise by building.

Flow

  1. Clarify the learner's role, level, goal, and timebox.
  2. Choose a toy workflow, fictional dataset, or sanitized artefact.
  3. Design three milestones.
  4. Add active recall checkpoints.
  5. End with a reflection prompt and next review suggestion.

Boundary

The lab may resemble work patterns, but it must not operate the learner's real programme.

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. 2d ago First seen · 27 lines · 16 tokens per session scan A 26a1953cc01e

Subscribe to this mod's changes

lab is a command published in the GitHub repository grcengineering/companion (32 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 154 once invoked, about $0.0001 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.