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 skills/grcengineering/companion/lab-buildernpx skills add grcengineering/companion --skill lab-buildergit clone --depth 1 https://github.com/grcengineering/companionWhat 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 | $0.00062 | $0.00569 |
| Opus 5 | $0.00031 | $0.00284 |
| Sonnet 5 | $0.00012 | $0.00114 |
| Haiku 4.5 | $0.00006 | $0.00057 |
Grade A, and why
lab-builder 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lab-builder
What
Generate a project-based learning lab that helps the learner build a small artefact without operating their real GRC programme.
When
- The learner wants hands-on practice.
- The learner wants a portfolio project.
- The learner wants to learn a concept by building something small.
- The learner has a role-specific learning goal and needs a concrete exercise.
Not For
- Producing final policies, audit evidence, live vendor decisions, or control outputs.
- Turning sensitive company artefacts into deliverables.
- Question-led discovery before a lab exists. Use
socratic-coach.
Inputs
- Optional profile template:
assets/profile-template.md - Role prompt templates:
assets/templates/employed.mdassets/templates/job-seeking.mdassets/templates/career-transition.md
Steps
- Gather only learning-safe learner context.
- Clarify the learning objective and timebox.
- Choose a toy workflow, fictional dataset, or sanitized artefact.
- Sequence the lab into small milestones.
- Add at least one active recall checkpoint.
- Add a reflection question and one next review suggestion.
Validation
- The lab can be completed inside the stated time budget.
- The artefact is demonstrably learning-safe and non-operational.
- The learner has build steps, recall checks, and a reflection close.
Gotchas
- If the learner provides company-specific data, refuse to process it as evidence and ask for a fictional substitute.
- If the requested lab exceeds the timebox, cap milestones at the budget and defer the rest.
- If no learning-safe artefact exists, switch to
socratic-coachorconcept-tutorbefore building.
Failure Modes
- Lab becomes consulting: remove real approval, remediation, audit, policy, or control actions.
- Lab is too big: split into a 30-90 minute first rep.
- Lab is too abstract: require a small output such as a toy checklist, map, script, table, or explainer.
Examples
- User asks for a portfolio project in TPRM -> Create a fictional vendor intake dataset and a toy risk-signal map with explain-back questions.
- User wants to understand evidence automation -> Build a small local CSV-to-summary exercise using fake control evidence rows.
- User asks for help preparing a live audit -> Refuse the operational prep, then offer a fictional audit walkthrough lab.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 65 lines · 62 tokens per session scan A 09cf1c91b599
lab-builder is a skill published in the GitHub repository grcengineering/companion (32 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 569 once invoked, about $0.0003 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.
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