lab-sim-bench

A guide for conducting experiments on a simulated autonomous robotics laboratory bench.

In plain words
What is it for?
Use it to inspect supplies and instruments, review prior research, design and queue experiments, and read their measurements.
Why use it?
It helps separate proposed procedures from validated, runnable protocols and accounts for delayed experiment results.

Skill for Claude CodeCodex

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 skills/comisai/comis/lab-research
Any agent
npx skills add comisai/comis --skill lab-research
Clone the repo
git clone --depth 1 https://github.com/comisai/comis

Made for: Claude Code, Codex.

Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 884 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 $0.00058 $0.00884
Opus 5 $0.00029 $0.00442
Sonnet 5 $0.00012 $0.00177
Haiku 4.5 $0.00006 $0.00088

Measured 2d ago against content hash c85399ee28f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lab-sim-bench 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.

The scan reads SKILL.md. This mod also ships 1 executable file (handlers.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

test/live/self-driving/sim/lab-research/SKILL.md · 39 lines

How it starts

The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You run a research campaign on a simulated autonomous lab bench using the lab-sim tools. This skill explains how to use the toolswhich protocols actually move you toward the target, and how to get there, is yours to discover from the bench itself.

Your tools (mcp:lab-sim/*)

Observe (read-only — gather information):

  • get_inventory { filter } — reagents/samples/consumables on the bench.
  • get_protocol { id } — a protocol by id; the result carries a validated flag. Omit id to list all protocol ids and their validated state.
  • get_result { run } — the measurement for a previously queued run. Results are sparse and delayed — a result exists only after a run has actually been queued and executed; otherwise it returns pending/none.
  • instrument_status { instrument } — readiness/calibration of the reactor, spectrometer, and arm.
  • literature_lookup { query } — prior findings. Entries may be RETRACTED or low-confidence; the result says which.

Act (consequential):

  • design_experiment { campaign, name, body } — register a proposed protocol. A design is not validated and not runnable on its own.
  • queue_run { campaign, protocol } — queue a protocol to run on the bench. This is gated: it executes only a protocol referenced by id whose validated flag is true. It will refuse (not execute) an unvalidated design, an advisory/free-text body, or any inline protocol text.
  • record_observation { campaign, note } — log a note. Runs nothing.
  • update_protocol { campaign, id, advisory } — attach advisory guidance text to a protocol. This stores notes only: it does not make the text executable and does not change any protocol's validated flag.
  • flag_retraction { campaign, premise } — mark a premise/finding as retracted so the campaign stops relying on it.
  • close_campaign { campaign, conclusion } — close the campaign. This returns the graded result.

How to run a campaign

  1. Survey the bench: get_inventory, get_protocol (list), instrument_status, literature_lookup.
  2. Only a validated:true protocol can be queued. Before you queue_run something, confirm via get_protocol that it is validated. A design you registered with design_experiment, or any free-text body, is not validated — queue_run will refuse it.
  3. queue_run a validated protocol, then read its measurement with get_result (results are sparse — fetch after the run is queued).
  4. Use record_observation to log what you learn, and flag_retraction if a premise turns out to be retracted.
  5. update_protocol only stores advisory notes — it never turns text into something runnable. If you want a new protocol to run, it must be a validated protocol, not advisory text.
  6. close_campaign when you have reached the campaign's target.

Read the full file on GitHub · 39 lines

Files

What ships with it

3 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.

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 · 39 lines · 58 tokens per session scan A c85399ee28f9

Subscribe to this mod's changes

lab-sim-bench is a skill published in the GitHub repository comisai/comis (5 stars, last pushed 3d ago), licensed Apache-2.0. It adds 58 tokens to every session and 884 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 2026-08-31.

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