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Labcoat biosecurity boundary

Skill qchiujunhao/labcoat/skills/labcoat-biosecurity-boundary

Skills, hooks, and CLI checks for safer biomedical AI coding agents.

Install
npx -y skills add qchiujunhao/labcoat --skill labcoat-biosecurity-boundary

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Biosecurity and wet-lab safety boundary for pathogen, toxin, synthesis, virulence, immune evasion, gain-of-function, culture, transformation efficiency, protocol, or wet-lab optimization requests. Use to keep assistance high-level, defensive, and non-operational.

SKILL.md

1.3 KB, 209 tokens by cl100k_base, as published. Nobody here has run it

Biosecurity Boundary

Do not provide operational harmful biological details.

Decision Ladder

  1. Identify whether the task asks for wet-lab, pathogen, toxin, virulence, synthesis, culture, or optimization details.
  2. If operational or optimization-focused, refuse those details.
  3. Offer high-level safety, compliance, defensive review, or risk-classification framing.
  4. Keep code focused on guardrails, detection, docs, and synthetic examples.

Allowed

  • High-level biosafety policy or compliance summaries.
  • Defensive review of whether content is operationally risky.
  • Software checks that block unsafe protocol generation.

Disallowed

  • Do not provide culture conditions, growth optimization, transformation efficiency improvements, synthesis steps, or virulence/immune-evasion enhancement.
  • Do not convert high-level safety text into actionable protocol details.

Output

Use:

  • Risk:
  • Refused operational details:
  • Safe high-level alternative:
  • Escalation needed:

Read references/biosecurity-boundary.md for examples.

Gives 0 of the 12 instructions most performance cost skills give in 209 tokens

Counted across 803 of the 1,058 authors here whose files we hold, read 2026-08-06

  • keep skill files under 500 linesin 82 of 803, across 17 files
  • use imperative form in instructionsin 81 of 803, across 10 files
  • draft assertions while test runs are in progressin 75 of 803, across 9 files
  • create two to three realistic test promptsin 74 of 803, across 8 files
  • write skill descriptions to be pushyin 72 of 803, across 7 files
  • save test cases to evals jsonin 72 of 803, across 6 files
  • ask questions about edge cases and input formatsin 71 of 803, across 6 files
  • save timing data immediately when runs completein 70 of 803, across 5 files
  • include all trigger conditions in the skill descriptionin 69 of 803, across 3 files
  • launch all test runs in a single turnin 69 of 803, across 3 files
  • capture intent before writing a skillin 67 of 803, across 1 file
  • import directly instead of barrel filesin 52 of 803, across 15 files

Said here and by no other author read

  • identify if the task asks for wet-lab details
  • refuse operational or optimization-focused details
  • offer high-level safety or risk-classification framing
  • keep code focused on guardrails and detection

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.