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BC bios-deep-research

Run deep biological research using the BIOS API. Supports API key and x402 crypto payments (USDC on Base). Start-and-check-back pattern works across heartbeats.

modbender/skill-library-mcp Claude Code author: modbender MIT 2 files body ≈ 1 991 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Run deep biological research using the BIOS API.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
76
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token references/x402-setup.md:118
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "verifyingContract": "0x83…913"
    quoted
  • low Exfiltration net-credential-use SKILL.md:49
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    **Use `curl` via `exec` for all BIOS API calls. Do NOT use `web_fetch` — it does not support Authorization headers.** Reference secrets via environment variable (`$BIOS_API_KEY`), never hardcode them
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:74
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "asset": "0x83…913",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:76
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "payTo": "0x4b…7e0",
    quoted
  • low Exfiltration net-credential-use SKILL.md:212
    Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)
    - Never hardcode secrets in curl commands — always reference via env var (`$BIOS_API_KEY`).
    detector

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 52/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 5 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 100Steps. 39 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1991 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 160: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 39 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.