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BC pytdc

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

FreedomIntelligence/OpenClaw-Medical-Skills Agent Skills author: FreedomIntelligence 7 files · 3 scripts body ≈ 3 106 tokens Open the sourcegithub.com↗ analyzed 11 h ago

Therapeutics Data Commons.

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
95
Quality 40%
91
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

How to improve

    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/datasets.md:29
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `CYP2…els` - CYP2C9 substrate (666 compounds)
      quoted
    • low Secrets in code secret-high-entropy-token references/datasets.md:30
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `CYP2…els` - CYP2D6 substrate (664 compounds)
      quoted
    • low Secrets in code secret-high-entropy-token references/datasets.md:31
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `CYP3…els` - CYP3A4 substrate (667 compounds)
      quoted
    • low Secrets in code secret-high-entropy-token references/datasets.md:80
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `SARS…eem` - In vitro screening (5,953 compounds)
      quoted
    • low Secrets in code secret-high-entropy-token references/datasets.md:84
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - `M1_R…icz` - M1 receptor agonist (1,700 compounds)
      quoted

    Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 85Steps. 67 steps, 3 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3106 tokens
    • 100Running it twice. No mutating operations
    • low 13 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 181: enough signal without eating the budget
    • +4Structure: 43 headings
    • +3Step-by-step instructions: 67 items
    • +4Has examples (24 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.