AF pharma-ai
智能药物发现AI助手，提供分子毒性预测、ADMET评估和虚拟筛选功能。 基于Python科学计算核心(RDKit + scikit-learn)和Node.js Skill包装。 Use when: - 需要预测分子的hERG心脏毒性、肝毒性或Ames致突变性 - 需要评估分子的溶解度、代谢稳定性等ADMET性质 - 需要从化合物库中筛选候选药物 - 需要验证分子是否符合Lipinski五规则 - 需要批量分析分子数据 Supports: SMILES输入, CSV批量处理, 实时预测
As a process F 35/100 · Will not run — References files that are not bundled: references/manual.md, references/roadmap.md
ProcedureInfrastructureData and analyticstype and topics are labelled automatically from the skill text
How to improve
- The text references files that are not there: add them or drop the references.
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 · 0
✓ No critical or high findings
Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/manual.md - warning
missing-refreference to a missing file: references/roadmap.md
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: references/manual.md, references/roadmap.md
- 0Tools and files. 2 referenced file(s) missing: references/manual.md, references/roadmap.md
- 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
- 100Steps. 15 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 391 tokens
- 100Running it twice. No mutating operations
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 247: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
This skill appears to be a prototype drug-discovery tool, but it advertises safety-related ADMET and Lipinski analysis that the code does not actually compute and includes unrelated ClawHub token/publishing instructions.
LLM: suspicious (high) · VirusTotal: · 29 May 2026