SKILLEMALL.ai

AC pharma-doc-reference

医药行业文档知识参考库——Universal Task OS的领域负载物。提供行业文档清单、内容要求清单、范本槽位,由UTOS执行轴动态编排管线、内容轴按清单法/样本法组织产出。触发词:医药、制药、药企、医学事务、市场部、推广部、合规、PV、药物警戒、KOL、学术会议、竞品分析、医保、招标、DRG、临床研究、DA、核心信息屋、Message House、ABP、品牌计划、准入、讲者、卫星会、CSR、ICSR、RMP、PSUR、医学写作、NDA、IND、CTA、BLA、ANDA、注册、法规、NMPA、FDA、GMP、QA、QC、供应链、生产、冷链、RWS、RWD、RWE、HTA、药物经济学、定价、谈判、科学拜访、客户分级、胜任力、培训、人才梯队、危机预案、跨部门协同、供应商管理、IIR、上市后研究、利益冲突、品牌视觉、入职培训、pharma、pharmaceutical。

ClawHub Agent Skills author: 波动几何 v1.0.1 MIT-0 5 files body ≈ 609 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceManufacturingInfrastructureLegaltype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
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

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 · 0

✓ No critical or high findings

Files scanned: 5. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 609 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 390: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

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

External checks

ClawHub: suspicious
This pharma reference skill is mostly documentation, but it tells the agent to automatically install and load another skill without a clear user approval step.
LLM: suspicious (high) · VirusTotal: · 29 May 2026