CD med-medical-term-normalization
将口语化通用医学记录转换为标准化、规范化的医学记录。输入口语化病历文本，调用内部医疗大模型，输出符合临床病历书写规范的标准化记录（术语规范、表述严谨、数据规范、结构规范）。
将口语化通用医学记录转换为标准化、规范化的医学记录。输入口语化病历文本，调用内部医疗大模型，输出符合临床病历书写规范的标准化记录（术语规范、表述严谨、数据规范、结构规范）。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 41/100
- 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
- 40Consistency. Frontmatter name (med-medical-term-normalization) differs from the folder (unisound-medical-term-normalization)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 27 steps
- 100Execution cost. Instruction body is 856 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)
- +3Description length 86: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 7 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (5 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.
External checks
ClawHub: suspicious
The skill’s medical-record normalization purpose is clear, but it can send sensitive records and an API key to any configured endpoint and can leave plaintext medical data on disk despite privacy wording that suggests otherwise.
LLM: suspicious (high) · VirusTotal: · 16 Sept 2026