BD medxpert-doc-toolchain
MedXpert 名片风格文档模板工具链。覆盖文档全生命周期：模板生成（T02/T03/T04/三版纸张）→ 收尾流水线（水印/暗纹/动态溯源/AI友好头/徽章/解锁）→ 导出（PDF/DOCX）→ 台账编号 → 审批流 → 电子签名 → 中英对照 → 乐享托管。触发场景：生成医疗器械/ISO13485 体系文档、程序文件、质量手册；文档收尾（品牌水印/溯源/解锁）；PDF/DOCX 导出；文档台账与编号；审批流与电子签名；中英对照翻译；文控体系搭建。当用户说「生成文档模板」「文档收尾」「加溯源水印」「文档台账」「电子签名」「中英对照」「文控体系」时加载本技能。
MedXpert 名片风格文档模板工具链。覆盖文档全生命周期：模板生成（T02/T03/T04/三版纸张）→ 收尾流水线（水印/暗纹/动态溯源/AI友好头/徽章/解锁）→ 导出（PDF/DOCX）→ 台账编号 → 审批流 → 电子签名 → 中英对照 → 乐享托管。触发场景：生成医疗器械/ISO13485…
As a process D 43/100 · 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 Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 8, column 17: description_en: MedXpert business-card-style document template toolchain: templ… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 284 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "title" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "description_zh" - note
frontmatter-keyunknown frontmatter key "description_en" - note
frontmatter-keyunknown frontmatter key "xiaping_category" - note
frontmatter-keyunknown frontmatter key "xiaping_tags" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 43/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 651 tokens
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
- -2localhost URLs: will not work for another user
- +2Single-language instructions
- +3Description length 284: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 52.