AD gongwen-format-pro
党政机关公文标准排版与质检校对技能，严格依据《党政机关公文格式》GB/T 9704-2012。当用户明确要求对公文做以下操作时使用：①排版——将 Markdown/TXT/DOCX/PDF(文本层) 草稿转换为国标合规的 Word 公文（红头、发文字号、2号小标宋标题、3号仿宋正文、一/（一）/1./（1）四级标题、附件、署名与成文日期、版记、页码）；②质检——扫描已有 .docx 公文，按高/中/低三级输出不合规清单与整改建议；③文风净化——在用户要求时，对口语、网络用语、AI 腔与常见错别字做表层规范化（实质性内容只标记不改写）。适用场景（需用户主动提出）：公文排版、红头文件、公文格式、发文格式、通知/请示/报告/函/纪要格式、发文字号、版记、GB/T 9704、公文质检、公文格式检查、公文校对纠错、统一公文文风、去口语化、去AI味、改成公务书面语、不规范 Word/TXT 重排为公文、检查已有公文是否合规。
党政机关公文标准排版与质检校对技能，严格依据《党政机关公文格式》GB/T 9704-2012。当用户明确要求对公文做以下操作时使用：①排版——将 Markdown/TXT/DOCX/PDF(文本层) 草稿转换为国标合规的 Word…
As a process D 46/100 · 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.
- 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: 17. 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") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1804 tokens
- 100Running it twice. No mutating operations
- low 11 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 412: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 30 items
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.