AD word-formatter
专业 Word 文档（.docx）后期排版、合规校验与图件处理技能，专注五类客户交付型咨询报告：①财务尽职调查报告 ②法律/综合尽职调查报告 ③风险评估报告（综合/COSO）④财税风险评估报告 ⑤财务分析报告。当前版本 v1.0.0「黑灰白」(2026-07-29)：配置驱动排版、5 类报告全配置、封面专业垂直分布（+分节符）、页眉双栏（客户名左+报告类型右）、Heading 1-6 层级规范、三线表/全线表、纯 Python 结构化图件渲染器。设计语言极度克制：仅黑/白/灰三色，无任何彩色（深蓝/深红等均禁用）。当用户要求对 Word 文档进行排版、格式规范化、样式统一，或提到"按尽调/风险评估/财务分析规范排版""修复 Word 格式""排版不符合要求""格式校验""插入流程图/股权架构图/风险矩阵"时使用。基于 python-docx 配置驱动排版。
专业 Word 文档（.docx）后期排版、合规校验与图件处理技能，专注五类客户交付型咨询报告：①财务尽职调查报告 ②法律/综合尽职调查报告 ③风险评估报告（综合/COSO）④财税风险评估报告 ⑤财务分析报告。当前版本 v1.0.0「黑灰白」(2026-07-29)：配置驱动排版、5…
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.
- 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: 15. 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 "agent_created" - note
frontmatter-keyunknown frontmatter key "build"
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 (python) that frontmatter does not declare
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1540 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
- +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
- +5Description quotes 4 example trigger phrases
- +3Description length 383: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.