AD make-to-markdown
工业级RAG Markdown物料生成技能，使用 markitdown 将各类文档和文件转换为 Markdown 格式。支持 .doc/.ppt 老格式自动预处理（Word/PowerPoint COM / LibreOffice）。启动时自动检测 OS/版本/能力，按平台选择最佳执行路径。触发词：转 Markdown / 转换文档 / markitdown / 文档转 md / 批量转换。当需要将 PDF、Word (.docx/.doc)、PowerPoint (.pptx/.ppt)、Excel (.xlsx, .xls)、HTML、CSV、JSON、XML、图片（含 EXIF/OCR）、音频（含语音转写）、ZIP 压缩包、YouTube 链接或 EPub 电子书转换为 Markdown 格式，为知识库提供统一的"通用语言"时触发此技能。
工业级RAG Markdown物料生成技能，使用 markitdown 将各类文档和文件转换为 Markdown 格式。支持 .doc/.ppt 老格式自动预处理（Word/PowerPoint COM / LibreOffice）。启动时自动检测 OS/版本/能力，按平台选择最佳执行路径。触发词：转…
As a process D 45/100 · 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: 9. 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 45/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 48 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3180 tokens
- 100Progress reporting. Reports progress
- low 14 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 377: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 48 items
- +4Has examples (7 code blocks)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.