AD pdf2md-universal
通用 PDF→Markdown 转换器。当用户需要把 PDF（研报/财报/招股书/论文/电子书/扫描件）转成 Markdown 再阅读或喂给 AI、或担心直接把 PDF 发给 AI 会消耗大量 token 时使用。三层策略：文本型 PDF 用 pdftotext 免费抽取、扫描型 PDF 自动 OCR 兜底、转换后输出 token 对比报告。Triggers: PDF转Markdown, 把PDF转成md, PDF怎么省token, 扫描版PDF提取文字, convert PDF to markdown, pdf 转 md, PDF转文档.
通用 PDF→Markdown 转换器。当用户需要把 PDF（研报/财报/招股书/论文/电子书/扫描件）转成 Markdown 再阅读或喂给 AI、或担心直接把 PDF 发给 AI 会消耗大量 token 时使用。三层策略：文本型 PDF 用 pdftotext 免费抽取、扫描型 PDF 自动 OCR…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: 通用 PDF→Markdown 转换器。当用户需要把 PDF（研报/财报/招股书/论文/电子书/扫描件）转成 Markdown 再阅… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - 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 (python) that frontmatter does not declare
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 463 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 273: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (2 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.