AC pdf-markdown-converter
Convert PDF documents to clean, well-formatted Markdown using the MinerU API. This skill uses mineru-open-api CLI to transform PDFs into Markdown with preserved structure, headings, lists, tables, formulas, and images. Supports token-free flash-extract for instant conversion and precision extract for complex academic papers and technical documents. Use when asked to 'convert PDF to Markdown', 'PDF to md', 'turn my PDF into Markdown', 'PDF转Markdown', 'PDF转md格式', 'how to get Markdown from PDF', 'export PDF as Markdown', 'PDF to GitHub readme', 'extract PDF content as Markdown', 'can you convert this PDF to text format', 'make this PDF editable'. Handles academic papers, research reports, technical manuals, books, and multi-column layouts. Ideal for knowledge base building, technical documentation, blog publishing, and converting research papers for version control.
As a process C 53/100 · Has gaps — 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "tools"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 245 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)
- +3Description length 875: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 4 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.