AF markdown-new
Convert public web pages into clean Markdown with markdown.new for AI workflows. Use when tasks require URL-to-Markdown conversion for summarization, RAG ingestion, extraction, archiving, or token reduction, including selecting conversion method (auto/ai/browser), enabling image retention, and handling rate limits or conversion failures.
Convert public web pages into clean Markdown with markdown.new for AI workflows. Use when tasks require URL-to-Markdown conversion for summarization, RAG…
As a process F 36/100 · Will not run — References files that are not bundled: scripts/..., references/...
How to improve
- The text references files that are not there: add them or drop the references.
- 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
missing-refreference to a missing file: scripts/... - warning
missing-refreference to a missing file: references/...
Process rating: all ten parameters 36/100
- 0Tools and files. 2 referenced file(s) missing: scripts/..., references/...
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (markdown-new) differs from the folder (markdown-convert)
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 26 steps
- 100Execution cost. Instruction body is 685 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
- +1No license
- +2Single-language instructions
- +3Description length 339: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.