AC html-ocr
OCR for HTML pages containing image-embedded or scanned content. Uses MinerU to extract text from images within HTML files and web pages. Features: OCR extraction for image content in HTML files. VLM mode for complex mixed-content pages. Handles HTML with embedded scanned images. Converts image text to searchable Markdown. Use when you need to: OCR images in HTML pages, extract text from image-heavy web pages, read scanned content embedded in HTML. Use when asked: 'how do I OCR an HTML page', 'extract text from images in HTML', 'this web page has images instead of text', 'can my agent OCR HTML content', 'is there a skill for HTML OCR'. Built on MinerU by OpenDataLab (Shanghai AI Lab) with advanced OCR capabilities. Perfect for web archiving, accessibility improvements, and content extraction from image-heavy web pages.
As a process C 56/100 · 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 "homepage"
Process rating: all ten parameters 56/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 352 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
- +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 830: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 6 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.