SKILLEMALL.ai

BC doc-analysis

Analyze the structure, layout, and content of Word documents (.doc, .docx) using MinerU. Returns structured Markdown with headings, paragraphs, tables, and layout information preserved. Features: deep document analysis preserving structure hierarchy. Extracts headings, lists, tables, and paragraph boundaries. Supports legacy .doc and modern .docx. Full analysis mode reveals document layout and formatting patterns. Use when you need to: analyze a Word document's content, understand document structure, inspect layout of a .docx file, get a structural overview of a Word file. Use when asked: 'how do I analyze this Word document', 'what is the structure of this docx', 'I want to understand this Word file layout', 'can my agent analyze a Word document', 'break down this .doc file for me'. Built on MinerU by OpenDataLab (Shanghai AI Lab), an open-source document intelligence engine. Supports English, Chinese, and multilingual content. Works with local files and URLs. Perfect for researchers, editors, and quality assurance teams who need to understand document structure before processing, editing, or converting Word files.

ClawHub Agent Skills author: mzlzyCA v0.4.0 MIT-0 2 files body ≈ 384 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerWordInfrastructureAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
55
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
For the model run — optional
  • 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

  • error description-long description is 1133 chars, limit 1024
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 384 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 1133: 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: 55.

External checks

ClawHub: clean
This looks like a document-extraction helper, but users should assume files or URLs they process may be sent to MinerU for extraction.
LLM: benign (medium) · VirusTotal: · 29 May 2026