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AC word-parser

Parse and extract structured content from Word documents (.docx, .doc) using the MinerU API. This skill uses mineru-open-api CLI to parse Word files into structured data including headings, paragraphs, tables, images, lists, and metadata. Supports flash-extract for quick parsing (no token) and precision extract for deep structure analysis with table and formula recognition. Use when asked to 'parse Word document', 'extract structure from docx', 'analyze Word file content', 'get headings from Word', 'extract tables from Word', 'Word文档解析', '提取Word结构', '分析Word文件内容', 'Word表格提取', 'how to parse a docx file', 'read Word document structure'. Ideal for document analysis, content indexing, data extraction from forms, automated report processing, and building document search systems.

ClawHub Agent Skills author: veeicwgy v0.2.0 MIT-0 2 files body ≈ 236 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationWordInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
C
53/100
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

    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

    • note frontmatter-key unknown 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. 8 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 236 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 783: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    This is a coherent Word-document parsing skill, but users should be mindful that parsed document contents may be written locally and processed through MinerU.
    LLM: benign (high) · VirusTotal: · 29 May 2026