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AC smart-pdf-reader

Intelligent PDF reader and content extractor powered by MinerU API. Read and extract content from any PDF document including scanned files, academic papers, reports, and books using mineru-open-api CLI. Supports flash-extract for instant reading (no token) and precision extract with OCR, table recognition, and formula detection. Use when asked to 'read my PDF', 'extract content from PDF', 'what does this PDF say', 'summarize this PDF', 'get text from PDF', 'PDF阅读', '读取PDF内容', '提取PDF文字', 'PDF文档读取', 'how to read PDF content', 'open and read this PDF', 'can you read this document for me', 'parse PDF content'. Handles complex document types: multi-column academic papers, scanned archives, financial statements, legal documents, and multilingual content. Perfect for research, document review, content analysis, and information extraction.

ClawHub Agent Skills author: veeicwgy v0.2.0 MIT-0 2 files body ≈ 262 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

IntegrationPDFResearchInfrastructureWriting and documentstype 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
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. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 262 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 843: 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.

    External checks

    ClawHub: clean
    This skill is a straightforward PDF extraction helper, but users should be aware it relies on a third-party CLI/API and may save extracted document content locally.
    LLM: benign (high) · VirusTotal: · 29 May 2026