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AC invoice-scan

AI-powered invoice OCR, scanning, and data extraction. Use when: (1) user needs OCR or text extraction from invoice images, scanned documents, or PDFs, (2) scanning/reading invoices to extract structured data (JSON, CSV, Excel), (3) validating invoice arithmetic or classifying document types (invoice vs receipt vs other), (4) processing handwritten invoices, stamps, or multi-language documents (Chinese, Russian, European, etc.), (5) user asks to read/parse/extract/OCR an invoice or receipt. Keywords: OCR, invoice scanning, receipt scanning, document OCR, invoice data extraction, invoice parser, invoice reader. Works in two modes: agent-native (uses your own vision — no API key needed, only formatOutput for export) or CLI standalone (needs ANTHROPIC_API_KEY). Env: ANTHROPIC_API_KEY (CLI mode only). Install: npm install --production in scripts/.

ClawHub Agent Skills author: mr-muddle v2.2.0 MIT-0 22 files body ≈ 1 449 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 63/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice

IntegrationFinancetype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 22. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 63/100

    • 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. 6 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 85Steps. 15 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1449 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 855: 120–800 characters recommended
    • -31 of 2 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 15 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This invoice-scanning skill clearly discloses that CLI mode sends invoice images to Anthropic and its behavior matches that purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026