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AC invoice-extractor

Extract structured data from invoices and receipts (PDFs and images). Output JSON, CSV, or build a running expense ledger. Use when someone shares an invoice to process, asks to track expenses, categorize spending, or prepare tax documents.

ClawHub Agent Skills author: 99rebels v1.2.0 MIT-0 8 files body ≈ 2 663 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

GeneratorFinancetype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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: 8. 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 51/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 10 mutating operations with no state check
    • 40Consistency. Frontmatter name (invoice-extractor) differs from the folder (rebels-invoice-extractor)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 45 steps
    • 100Failures and branches. 8 branches, has a failure section
    • 100Execution cost. Instruction body is 2663 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 11 top-level sections: this looks like several domains in one skill

    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
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 240: enough signal without eating the budget
    • +4Structure: 26 headings
    • +3Step-by-step instructions: 45 items
    • +4Has examples (20 code blocks)
    • +4Reference files are cited in the instructions (3 of 4)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a disclosed local invoice and expense-ledger tool, with financial file-writing and deletion features that users should operate deliberately.
    LLM: benign (high) · VirusTotal: · 29 May 2026