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AF laiye-doc-processing

Enterprise-grade agentic document processing API. Accurately extracts key fields and line items from invoices, receipts, orders and more across 10+ file formats, with confidence scoring. Zero-configuration, fast integration. Professionally optimized on massive enterprise documents.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 2 528 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Enterprise-grade agentic document processing API.

As a process F 52/100 · Will not run — References files that are not bundled: ../../refers/backend/flows/ADP-Flow-Index.md, ../../refers/backend/flows/09-Doc-Extraction-Flow.md, ../../refers/backend/flows/08-Doc-Recognition-Flow.md

IntegrationAI and agentsFinancetype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
52/100
Will not run
References files that are not bundled: ../../refers/backend/flows/ADP-Flow-Index.md, ../../refers/backend/flows/09-Doc-Extraction-Flow.md, ../../refers/backend/flows/08-Doc-Recognition-Flow.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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

  • warning missing-ref reference to a missing file: ../../refers/backend/flows/ADP-Flow-Index.md
  • warning missing-ref reference to a missing file: ../../refers/backend/flows/09-Doc-Extraction-Flow.md
  • warning missing-ref reference to a missing file: ../../refers/backend/flows/08-Doc-Recognition-Flow.md
  • note frontmatter-key unknown frontmatter key "License"

Process rating: all ten parameters 52/100

Will not run. References files that are not bundled: ../../refers/backend/flows/ADP-Flow-Index.md, ../../refers/backend/flows/09-Doc-Extraction-Flow.md, ../../refers/backend/flows/08-Doc-Recognition-Flow.md
  • 0Tools and files. 3 referenced file(s) missing: ../../refers/backend/flows/ADP-Flow-Index.md, ../../refers/backend/flows/09-Doc-Extraction-Flow.md, ../../refers/backend/flows/08-Doc-Recognition-Flow.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 7 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 61 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2528 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 13 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
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 282: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 61 items
  • +3Output format is stated explicitly
  • +4Has examples (15 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.