SKILLEMALL.ai
GitHub ↗ RU Sign in

BD expense_invoice_ocr

支持识别企业财务报销场景的19 种常见票据，包括：增值税发票,增值税卷票,出租车发票,火车票,航空运输电子客票行程单,机动车销售统一发票,定额发票,过路过桥费发票,医疗发票,税收完税证明,船票,非税票据,通用机打发票,汽车票,值税通行费发票,网约车行程单,银联POS签购单,医疗住院发票,医疗费用结算单识别。仅在用户明确要求识别某张本地票据图片时触发，调用前必须确认用户同意上传该文件到 Scnet 远程 OCR 服务。

ClawHub Agent Skills author: SCNet-sugon v1.0.8 MIT-0 9 files body ≈ 905 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
D
41/100
Unfinished process
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "required_env_vars"
  • note frontmatter-key unknown frontmatter key "optional_env_vars"
  • note frontmatter-key unknown frontmatter key "primary_credential"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note frontmatter-key unknown frontmatter key "input"
  • note frontmatter-key unknown frontmatter key "output"

Process rating: all ten parameters 41/100

  • 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
  • 40Consistency. Frontmatter name (expense_invoice_ocr) differs from the folder (expense-invoice-ocr)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Execution cost. Instruction body is 905 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +2Single-language instructions
  • +3Description length 210: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (3 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: clean
This OCR skill is clearly designed to upload a user-chosen invoice or receipt file to Scnet for recognition, and that sensitive data flow is disclosed with consent instructions.
LLM: benign (high) · VirusTotal: · 11 Aug 2026