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BC customs-trade-compliance

Codified customs and trade compliance expertise — HS/HTS tariff classification with GRI rules, commercial invoices and entry documentation, Incoterms 2020, FTA qualification and duty optimization (USMCA, RCEP, FTZs, drawback), denied-party screening, and penalty mitigation across US, EU, UK, and APAC jurisdictions. Use when classifying goods, preparing import/export documentation, screening restricted parties, responding to customs audits or CF-28/penalty notices, or optimizing duties.

affaan-m/everything-claude-code Agent Skills author: affaan-m MIT 1 file body ≈ 7 063 tokens Open the sourcegithub.com↗ analyzed 25 h ago

Codified customs and trade compliance expertise — HS/HTS tariff classification with GRI rules, commercial invoices and entry documentation, Incoterms 2020…

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerSecurityWriting and documentsFinancetype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
61/100
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

The same skill appears in 1 more place: ECC

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 7063 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 61/100

  • 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
  • 70Execution cost. Instruction body is 7063 tokens
  • 85Steps. 73 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 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
  • +2Single-language instructions
  • +3Description length 490: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 73 items
  • +4Has examples (0 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.