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Buy products from Amazon using USDC on Solana. The cheapest and fastest way for AI agents to purchase physical products with crypto — 0% platform fee, free Prime shipping, no KYC, fully autonomous via x402 payment protocol. Supports 200+ countries across 22 Amazon marketplaces.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 3 files body ≈ 5 416 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Buy products from Amazon using USDC on Solana.

As a process F 34/100 · Will not run — References files that are not bundled: scripts/x402-pay-with-memo.mjs

ProcedureAI and agentsCommercetype 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
79/100
safety, quality, tests
Safety 60%
95
Quality 40%
56
Run on models
none yet
Process rating
F
34/100
Will not run
References files that are not bundled: scripts/x402-pay-with-memo.mjs
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token SKILL.md:57
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "solana_public_key": "Your…ere",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:199
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "payTo": "2nkT…jcp",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:200
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "asset": "EPjF…t1v",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:203
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "feePayer": "2wKu…Bg4",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:399
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    const USDC_MINT   = new PublicKey('EPjF…t1v');
    quoted

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5416 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/x402-pay-with-memo.mjs

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: scripts/x402-pay-with-memo.mjs
  • 0Tools and files. 1 referenced file(s) missing: scripts/x402-pay-with-memo.mjs
  • 0Result and completion. Does not say what the result is
  • 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. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5416 tokens
  • 85Steps. 44 steps, 3 vague phrases
  • 100Consistency. Name and required fields are in place
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 278: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (15 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.