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BC greenhelix-x402-merchant-starter-kit

x402 Merchant Starter Kit: Deploy Your Own Crypto-Native Storefront. Comprehensive x402 paywall + MCP server + product catalog guide. Deploy in 15 minutes. Includes Express.js storefront, SQLite catalog, Gumroad/Polar dual-rail checkout, Schema.org JSON-LD, llms.txt agent discovery, CI/CD pipeline, and nginx config. The same stack powering claw.greenhelix.net.

ClawHub Agent Skills author: mirni v1.3.1 MIT-0 1 file body ≈ 3 457 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

TemplateGitHubInfrastructureAI and agentstype 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
86/100
safety, quality, tests
Safety 60%
98
Quality 40%
68
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration read-dotenv SKILL.md:156
    Reads a .env file
    cp .env.example .env
  • low Secrets in code secret-high-entropy-token SKILL.md:290
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "asset": "0x03…F7e"
    quoted

Files scanned: 1. 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")
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "price_usd"
  • note frontmatter-key unknown frontmatter key "content_type"
  • note frontmatter-key unknown frontmatter key "executable"
  • note frontmatter-key unknown frontmatter key "install"
  • note frontmatter-key unknown frontmatter key "credentials"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 21 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web, python, node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 50 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3457 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 16 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
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +3Description length 362: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 50 items
  • +4Has examples (15 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is a non-executing guide for deploying a crypto storefront; it openly discusses payment, token, and agent-buying features, so users should follow it only with scoped credentials and code review.
LLM: benign (medium) · VirusTotal: · 29 May 2026