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BD iauotpay-api

Purchase API keys from iAutoPay Fact API using USDC on Base chain. Use this skill when: - Buying API keys for AI agent payment services - Managing API key subscriptions (1/7/30 days) - Checking user account information and usage statistics - Checking server information and pricing - Integrating crypto payments for API access

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 6 607 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Purchase API keys from iAutoPay Fact API using USDC on Base chain.

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmenttype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
74
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token SKILL.md:22
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **Asset**: `0x03…F7e` (USDC)
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:52
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "asset": "0x03…F7e",
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:211
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    -d '{"to": "0x12…678", "amount": "10000", "asset": "0x03…F7e"}'
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:219
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "asset": "0x03…F7e"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:447
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    **USDC Contract**: `0x03…F7e` (Base Sepolia)
    quoted

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6607 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 42/100

  • 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. 10 mutating operations with no state check
  • 40Consistency. Frontmatter name (iauotpay-api) differs from the folder (iautopay)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6607 tokens
  • 100Steps. 45 steps
  • 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 326: enough signal without eating the budget
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 45 items
  • +4Has examples (40 code blocks)

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