AC x402-agent-tools
Use this skill when the agent needs LLM inference without an API key, persistent memory that survives across sessions, uptime monitoring, exact math, web scraping, SEO audits, code lint, or live crypto prices — and wants to pay per call from its own wallet instead of holding accounts or subscriptions. Trigger on "x402", "pay per call", "agent memory", "remember this across sessions", "scratchpad", "no API key", "monitor this URL", "is this site up", "what is this site built with", "USDC on Base", or any paid-API request where the agent has a funded wallet. 62 endpoints, $0.001–$0.05 per call, USDC on Base via the x402 protocol. The paying wallet IS the identity — no signup, no keys.
Use this skill when the agent needs LLM inference without an API key, persistent memory that survives across sessions, uptime monitoring, exact math, web…
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 58/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 22 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1233 tokens
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +3Description length 691: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 22 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.