AD pzero
Point OpenClaw at PZERO prepaid inference. OpenAI-compatible chat completions, Bearer pzero_ key, custom provider (not a bundled OpenClaw plugin). Use when the user wants cheaper privacy-first models on a prepaid USDC balance.
Point OpenClaw at PZERO prepaid inference.
As a process D 44/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Exfiltration
net-credential-useSKILL.md:99Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded)Same credits, hosted connector: `https://mcp.pzero.studio/mcp` with `Authorization: Bearer $PZERO_API_KEY`. Human docs: https://docs.pzero.studio/agents/mcp
vendor-hostquoted
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 44/100
- 0Steps. Prose only: no discrete steps
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 692 tokens
- 100Running it twice. No mutating operations
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 226: enough signal without eating the budget
- +4Structure: 5 headings
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.