AC openclaw-json-toolkit
Enterprise-grade JSON processing suite — format, validate, deep-diff, JSONPath query, structural transform, and schema generation in one MCP server. Use when: (1) user says 'format this JSON' or 'pretty print this', (2) user asks 'validate my JSON' or 'is this valid JSON', (3) user needs to 'compare two JSON objects' or 'diff these configs', (4) user wants to 'query nested JSON' or 'extract with JSONPath', (5) user requests 'flatten JSON' or 'generate JSON Schema'. Supports draft-07 schema, recursive flatten, wildcard queries, filter expressions, array slicing. Zero install, sub-100ms on Cloudflare Workers. Free + Pro $9/mo.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, 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 · 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 "read_when" - note
frontmatter-keyunknown frontmatter key "commands"
Process rating: all ten parameters 56/100
- 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. 11 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 16 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2256 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +1No license
- +2Single-language instructions
- +3Description length 632: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 16 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.