AC openclaw-regex-engine
Production-grade regex processing suite — test patterns with capture groups, explain any regex in plain English, build regex from natural language descriptions, browse 50+ battle-tested patterns, and find-replace with backreferences. Use when: (1) user says 'test this regex' or 'does this pattern match', (2) user asks 'explain this regex' or 'what does this regex do', (3) user needs to 'build a regex for emails' or 'create a pattern that matches URLs', (4) user wants a 'ready-made regex for phone numbers' or 'UUID pattern', (5) user requests 'regex find and replace' or 'search and replace with backreferences'. Supports all ES2024 flags, named groups, lookahead/lookbehind. Zero install, sub-100ms on Cloudflare Workers. Free + Pro $9/mo.
As a process C 53/100 · 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 53/100
- 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
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2439 tokens
- 100Running it twice. Mutating operations check current state
- 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 745: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.