AB skill-factory
Design, build, evaluate, and optimize production-ready Agent Skills for ClawHub. Use when creating a new skill, redesigning an existing skill, choosing between a single skill, references/scripts, or a router with variants, improving skill triggers, validating portability, or preparing a skill for publication. Also use when turning a rough skill idea into a self-contained, publishable skill package.
As a process B 79/100 · Nearly there — weak spots: running it twice, progress reporting
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Risky intent
intent-offensive-securityreferences/skill-mechanics.md:114Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- privilege escalation;
-
low Risky intent
intent-offensive-securitySKILL.md:204Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- credential harvesting;
Files scanned: 4. 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 79/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 10 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 124 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2235 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 401: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 124 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.