AB request-approval
Use Preloop's request_approval tool to get human approval before risky operations like deletions, production changes, or external modifications
As a process B 71/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
For the model run — optional
- 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: 6. 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 71/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 11 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 62 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1197 tokens
- 100Progress reporting. Reports progress
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
- -216 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 143: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 62 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.
External checks
ClawHub: suspicious
The skill is mostly a coherent approval-gating guide, but its setup docs include a risky unpinned MCP server command and some guidance that weakens approval requirements outside production.
LLM: suspicious (high) · VirusTotal: benign · 10 Sept 2026