AB five-star-reviewers
orchestrate a five-reviewer code review over a git diff, pull request diff, patch, or commit range by launching one dedicated sub-agent per reviewer role, then produce one consolidated report for a follow-up ai coding pass. use when reviewing a code repository, comparing working tree changes, checking a pr, or evaluating changes between two git revisions. optimized for pragmatic, language-agnostic review that prioritizes correctness, architecture, testability, readability, and simplicity while actively discouraging code bloat, unnecessary abstraction, and maintenance-heavy designs.
As a process B 72/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, 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 · 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 72/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 5 branches
- 100Tools and files. No external tools needed
- 100Steps. 74 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1989 tokens
- 100Running it twice. Mutating operations check current state
- low 14 top-level sections: this looks like several domains in one skill
- low The skill ranks results itself: that belongs to the system behind the tool, not the model
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 588: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 74 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
- +4Reference files are cited in the instructions (3 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.