AD code-review
Multi-agent deep review for code PRs in any repo. Use when asked to "deep review this PR," "multi-agent review," "review
Multi-agent deep review for code PRs in any repo.
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerGitHubSoftware developmentAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
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: 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 46/100
- 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
- 40Consistency. Frontmatter name (code-review) differs from the folder (cot-code-review)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (read) that frontmatter does not declare
- 100Steps. 21 steps
- 100Execution cost. Instruction body is 1361 tokens
- 100Running it twice. Mutating operations check current state
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
- +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
- +5Description quotes 2 example trigger phrases
- +3Description length 120: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.
External checks
ClawHub: clean
This skill is a disclosed multi-agent code review workflow with proportionate repo and GitHub actions for its stated purpose.
LLM: benign (high) · VirusTotal: · 22 Aug 2026