AF review-skill-improver
Analyzes feedback logs to identify patterns and suggest improvements to review skills. Use when you have accumulated feedback data and want to improve review accuracy.
Analyzes feedback logs to identify patterns and suggest improvements to review skills.
As a process F 48/100 · Will not run — References files that are not bundled: ../review-feedback-schema/SKILL.md
AnalyzerData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
How to improve
- The text references files that are not there: add them or drop the references.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: ../review-feedback-schema/SKILL.md
Process rating: all ten parameters 48/100
Will not run. References files that are not bundled: ../review-feedback-schema/SKILL.md
- 0Tools and files. 1 referenced file(s) missing: ../review-feedback-schema/SKILL.md
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 17 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1581 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)
- +1No license
- +2Single-language instructions
- +3Description length 167: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 17 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.
External checks
ClawHub: clean
This skill is a markdown-only review aid that analyzes feedback logs and suggests evidence-based improvements without hidden execution, persistence, or credential use.
LLM: benign (high) · VirusTotal: · 3 Jun 2026