Council Verification Skill
Use LLM Council's multi-model deliberation to verify work with structured, machine-actionable verdicts.
When to Use
- •Verify code changes before committing
- •Validate implementation against requirements
- •Check documents for accuracy and completeness
- •Get multi-model consensus on quality
Workflow
- •Capture Snapshot: Capture current git diff or file state (snapshot pinning for reproducibility)
- •Invoke Verification: Call
mcp:llm-council/verifywith isolated context - •Receive Verdict: Get structured JSON with verdict, confidence, and blocking issues
- •Audit Trail: Persist transcript via
mcp:llm-council/audit
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
rubric_focus | string | null | Focus area: "Security", "Performance", "Accessibility" |
confidence_threshold | float | 0.7 | Minimum confidence for PASS verdict |
snapshot_id | string | required | Git commit SHA for reproducibility |
Output Schema
json
{
"verdict": "pass|fail|unclear",
"confidence": 0.85,
"rubric_scores": {
"accuracy": 8.5,
"completeness": 7.0,
"clarity": 9.0,
"conciseness": 8.0
},
"blocking_issues": [...],
"rationale": "Chairman synthesis...",
"transcript_location": ".council/logs/..."
}
Exit Codes (for CI/CD)
- •
0: PASS - Approved with confidence >= threshold - •
1: FAIL - Rejected - •
2: UNCLEAR - Confidence below threshold, requires human review
Example Usage
bash
# Verify current changes council-verify --snapshot $(git rev-parse HEAD) --rubric-focus Security # Verify specific files council-verify --target-paths "src/auth.py,src/api.py" --snapshot abc123
Progressive Disclosure
- •Level 1: This metadata (~200 tokens)
- •Level 2: Full instructions above (~600 tokens)
- •Level 3: See
references/rubrics.mdfor detailed rubric definitions
Related Skills
- •
council-review: Code review with structured feedback - •
council-gate: CI/CD quality gate