Agent Skills: Council Review Skill

Domain knowledge for multi-agent council review protocols, orchestration patterns, scoring systems, and deliberation frameworks

UncategorizedID: lobbi-docs/claude/council-review

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plugins/claude-code-expert/skills/council-review/SKILL.md

Skill Metadata

Name
council-review
Description
Domain knowledge for multi-agent council review protocols, orchestration patterns, scoring systems, and deliberation frameworks

Council Review Skill

Domain knowledge for orchestrating multi-agent review councils with structured deliberation protocols.

Use For

  • Running /cc-council reviews with appropriate protocol selection
  • Configuring council members, weights, and voting thresholds
  • Understanding when to use each deliberation protocol
  • Interpreting council scores and making go/no-go decisions
  • Setting up auto-fix pipelines with confidence thresholds
  • Integrating council reviews into CI/CD pipelines

Protocol Selection Guide

Decision Tree

What are you reviewing?
├── Security-sensitive code (auth, payments, secrets)
│   └── Use: red-blue-team --preset security
├── Architecture or design decision
│   └── Use: six-thinking-hats --preset architecture
├── Small PR (<100 lines)
│   └── Use: rapid-fire --preset quick
├── Large PR (>500 lines, multi-file)
│   └── Use: blackboard --preset full
├── Contentious change (team disagreement)
│   └── Use: delphi --preset standard
└── Regular code change
    └── Use: expert-panel --preset standard

Protocol Comparison

| Protocol | Rounds | Agent Interaction | Token Cost | Quality | Speed | |----------|--------|-------------------|------------|---------|-------| | rapid-fire | 1 | None | Low | Good | Fast | | expert-panel | 1-2 | After analysis | Medium | High | Medium | | blackboard | Async | Shared space | Medium | High | Medium | | red-blue-team | 2 | Adversarial | High | Very High | Slow | | six-thinking-hats | 6 views | Structured | High | Very High | Slow | | delphi | 2-3 | Anonymous | Highest | Highest | Slowest |

Orchestration Best Practices

Fan-Out / Fan-In

  • Always spawn all agents in a single message for true parallelism
  • Each agent gets scoped context — only the files/info they need
  • Use run_in_background: false so results come back synchronously
  • Handle partial failures: if 3/4 agents respond, proceed with 3

Context Scoping

Giving each agent the minimum viable context:

  • Reduces token cost by 40-60%
  • Improves finding quality (less noise to filter)
  • Prevents agents from commenting outside their specialty

Weight Calibration

Default weights reflect review importance:

code-reviewer:         1.0  (always relevant)
security-reviewer:     0.9  (high impact, veto power)
architecture-reviewer: 0.9  (structural decisions matter)
test-strategist:       0.8  (coverage critical for confidence)
performance-analyst:   0.7  (important but often subjective)
accessibility-reviewer: 0.6 (important for frontend)
api-reviewer:          0.6  (important for API changes)
dependency-auditor:    0.6  (important for supply chain)
docs-reviewer:         0.5  (lower weight, rarely blocks)

Veto Power

  • Only security-reviewer and secrets-scanner have default veto
  • Veto triggers on: critical finding + confidence >= 0.8
  • Veto overrides weighted voting — always results in changes-requested
  • Rationale: security issues must never be approved by majority vote

Consensus Detection

When 2+ agents flag the same file+line range:

  • Boost confidence by 1.2x
  • Mark as "consensus" in report (stronger signal)
  • These findings are almost always valid

Conflict Resolution

When agents disagree on severity:

  • Lead agent (if designated) has tie-breaking authority
  • Otherwise: higher-weight agent's assessment wins
  • Always report the conflict with both perspectives

Scoring System

Scope Independence

Each scope (security, quality, performance, etc.) is scored independently on a 0-100 scale. This prevents a strong quality score from masking a weak security score.

Deduction Tables

Findings map to deductions via category lookup tables. The deduction is multiplied by the finding's confidence score, so low-confidence findings have proportionally less impact.

Scoring Modes

Weighted (default): Scope scores are combined using configurable weights. Good for overall quality assessment where trade-offs are acceptable.

Pass-fail: Each scope must independently meet its threshold. Good for compliance and gating — no scope can compensate for another.

Highest-concern: Overall score equals the weakest scope. Most conservative mode — forces attention to the weakest area.

Auto-Fix Guidelines

When to Auto-Fix

  • Formatting and style issues (confidence typically 0.95+)
  • Import organization (high confidence, mechanical)
  • Type annotations (when TypeScript can infer)
  • Simple null checks (optional chaining additions)

When NOT to Auto-Fix

  • Business logic changes (too context-dependent)
  • Architecture refactoring (requires human judgment)
  • Test modifications (risk of masking real failures)
  • Migration files (must be append-only)
  • Generated files (will be overwritten)

Safety Checks

After auto-fix:

  1. Run --fix-dry-run first to preview changes
  2. Auto-fix respects skip_patterns in config
  3. Post-fix validation: lint + typecheck
  4. If validation fails: revert the fix, report as "fix-failed"

CI/CD Integration

Pre-Merge Gate

# In CI pipeline:
/cc-council . --preset pre-merge --format json --changed-only > council-result.json
# Check exit code: 0=approved, 1=changes-requested, 2=error

Quality Gate Thresholds

Recommended thresholds by environment:

Development:  --threshold 0.5  (permissive, speed over safety)
Staging:      --threshold 0.7  (balanced)
Production:   --threshold 0.85 (strict)
Compliance:   --threshold 0.9 --scoring pass-fail (audit-grade)

State Machine & Resume

The council saves state at each phase boundary. If a phase fails (e.g., network timeout during fan-out), you can resume from the last checkpoint:

/cc-council --resume <session-id>

State includes:

  • Council plan (members, protocol, scopes)
  • Raw agent outputs (findings + votes)
  • Deliberation results (consensus, conflicts)
  • Score calculations

This means you never lose work from a partially completed council.