---
name: dual-verification
description: Use two independent agents for reviews or research, then collate findings to identify common findings, unique insights, and divergences
when_to_use: comprehensive audits, plan reviews, code reviews, research tasks, codebase exploration, verifying content matches implementation, quality assurance for critical content
version: 1.0.0
---

# Dual Verification Review

## Overview

Use two independent agents to systematically review content or research a topic, then use a collation agent to compare findings.

**Core principle:** Independent dual perspective + systematic collation = higher quality, managed context.

**Announce at start:** "I'm using the dual-verification skill for comprehensive [review/research]."

## When to Use

Use dual-verification when:

**For Reviews:**
- **High-stakes decisions:** Before executing implementation plans, merging to production, or deploying
- **Comprehensive audits:** Documentation accuracy, plan quality, code correctness
- **Quality assurance:** Critical content that must be verified against ground truth
- **Risk mitigation:** When cost of missing issues exceeds cost of dual review

**For Research:**
- **Codebase exploration:** Understanding unfamiliar code from multiple angles
- **Problem investigation:** Exploring a bug or issue with different hypotheses
- **Information gathering:** Researching a topic where completeness matters
- **Architecture analysis:** Understanding system design from different perspectives
- **Building confidence:** When you need high-confidence understanding before proceeding

**Don't use when:**
- Simple, low-stakes changes (typo fixes, minor documentation tweaks)
- Time-critical situations (production incidents requiring immediate action)
- Single perspective is sufficient (trivial updates, following up on previous review)
- Cost outweighs benefit (quick questions with obvious answers)

## Quick Reference

| Phase | Action | Output |
|-------|--------|--------|
| **Phase 1** | Dispatch 2 agents in parallel with identical prompts | Two independent reports |
| **Phase 2** | Dispatch collation agent to compare findings | Collated report with confidence levels |
| **Phase 3** | Present findings to user | Common (high confidence), Exclusive (consider), Divergences (investigate) |

**Confidence levels:**
- **VERY HIGH:** Both agents found (high confidence - act on this)
- **MODERATE:** One agent found (unique insight - consider carefully)
- **INVESTIGATE:** Agents disagree (needs resolution)

## Why This Pattern Works

**Higher quality through independence:**
- Common findings = high confidence (both found)
- Exclusive findings = unique insights one agent caught
- Divergences = areas needing investigation

**Context management:**
- Two detailed reviews = lots of context
- Collation agent does comparison work
- Main context gets clean summary

**Confidence levels:**
- Both found → Very likely real issue → Fix immediately
- One found → Edge case or judgment call → Decide case-by-case
- Disagree → Requires investigation → User makes call

## The Three-Phase Process

### Phase 1: Dual Independent Review

**Dispatch 2 agents in parallel with identical prompts.**

**Agent prompt template:**
```
You are [agent type] conducting an independent verification review.

**Context:** You are one of two agents performing parallel independent reviews. Another agent is reviewing the same content independently. A collation agent will later compare both reviews.

**Your task:** Systematically verify [subject] against [ground truth].

**Critical instructions:**
- Current content CANNOT be assumed correct. Verify every claim.
- You MUST follow the review report template structure
- Template location: ${CLAUDE_PLUGIN_ROOT}templates/verify-template.md
- You MUST save your review with timestamp: `.work/{YYYY-MM-DD}-verify-{type}-{HHmmss}.md`
- Time-based naming prevents conflicts when agents run in parallel.
- Work completely independently - the collation agent will find and compare all reviews.

**Process:**

1. Read the review report template to understand the expected structure
2. Read [subject] completely
3. For each [section/component/claim]:
   - Identify what is claimed
   - Verify against [ground truth]
   - Check for [specific criteria]

4. Categorize issues by:
   - Category ([issue type 1], [issue type 2], etc.)
   - Location (file/section/line)
   - Severity ([severity levels])

5. For each issue, provide:
   - Current content (what [subject] says)
   - Actual [ground truth] (what is true)
   - Impact (why this matters)
   - Action (specific recommendation)

6. Save using template structure with all required sections

**The template provides:**
- Complete structure for metadata, issues, summary, assessment
- Examples of well-written reviews
- Guidance on severity levels and categorization
```

**Example: Documentation Review**
- Agent type: technical-writer
- Subject: README.md and CLAUDE.md
- Ground truth: current codebase implementation
- Criteria: file paths exist, commands work, examples accurate

**Example: Plan Review**
- Agent type: plan-review-agent
- Subject: implementation plan
- Ground truth: 35 quality criteria (security, testing, architecture, etc.)
- Criteria: blocking issues, non-blocking improvements

**Example: Code Review**
- Agent type: code-review-agent
- Subject: implementation code
- Ground truth: coding standards, plan requirements
- Criteria: meets requirements, follows standards, has tests

### Phase 2: Collate Findings

**Dispatch collation agent to compare the two reviews.**

**Dispatch collation agent:**
```
Use Task tool with:
  subagent_type: "cipherpowers:review-collation-agent"
  description: "Collate dual [review type] reviews"
  prompt: "You are collating two independent [review type] reviews.

**Critical instructions:**
- You MUST follow the collation report template structure
- Template location: ${CLAUDE_PLUGIN_ROOT}templates/verify-collation-template.md
- Read the template BEFORE starting collation
- Save to: `.work/{YYYY-MM-DD}-verify-{type}-collated-{HHmmss}.md`

**Inputs:**
- Review #1: [path to first review file]
- Review #2: [path to second review file]

**Your task:**

1. **Read the collation template** to understand the required structure

2. **Parse both reviews completely:**
   - Extract all issues from Review #1
   - Extract all issues from Review #2
   - Create internal comparison matrix

3. **Identify common issues** (both found):
   - Same issue found by both reviewers
   - Confidence: VERY HIGH

4. **Identify exclusive issues** (only one found):
   - Issues found only by Agent #1
   - Issues found only by Agent #2
   - Confidence: MODERATE (may be edge cases)

5. **Identify divergences** (agents disagree):
   - Same location, different conclusions
   - Contradictory findings

6. **IF divergences exist → Verify with plan-review agent:**
   - Dispatch cipherpowers:plan-review-agent for each divergence
   - Provide both perspectives and specific divergence point
   - Incorporate verification analysis into report

7. **Follow template structure for output:**
   - Metadata section (complete all fields)
   - Executive summary (totals and breakdown)
   - Common issues (VERY HIGH confidence)
   - Exclusive issues (MODERATE confidence)
   - Divergences (with verification analysis)
   - Recommendations (categorized by action type)
   - Overall assessment

**The template provides:**
- Complete structure with all required sections
- Examples of well-written collation reports
- Guidance on confidence levels and categorization
- Usage notes for proper assessment
```

### Phase 3: Present Findings to User

**Present collated report with clear action items:**

1. **Common issues** (both found):
   - These should be addressed immediately
   - Very high confidence they're real problems

2. **Exclusive issues** (one found):
   - User decides case-by-case
   - Review agent's reasoning
   - May be edge cases or may be missed by other agent

3. **Divergences** (agents disagree):
   - User investigates and makes final call
   - May need additional verification
   - May indicate ambiguity in requirements/standards

## Parameterization

Make the pattern flexible by specifying:

**Subject:** What to review
- Documentation files (README.md, CLAUDE.md)
- Implementation plans (plan.md)
- Code changes (git diff, specific files)
- Test coverage (test files)
- Architecture decisions (design docs)

**Ground truth:** What to verify against
- Current implementation (codebase)
- Quality criteria (35-point checklist)
- Coding standards (practices)
- Requirements (specifications)
- Design documents (architecture)

**Agent type:** Which specialized agent to use
- technical-writer (documentation)
- plan-review-agent (plans)
- code-review-agent (code)
- rust-agent (Rust-specific)
- ultrathink-debugger (complex issues)

**Granularity:** How to break down review
- Section-by-section (documentation)
- Criteria-by-criteria (plan review)
- File-by-file (code review)
- Feature-by-feature (architecture review)

**Severity levels:** How to categorize issues
- critical/high/medium/low (general)
- BLOCKING/NON-BLOCKING (plan/code review)
- security/performance/maintainability (code review)

## When NOT to Use

**Skip dual verification when:**
- Simple, low-stakes changes (typo fixes)
- Time-critical situations (production incidents)
- Single perspective sufficient (trivial updates)
- Cost outweighs benefit (minor documentation tweaks)

**Use single agent when:**
- Regular incremental updates
- Following up on dual review findings
- Implementing approved changes

## Example Usage: Plan Review

```
User: Review this implementation plan before execution

You: I'm using the dual-verification skill for comprehensive review.

Phase 1: Dual Independent Review
  → Dispatch 2 plan-review-agent agents in parallel
  → Each applies 35 quality criteria independently
  → Agent #1 finds: 3 BLOCKING issues, 7 NON-BLOCKING
  → Agent #2 finds: 4 BLOCKING issues, 5 NON-BLOCKING

Phase 2: Collate Findings
  → Dispatch review-collation-agent
  → Collator compares both reviews
  → Produces collated report

Collated Report:
  Common Issues (High Confidence):
    - 2 BLOCKING issues both found
    - 3 NON-BLOCKING issues both found

  Exclusive Issues:
    - Agent #1 only: 1 BLOCKING, 4 NON-BLOCKING
    - Agent #2 only: 2 BLOCKING, 2 NON-BLOCKING

  Divergences: None

Phase 3: Present to User
  → Show common BLOCKING issues (fix immediately)
  → Show exclusive BLOCKING issues (user decides)
  → Show all NON-BLOCKING for consideration
```

## Example Usage: Documentation Review

```
User: Audit README.md and CLAUDE.md for accuracy

You: I'm using the dual-verification skill for comprehensive documentation audit.

Phase 1: Dual Independent Review
  → Dispatch 2 technical-writer agents in parallel
  → Each verifies docs against codebase
  → Agent #1 finds: 13 issues (1 critical, 3 high, 6 medium, 3 low)
  → Agent #2 finds: 13 issues (4 critical, 1 high, 4 medium, 4 low)

Phase 2: Collate Findings
  → Dispatch review-collation-agent
  → Identifies: 7 common, 6 exclusive, 0 divergences

Collated Report:
  Common Issues (High Confidence): 7
    - Missing mise commands (CRITICAL)
    - Incorrect skill path (MEDIUM)
    - Missing /verify command (HIGH)

  Exclusive Issues: 6
    - Agent #1 only: 3 issues
    - Agent #2 only: 3 issues

Phase 3: Present to User
  → Fix common issues immediately (high confidence)
  → User decides on exclusive issues case-by-case
```

## Example Usage: Codebase Research

```
User: How does the authentication system work in this codebase?

You: I'm using the dual-verification skill for comprehensive research.

Phase 1: Dual Independent Research
  → Dispatch 2 Explore agents in parallel
  → Each investigates auth system independently
  → Agent #1 finds: JWT middleware, session handling, role-based access
  → Agent #2 finds: OAuth integration, token refresh, permission checks

Phase 2: Collate Findings
  → Dispatch review-collation-agent
  → Identifies: 4 common findings, 3 unique insights, 1 divergence

Collated Report:
  Common Findings (High Confidence): 4
    - JWT tokens used for API auth (both found)
    - Middleware in src/auth/middleware.ts (both found)
    - Role enum defines permissions (both found)
    - Refresh tokens stored in Redis (both found)

  Unique Insights: 3
    - Agent #1: Found legacy session fallback for admin routes
    - Agent #2: Found OAuth config for SSO integration
    - Agent #2: Found rate limiting on auth endpoints

  Divergence: 1
    - Token expiry: Agent #1 says 1 hour, Agent #2 says 24 hours
    - → Verification: Config has 1h access + 24h refresh (both partially correct)

Phase 3: Present to User
  → Common findings = confident understanding
  → Unique insights = additional context worth knowing
  → Resolved divergence = clarified token strategy
```

## Related Skills

**When to use this skill:**
- Comprehensive reviews before major actions
- High-stakes decisions (execution, deployment, merge)
- Quality assurance for critical content

**Other review skills:**
- verifying-plans: Single plan-review-agent (faster, less thorough)
- conducting-code-review: Single code-review-agent (regular reviews)
- maintaining-docs-after-changes: Single technical-writer (incremental updates)

**Use dual-verification when stakes are high, use single-agent skills for regular work.**

## Common Mistakes

**Mistake:** "The reviews mostly agree, I'll skip detailed collation"
- **Why wrong:** Exclusive issues and subtle divergences matter
- **Fix:** Always use collation agent for systematic comparison

**Mistake:** "This exclusive issue is probably wrong since other reviewer didn't find it"
- **Why wrong:** May be valid edge case one reviewer caught
- **Fix:** Present with MODERATE confidence for user judgment, don't dismiss

**Mistake:** "I'll combine both reviews myself instead of using collation agent"
- **Why wrong:** Context overload, missing patterns, inconsistent categorization
- **Fix:** Always dispatch collation agent to handle comparison work

**Mistake:** "Two agents is overkill, I'll just run one detailed review"
- **Why wrong:** Missing the independence that catches different perspectives
- **Fix:** Use dual verification for high-stakes, single review for regular work

**Mistake:** "The divergence is minor, I'll pick one perspective"
- **Why wrong:** User needs to see both perspectives and make informed decision
- **Fix:** Mark as INVESTIGATE and let user decide

## Remember

- Dispatch 2 agents in parallel for Phase 1 (efficiency)
- Use identical prompts for both agents (fairness)
- Dispatch collation agent for Phase 2 (context management)
- Present clean summary to user in Phase 3 (usability)
- Common issues = high confidence (both found)
- Exclusive issues = requires judgment (one found)
- Divergences = investigate (agents disagree)
- Cost-benefit: Use for high-stakes, skip for trivial changes