dual-verification

What this skill does

# 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 | User Action |
|-------|--------|--------|-------------|
| **Phase 1** | Dispatch 2 agents in parallel | Two independent reports | Wait |
| **Phase 2** | Collate findings, present to user | Collated report | Can `/revise common` |
| **Phase 3** | Cross-check exclusive issues (background) | Validated exclusive issues | Can `/revise exclusive` or `/revise all` |

**Confidence levels:**
- **VERY HIGH:** Both agents found (high confidence - act on this)
- **MODERATE:** One agent found (unique insight - needs cross-check)
- **INVESTIGATE:** Agents disagree (resolved during collation)

**Exclusive issue states (after cross-check):**
- **VALIDATED:** Cross-check confirmed issue exists → implement
- **INVALIDATED:** Cross-check found issue doesn't apply → skip
- **UNCERTAIN:** Cross-check couldn't determine → user decides

## Why This Pattern Works

**Higher quality through independence:**
- Common findings = high confidence (both found)
- Exclusive findings = unique insights one agent caught → validated by cross-check
- Divergences = resolved during collation

**Context management:**
- Two detailed reviews = lots of context
- Collation agent does comparison work
- Cross-check runs in background while user reviews
- Main context gets clean summary

**Confidence progression:**
- Both found → VERY HIGH → Fix immediately (`/revise common`)
- One found → MODERATE → Cross-check validates → VALIDATED/INVALIDATED/UNCERTAIN
- Disagree → INVESTIGATE → Resolved during collation

**Parallel workflow:**
- User gets collation results immediately
- Can start `/revise common` while cross-check runs
- Cross-check completes → `/revise exclusive` or `/revise all`

## 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 and Present

**Dispatch collation agent to compare the two reviews, then present to user immediately.**

**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 (pending cross-check)

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

6. **IF divergences exist → Verify with appropriate agent:**
   - Dispatch verification 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 - pending cross-check)
   - 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
```

**Present collated report to user immediately:**

```
Collation complete. Report saved to: [path]

**Summary:**
- Common issues: X (VERY HIGH