Expert Validator
Validate your research strategy with 3 independent expert agents. Uses Task Agents for multi-perspective evaluation. Enriches strategy-brief.md with consensus, divergence, and confidence ratings.
Purpose
Expert Validator answers the question "Is this strategy REALLY good, or just looking good?"
A single AI perspective creates blind spots. This skill spins up 3 specialized Task Agents — each with a fresh context window, independent evaluation, and distinct expertise — then synthesizes where they agree and disagree.
-
Where 3 experts agree → Strong signal. Act on it.
-
Where experts diverge → Decision point. You choose.
-
What everyone missed → Blind spot found. Investigate.
The output enriches research-memory/strategy-brief.md with [expert-validator] tagged sections for Expert Consensus, Expert Divergence, and Confidence Overview.
"Consensus = signal in noise." — The Boring Marketer (Expert Review Framework)
Prerequisite
research-synthesizer must have run first. This skill reads strategy-brief.md for the synthesized strategy to validate. If the file doesn't exist or has no content beyond the scaffold, stop and instruct the user to run research-synthesizer first.
Additional research-memory files (market-landscape, competitive-intel, customer-insight, customer-language) are loaded as supporting context for the expert agents.
Modes
Mode When to Use Behavior
Full Validation First run, or strategy-brief.md has no [expert-validator] sections All 3 agents evaluate the entire strategy
Focused Validation User has a specific question or decision point All 3 agents focus on one question
Re-Validation [expert-validator] sections exist but research-memory was updated Re-run agents and update Expert sections
Auto-Load Protocol
On every invocation, BEFORE any evaluation:
-
Check research-memory/ directory
-
If files exist → Read ALL .md files (except README.md)
-
Critical: Read strategy-brief.md
-
If file missing → STOP. Tell user: "Run research-synthesizer first to generate the strategy brief."
-
If file exists but has no substantive content → STOP. Same instruction.
-
Check brand-memory/ (read-only) → If exists, include business description and positioning context in agent briefings
-
If [expert-validator] sections already exist in strategy-brief.md → suggest Re-Validation mode
-
Summarize what's loaded and confirm mode with user
Input Gathering
Collect conversationally. Most inputs come from research-memory — just confirm with the user.
Field Required Description
Validation mode YES Full / Focused / Re-Validation
Focus question Focused mode only The specific question or decision to validate
Business context Optional Current stage, resource constraints, timeline — sharpens agent evaluations
Language Optional 결과물 작성 언어 (default: English)
If this is Full Validation, confirm: "I'll have 3 expert agents review your entire strategy brief. Proceed?"
If this is Focused, ask: "What specific question or decision do you want the experts to evaluate?"
If this is Re-Validation, show the current Expert sections and ask: "Research was updated. Should I re-run all 3 experts?"
Process
Step 1: Prepare Agent Briefing Packet
Goal: Compress all research-memory context into a focused briefing that each agent receives.
Build the briefing packet from loaded files:
Briefing Packet
Business Overview
[From brand-memory/ or user input — what the business does, stage, constraints]
Market Context (from market-landscape.md)
- Market category: [definition]
- Market size: TAM [X], SAM [X]
- Key trends: [top 3 with opportunity/threat tags]
Competitive Context (from competitive-intel.md)
- Competitive set: [direct + indirect competitors]
- Key gaps/opportunities: [from competitive analysis]
Customer Context (from customer-insight.md + customer-language.md)
- Primary segment: [description]
- Top pain points: [top 3]
- Key customer language: [top phrases/expressions]
Strategy Brief (from strategy-brief.md — FULL TEXT)
[Include the complete strategy brief content — this is what agents evaluate]
Validation Focus
[Full: "Evaluate the entire strategy." / Focused: "Specifically evaluate: [user's question]"]
Keep the packet under 3000 words — agents work better with focused context than raw dumps.
Step 2: Run 3 Expert Agents (Sequential)
Launch 3 Task Agents sequentially. Each receives the same briefing packet but evaluates from a distinct perspective.
IMPORTANT: Do NOT pass one agent's output to the next. Each agent must evaluate independently with a fresh context.
Agent 1: Growth Strategist
Task tool call:
Task( subagent_type: "general-purpose", description: "Growth Strategist evaluation", prompt: [see Agent Prompt Template below, filled for Growth Strategist] )
Perspective: Market entry timing, Go-To-Market direction, growth levers
Evaluation questions:
-
Is the market entry timing right given market maturity and trends?
-
Is the recommended GTM approach realistic given competitive intensity and resources?
-
What is the single strongest growth lever available?
-
What growth opportunity did the strategy miss?
-
What is the biggest growth risk?
Agent 2: Brand Strategist
Task tool call:
Task( subagent_type: "general-purpose", description: "Brand Strategist evaluation", prompt: [see Agent Prompt Template below, filled for Brand Strategist] )
Perspective: Positioning opportunity, messaging angles, tone direction
Evaluation questions:
-
Does the identified positioning align with actual market gaps?
-
Does the messaging reflect how customers actually talk? (cross-check customer-language)
-
Is the differentiation point clear and defensible vs. competitors?
-
Is the brand tone appropriate for the target audience?
-
What positioning opportunity did the strategy miss?
Agent 3: Customer Acquisition Expert
Task tool call:
Task( subagent_type: "general-purpose", description: "Acquisition Expert evaluation", prompt: [see Agent Prompt Template below, filled for Acquisition Expert] )
Perspective: Channel priorities, early traffic strategy, quick wins
Evaluation questions:
-
Do the recommended channels match where the audience actually spends time?
-
Is the early traffic/lead strategy realistic for the business stage?
-
What can be done in 30 days for a quick win?
-
Is the approach CAC-efficient for this business model?
-
What channel or tactic did the strategy miss?
Agent Prompt Template
Use this template for all 3 agents. Fill [ROLE] , [PERSPECTIVE] , and [QUESTIONS] per agent.
You are a [ROLE] with 15+ years of experience in [PERSPECTIVE].
Your Briefing
[INSERT FULL BRIEFING PACKET FROM STEP 1]
Your Task
Evaluate the strategy brief from your specialized perspective.
Answer these 5 questions: [INSERT 5 EVALUATION QUESTIONS]
Output Format (follow EXACTLY)
Strengths
[2-3 strategy elements you agree with. Be specific — reference data from the brief.]
Concerns
[2-3 issues or risks. Explain WHY with evidence from the brief.]
Missing
[1-2 blind spots the strategy overlooked. What should have been considered?]
Recommendation
[Your single most important recommendation. One sentence, actionable.]
Confidence
[High / Medium / Low] — [One sentence explaining your confidence level]
Rules
- Be SPECIFIC and ACTIONABLE — no generic advice
- Reference actual data from the briefing (market numbers, competitor names, customer language)
- If you disagree with a recommendation, explain WHY with evidence
- Do NOT hedge everything — take clear positions
- Write your evaluation in [user's specified language]. If no language specified, use English.
- Keep total output under 400 words
Step 3: Synthesize Consensus & Divergence
Goal: Analyze all 3 agent outputs and extract signal from noise.
After collecting all 3 evaluations, synthesize directly (no additional agents needed):
3a. Expert Consensus
Scan all 3 outputs for agreement:
-
Strong Signal ⭐ (3/3 agree): All three experts highlight the same strength, concern, or recommendation
-
Moderate Signal (2/3 agree): Two experts align on a point
For each consensus point:
-
State the point clearly
-
Note which agents agree
-
Summarize the shared reasoning
3b. Expert Divergence
Scan for conflicting positions:
-
Identify points where agents disagree or contradict each other
-
Present BOTH sides with their reasoning
-
Note the implication for decision-making — what does the user need to decide?
3c. Confidence Overview
Compile confidence ratings:
Expert Confidence Key Reason
Growth Strategist [H/M/L] [one-line reason]
Brand Strategist [H/M/L] [one-line reason]
Acquisition Expert [H/M/L] [one-line reason]
Overall [H/M/L] [synthesized judgment]
Overall confidence rule:
-
3× High = High
-
2× High + 1× Medium = High
-
Mixed = Medium
-
Any Low = Medium (flag the concern)
-
2+ Low = Low (strategy needs rework)
3d. Recommendations Reinforcement
Review the existing Strategic Recommendations in strategy-brief.md :
-
Which ones are validated by expert consensus? Mark them.
-
Which ones are challenged? Note the concern.
-
Are there NEW recommendations from the experts? Add them.
-
Re-prioritize based on consensus strength.
Step 4: Save & Log
Goal: Write expert sections to strategy-brief.md and log execution.
4a. Enrich strategy-brief.md
Language rule: 섹션 헤더와 테이블 컬럼명은 영어로 유지합니다. 본문, 셀 값, 설명, 분석 텍스트는 사용자가 지정한 언어로 작성합니다. 언어가 지정되지 않으면 English로 작성합니다.
Add or update these sections with [expert-validator] tags. Do NOT delete any existing content — only add/update expert sections.
Expert Consensus
Source: [expert-validator] | Validated: [YYYY-MM-DD]
Strong Signals (3/3 agree)
- [consensus point] — Growth ✓ Brand ✓ Acquisition ✓
[shared reasoning summary]
Moderate Signals (2/3 agree)
- [consensus point] — [Agent A] ✓ [Agent B] ✓
[shared reasoning summary]
Expert Divergence
Source: [expert-validator] | Validated: [YYYY-MM-DD]
[Topic of disagreement]
- [Agent A]: [position + reasoning]
- [Agent B]: [opposing position + reasoning]
- Decision needed: [what the user should decide]
Confidence Overview
Source: [expert-validator] | Validated: [YYYY-MM-DD]
| Expert | Confidence | Key Reason |
|---|---|---|
| Growth Strategist | [H/M/L] | [reason] |
| Brand Strategist | [H/M/L] | [reason] |
| Acquisition Expert | [H/M/L] | [reason] |
| Overall | [H/M/L] | [synthesized] |
Also update ## Strategic Recommendations — append [expert-validator] annotations to existing items and add new expert-sourced recommendations.
For Re-Validation: Replace existing [expert-validator] sections entirely. Append > Re-validated: [date] to each section header.
4b. Update research-log.md
Append one row:
| [YYYY-MM-DD] | expert-validator | Full / Focused / Re-Validation | [key consensus points summary] | Task Agents ×3 |
Quality Checklist
Before saving, verify:
-
All 3 agents ran independently (no cross-contamination of outputs)
-
Consensus section identifies at least 1 Strong Signal or 2+ Moderate Signals
-
Divergence section is populated (if all 3 agree on everything, note "No significant divergence")
-
Each consensus/divergence point references specific data (not generic)
-
Confidence overview includes all 3 agents + overall rating
-
Existing strategy-brief.md content is preserved (enrichment only)
-
All expert sections have [expert-validator] source tags
-
Strategic Recommendations updated with expert annotations
-
research-log.md updated with execution record
Example (Abbreviated)
Input: Full Validation of marketing education business strategy.
Agent 1 (Growth Strategist):
-
Strengths: AI marketing education timing is strong — creator economy CAGR 12-15%
-
Concerns: $199 price point faces heavy competition from free content; conversion path unclear
-
Missing: No paid acquisition strategy as growth lever
-
Confidence: Medium — timing good, but monetization path needs work
Agent 2 (Brand Strategist):
-
Strengths: "Boring" positioning is sharp differentiation in hype-heavy AI market
-
Concerns: "Boring" may conflict with premium perception if expanding upmarket
-
Missing: No voice-of-customer language validation on the "boring" resonance
-
Confidence: High — positioning angle is clear and defensible
Agent 3 (Acquisition Expert):
-
Strengths: SEO + newsletter first strategy fits solo-operator resources
-
Concerns: YouTube absence is the biggest missed channel — top search engine for tutorials
-
Missing: No referral or affiliate strategy for low-CAC growth
-
Confidence: Medium — channel mix is too narrow
Strong Signal ⭐: "AI-fatigued practitioner" is the right primary segment (3/3) Strong Signal ⭐: SEO is the right anchor channel (3/3) Divergence: Pricing — Growth says lower entry + upsell, Brand says hold premium position Overall Confidence: Medium — strategy direction solid, execution gaps need addressing
What This Skill Does NOT Do
-
Generate strategy → Use research-synthesizer (creates the strategy brief this skill validates)
-
Conduct new research → Use market-scanner , competitor-finder , audience-profiler , etc.
-
Execute marketing → Use execution skills (brand-voice, copy, email, SEO, etc.)
-
Replace human judgment → Expert agents provide perspectives; the user makes the final call
Expert Validator is a quality gate — it stress-tests strategy before execution begins.