Multi persona critique

Multi-Persona Critique: Parallel Philosophical Review of Proposals

Overview

This skill takes a set of proposals — feature ideas, architectural decisions, design choices, strategy options — and sends ALL of them to 5 distinct intellectual personas for parallel, independent critique. Each persona brings a different philosophical lens. The skill then synthesizes all critiques into a consensus report showing where personas agree, where they disagree, and what the disagreements reveal.

This is NOT the roast skill. Key differences:

• roast critiques CODE with HackerNews personas and validates file:line claims
• This skill critiques IDEAS/PROPOSALS with philosophical/methodological personas and evaluates logical coherence, practical viability, and human impact
• roast is evidence-based (checking actual code); this is argument-based (evaluating reasoning)

Key constraints baked into the workflow:

• Every persona sees ALL proposals — no cherry-picking
• Personas run in parallel with no awareness of each other — independence is the source of value
• Ratings are mandatory: STRONG / PROMISING / WEAK / REJECT for every proposal from every persona
• Rankings are mandatory: each persona orders proposals from strongest to weakest
• Fairness mandate: genuine strengths must be acknowledged, genuine weaknesses explained with precision
• Disagreements are preserved, not averaged away — the disagreements ARE the insight
• The synthesis phase adds cross-cutting analysis, it does not edit persona outputs

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Reference Loading Table

Signal	Load These Files	Why
example-driven tasks, errors	examples-and-errors.md	Loads detailed guidance from examples-and-errors.md.
dispatching the five critique personas (Phase 2)	personas.md	Loads detailed guidance from personas.md.
writing the Phase 5 synthesis report	synthesis-template.md	Loads detailed guidance from synthesis-template.md.
roast-style code critique with HN personas	roast.md	Loads the roast workflow: evidence-based critique via 5 HN personas with claim validation.
HN persona specs, claim format, validation verdicts	hn-personas.md	Loads HN commenter persona specifications, prompt template, and claim format.

Instructions

Phase 1: UNDERSTAND PROPOSALS

Goal: Extract or generate clear, numbered proposals ready for critique.

Step 1: Determine input mode

Input	Action
User provides proposals directly	Extract and number them
User says "generate N ideas about X"	Research the domain, read relevant code/docs, then generate proposals
Ambiguous input	Ask user to clarify before proceeding

Step 2: Normalize proposals

Each proposal must be a clear, self-contained description (2-4 sentences) that any of the 5 personas can evaluate independently. If user-provided proposals are vague, expand them to include:

• What the proposal does
• Why it matters (the problem it solves)
• How it differs from the status quo

If generating proposals, research the domain first:

• Use Glob and Grep to understand existing code, docs, and architecture
• Use Read to examine key files relevant to the domain
• Generate proposals grounded in actual context, not hypotheticals

Step 3: Number and present

Present the numbered proposal list back to the user before proceeding. Format:

Proposals for critique:
1. [Title] — [2-4 sentence description]
2. [Title] — [2-4 sentence description]
...

Gate: Numbered list of proposals ready. Each proposal is self-contained with 2-4 sentences. Proceed only when gate passes.

Phase 2: BRIEF PERSONAS

Goal: Construct prompts for each of the 5 personas.

Load the full persona specifications from ${CLAUDE_SKILL_DIR}/references/personas.md. For each persona, construct a prompt containing an identity block, the numbered proposals, rating and ranking requirements, a fairness mandate, and the structured output format — see ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md (Phase 2: Persona Prompt Construction) for the complete construction recipe.

Gate: 5 persona prompts constructed, each containing all proposals and the full persona specification. Proceed only when gate passes.

Phase 3: DISPATCH (Parallel)

Goal: Launch all 5 personas in parallel and collect independent critiques.

Launch 5 agents using the Agent tool, one per persona. Each agent runs independently with no awareness of other personas.

The 5 parallel agents:

1. The Logician (Bertrand Russell) Focus: Logical coherence, hidden assumptions, falsifiability, necessity vs novelty

2. The Pragmatic Builder (20-year staff engineer) Focus: Build cost vs value, maintenance burden, simpler alternatives, user need

3. The Systems Purist (Edsger Dijkstra) Focus: Accidental complexity, separation of concerns, elegance, failure modes

4. The End User Advocate (8-hours-a-day tool user) Focus: Daily impact, friction, delight, whether the problem is already solved

5. The Skeptical Philosopher (Illich/Postman/Franklin) Focus: Human agency, dependency risk, genuine vs manufactured problems, unintended consequences

Each agent must produce:

• A rating (STRONG / PROMISING / WEAK / REJECT) for every proposal with 2-3 sentence justification
• A ranked list of all proposals from strongest to weakest
• Any cross-cutting observations that apply to multiple proposals

CRITICAL: Wait for ALL 5 agents to complete before proceeding to Phase 4. Do not begin synthesis on partial results. Every persona must contribute before consensus can be determined.

Gate: All 5 persona reports received. Each report contains ratings for all proposals and a ranked list. Proceed only when gate passes.

Phase 4: SYNTHESIZE

Goal: Build a consensus matrix and identify agreement, disagreement, and cross-cutting patterns.

Step 1: Build the consensus matrix

Create a matrix: proposals (rows) x personas (columns) x ratings. See the consensus matrix template in ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md.

Step 2: Classify consensus patterns

For each proposal, classify:

• CONSENSUS (4+ personas agree within one tier): Strong signal
• CONTESTED (2-3 split): The disagreement itself is informative
• OUTLIER (1 disagrees with 4): Worth understanding why one persona sees differently

Step 3: Extract disagreement specifics

For CONTESTED and OUTLIER proposals, extract the specific disagreement:

• What does each side see that the other does not?
• Is the disagreement about values (what matters) or facts (what is true)?
• Does one persona have domain-relevant insight the others lack?

Step 4: Calculate weighted consensus score

Assign numeric values: STRONG=3, PROMISING=2, WEAK=1, REJECT=0

For each proposal: sum all 5 ratings, giving a score from 0-15.

Step 5: Rank proposals by consensus score

Sort proposals from highest to lowest weighted score. Note ties and what distinguishes tied proposals.

Gate: Consensus matrix complete with classifications, disagreement analysis, and ranked scores. Proceed only when gate passes.

Phase 5: PRESENT

Goal: Deliver the synthesis report using the template from ${CLAUDE_SKILL_DIR}/references/synthesis-template.md.

Load the synthesis template and populate all 7 sections (Consensus Matrix; Features to Build; Worth Investigating; Interesting Disagreements; Shelve; Cross-Cutting Insights; Deepest Insight). See ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md (Phase 5: Synthesis Report Sections) for each section's purpose and score-band criteria.

Gate: Report complete with all sections populated. Critique done.

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Examples, Error Handling, and Detection

See ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md for:

• Examples: critique provided proposals, generate+critique ideas, evaluate architectural options
• Failure modes: averaging disagreement, post-hoc rationalization, consensus-as-truth, skipping justification, resolving contested items, sequential execution
• Error Handling: bare ratings, skipped proposals, uniform agreement, fewer than 2 proposals

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References

Reference Files

• ${CLAUDE_SKILL_DIR}/references/personas.md: Full persona specifications, identity, evaluation criteria, prompt templates
• ${CLAUDE_SKILL_DIR}/references/synthesis-template.md: Consensus matrix format and synthesis report structure
• ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md: Worked examples, failure modes, error handling

Related Skills

• roast: Code critique with evidence-based validation (complementary — roast critiques code, this critiques ideas)
• decision-helper: Weighted decision scoring for architectural choices (narrower — single-dimension scoring vs multi-persona critique)