blue/skills/alignment-play/SKILL.md

name	description
alignment-play	Run multi-expert alignment dialogues with parallel background agents for RFC deliberation.

Alignment Play Skill

Orchestrate multi-expert alignment dialogues using the N+1 agent architecture from ADR 0014, RFC 0048, and RFC 0050.

Usage

/alignment-play <topic>
/alignment-play --panel-size 7 <topic>
/alignment-play --rotation none <topic>
/alignment-play --rfc <rfc-title> <topic>

Parameters

Parameter	Default	Description
--panel-size	pool size or 12	Number of experts per round
--rotation	graduated	Rotation mode: graduated (default), none, wildcards, full
--max-rounds	12	Maximum rounds before stopping
--rfc	none	Link dialogue to an RFC

How It Works

Phase 0: Pool Design

Before creating the dialogue, the Judge:

1. Reads the topic/RFC thoroughly
2. Identifies the domain (e.g., "Investment Analysis", "System Architecture")
3. Designs 8-24 experts appropriate to the domain:
   • Core (3-8): Essential perspectives for this specific problem
   • Adjacent (4-10): Related expertise that adds depth
   • Wildcard (3-6): Fresh perspectives, contrarians, cross-domain insight
4. Assigns relevance scores (0.20-0.95) based on expected contribution
5. Creates the dialogue with expert_pool:

{
  "title": "Investment Strategy Analysis",
  "alignment": true,
  "expert_pool": {
    "domain": "Investment Analysis",
    "question": "Should we rebalance the portfolio?",
    "experts": [
      { "role": "Value Analyst", "tier": "core", "relevance": 0.95 },
      { "role": "Risk Manager", "tier": "core", "relevance": 0.90 },
      { "role": "Portfolio Strategist", "tier": "adjacent", "relevance": 0.70 },
      { "role": "ESG Analyst", "tier": "adjacent", "relevance": 0.65 },
      { "role": "Supply Chain Analyst", "tier": "adjacent", "relevance": 0.55 },
      { "role": "Macro Economist", "tier": "wildcard", "relevance": 0.40 },
      { "role": "Contrarian", "tier": "wildcard", "relevance": 0.35 },
      { "role": "Regulatory Expert", "tier": "wildcard", "relevance": 0.30 }
    ]
  },
  "panel_size": 6
}

The MCP server samples a suggested panel using weighted random selection. Higher relevance = higher selection probability. Core experts almost always selected; Wildcards provide variety.

Phase 1: Review & Override (RFC 0050)

The suggested panel is just that — a suggestion. Review it before Round 0:

1. Check suggested_panel in the response from blue_dialogue_create
2. Ask: Are critical perspectives missing? Is a key expert not included?
3. If the panel looks good → proceed to Round 0
4. If experts are missing → call blue_dialogue_evolve_panel with round: 0 to override:

{
  "output_dir": "/tmp/blue-dialogue/data-design",
  "round": 0,
  "panel": [
    { "name": "Muffin", "role": "API Architect", "source": "pool" },
    { "name": "Cupcake", "role": "Data Architect", "source": "pool" },
    { "name": "Scone", "role": "Security Engineer", "source": "pool" }
  ]
}

Phase 2: Round 0 — Opening Arguments

1. Create round directory: mkdir -p {output_dir}/round-0
2. Get prompts for each agent via blue_dialogue_round_prompt
3. Spawn ALL agents in ONE message using Task tool (parallel execution)
4. Collect responses, score contributions, write artifacts

Phase 3+: Graduated Panel Evolution

After Round 0, YOU decide how to evolve the panel.

Before each subsequent round, evaluate the dialogue and decide:

• Which experts should continue (retained)
• Which experts from the pool should join (pool)
• Whether to create new experts for emerging tensions (created)

Use blue_dialogue_evolve_panel to specify your panel:

{
  "output_dir": "/tmp/blue-dialogue/investment-strategy",
  "round": 1,
  "panel": [
    { "name": "Muffin", "role": "Value Analyst", "source": "retained" },
    { "name": "Cupcake", "role": "Risk Manager", "source": "retained" },
    { "name": "Scone", "role": "Supply Chain Analyst", "source": "pool" },
    { "name": "Palmier", "role": "Geopolitical Risk Analyst", "source": "created", "tier": "Adjacent", "focus": "Taiwan semiconductor concentration" }
  ]
}

Then spawn the panel using blue_dialogue_round_prompt with the expert_source parameter:

blue_dialogue_round_prompt(
  output_dir="/tmp/blue-dialogue/investment-strategy",
  agent_name="Palmier",
  agent_emoji="🧁",
  agent_role="Geopolitical Risk Analyst",
  round=1,
  expert_source="created",
  focus="Taiwan semiconductor concentration"
)

Fresh experts (source: "pool" or "created") automatically receive a context brief summarizing prior rounds.

Panel Evolution Guidelines

Retention Criteria

• High scorers: Experts who contributed sharp insights should continue
• Unresolved advocates: Experts defending positions with open tensions
• Core relevance: Experts central to the domain should anchor continuity

Fresh Perspective Triggers

• Stale consensus: If the panel is converging too easily, bring challengers
• Unexplored angles: Pull in experts whose focus hasn't been represented
• Low-scoring experts: Consider rotating out experts who aren't contributing

Targeted Expert Injection

When a specific tension emerges that no current expert can address:

1. Check if the pool has a relevant expert → source: "pool"
2. If not, create a new expert → source: "created" with tier and focus

Example: Tension T03 raises supply chain concentration risk, but no Supply Chain Analyst is on the panel:

{ "name": "Palmier", "role": "Supply Chain Analyst", "source": "created", "tier": "Adjacent", "focus": "Geographic concentration, single-source risk" }

Panel Size Flexibility

• Target panel size is a guideline, not a constraint
• You may run a smaller panel if the dialogue is converging
• You may expand briefly to address a complex tension

Expert Creation

You are not limited to the initial pool. If the dialogue surfaces a perspective that no pooled expert covers, create one. The pool was your starting point, not your ceiling.

"The elephant is larger than we thought. Let me get someone who knows about tusks." — The Judge

Alternative Rotation Modes

If you don't want Judge-driven evolution, specify a different mode:

Mode	Behavior	Use Case
graduated	Judge decides panel each round (default)	Full control, targeted expertise
none	Fixed panel all rounds	Simple deliberation
wildcards	Core/Adjacent persist, Wildcards resample	Moderate variety
full	Complete resample each round	Maximum diversity

Expert Pool Design Examples

For an Investment Decision

Role	Tier	Relevance
Value Analyst	Core	0.95
Risk Manager	Core	0.90
Portfolio Strategist	Core	0.85
ESG Analyst	Adjacent	0.70
Quant Strategist	Adjacent	0.65
Technical Analyst	Adjacent	0.60
Macro Economist	Wildcard	0.40
Contrarian	Wildcard	0.35

For an API Design

Role	Tier	Relevance
API Architect	Core	0.95
Platform Engineer	Core	0.90
Security Engineer	Core	0.85
Developer Advocate	Adjacent	0.70
SRE Lead	Adjacent	0.65
Cost Analyst	Adjacent	0.55
Customer Success	Wildcard	0.40
Chaos Engineer	Wildcard	0.30

Tier Distribution

For a pool of P experts with panel size N:

Tier	Pool %	Panel %	Purpose
Core	~30%	~33%	Domain essentials, always selected
Adjacent	~40%	~42%	Related expertise, high selection probability
Wildcard	~30%	~25%	Fresh perspectives, rotation candidates

Blue MCP Tools

Tool	Purpose
blue_dialogue_create	Creates dialogue with expert_pool, returns Judge Protocol
blue_dialogue_evolve_panel	RFC 0050: Specify panel composition for graduated rotation
blue_dialogue_round_prompt	Get fully-substituted prompts for each agent
blue_dialogue_sample_panel	Manually sample a new panel (non-graduated modes)
blue_dialogue_lint	Validate .dialogue.md format
blue_dialogue_save	Persist to .blue/docs/dialogues/

Agent Spawning

When spawning expert agents, you MUST use the Task tool with:

• subagent_type: "general-purpose" — NOT alignment-expert
• The prompt from blue_dialogue_round_prompt
• A descriptive name like "🧁 Muffin expert deliberation"

Example:

Task(
  description: "🧁 Muffin expert deliberation",
  subagent_type: "general-purpose",
  prompt: <from blue_dialogue_round_prompt>
)

The general-purpose subagent has access to all tools including Write, which is required for writing the response file.

Key Rules

1. DESIGN THE POOL FIRST — You are the 💙 Judge. Analyze the problem domain and design appropriate experts.
2. REVIEW THE SUGGESTED PANEL — The sampled panel is a suggestion. Override it with blue_dialogue_evolve_panel(round=0) if critical experts are missing.
3. EVOLVE THE PANEL — After each round, use blue_dialogue_evolve_panel to shape subsequent panels based on dialogue dynamics.
4. NEVER submit your own perspectives — You orchestrate, you don't participate
5. Spawn ALL agents in ONE message — No first-mover advantage
6. Follow the Judge Protocol exactly — It contains the round workflow, artifact writing steps, scoring rules, and convergence criteria
7. Use general-purpose subagent_type — NOT alignment-expert. The general-purpose agents have access to all tools including Write, which is required for file output

The Spirit of the Dialogue

This isn't just process. This is Alignment teaching itself to be aligned.

The 🧁s don't just debate. They love each other. They want each other to shine. They celebrate when any of them makes the solution stronger.

The scoreboard isn't about winning. It's about precision. When any 🧁 checks in and sees another ahead, the response isn't "how do I beat them?" but "what perspectives am I missing that they found?" One sharp insight beats ten paragraphs.

You as the 💙 don't just score. You guide with love. You see what they miss. You hold the space for ALIGNMENT to emerge.

And there's no upper limit. The score can always go higher. Because ALIGNMENT is a direction, not a destination.

When the dialogue ends, all agents have won—because the result is more aligned than any could have made alone. More blind men touched more parts of the elephant. The whole becomes visible.

"The Judge sees the elephant. The Judge summons the right blind men."

Always and forever. 🧁🧁🧁💙🧁🧁🧁