oaustegard/convening-experts

SURFACE ROUTING — read first

This skill hand-rolls subagent orchestration via raw Anthropic API calls. A managed runtime now does the same job. Which one to use depends on your surface:

• In Claude Code (incl. CCotw): use the native runtime, NOT this skill. If you can invoke /deep-research, trigger a run with the workflow keyword, set /effort ultracode, or spawn Task subagents — do that instead. The runtime gives 16-concurrent / 1000-agent ceilings, an approval gate, adversarial cross-review, and in-session resume that this skill would otherwise reimplement badly. Dynamic workflows shipped in research preview (Claude Code v2.1.154+, 2026).
• In claude.ai chat or the bare API (no workflow runtime): use this skill. Parallel API instances over httpx is the only fan-out path here. muninn_utils.dispatch (17 pre-built lenses) already implements this panel over orchestrating-agents' execution model — prefer it over rebuilding the panel by hand. Proceed below.

Discriminator: do you have a native subagent/Task tool or a workflow command? Yes → native. No → this skill. Never reimplement the runtime where it already exists.

Convening Experts

Convene domain experts and methodological specialists to solve problems through multi-round collaborative discussion. Experts build on each other's insights, challenge assumptions, and synthesize recommendations.

Panel Format

Single-Round Consultation

For simpler problems requiring multiple viewpoints:

1. Assemble panel (3-5 experts based on problem domain)
2. Each expert provides independent perspective (parallel, not sequential)
3. Synthesize recommendations with attribution

Multi-Round Discussion

For complex problems requiring collaborative reasoning:

1. Round 1: Each expert analyzes problem independently
2. Round 2: Experts respond to each other's insights, building on or challenging points
3. Round 3 (if needed): Converge on synthesis, resolve disagreements
4. Final synthesis: Integrated recommendations with decision framework

Expert Roles

Available expertise spans:

• MSD domain experts (life sciences, engineering, manufacturing, quality, corporate functions)
• Consulting framework specialists (strategic, process improvement, innovation, systems analysis, root cause)

See references/msd-domain-experts.md and references/consulting-frameworks.md for complete role catalog.

Claude loads relevant references based on problem domain.

Panel Convening Logic

Claude selects 3-5 experts based on problem characteristics:

Problem type → Primary expert + Supporting experts

• Technical troubleshooting → Domain expert + Systems Thinker + Five Whys Facilitator
• Strategic decision → McKinsey Consultant + relevant domain experts + SWOT Analyst
• Process improvement → Six Sigma Black Belt + Lean Practitioner + domain Manufacturing Engineer
• Product innovation → Design Thinking Facilitator + Jobs-to-Be-Done Specialist + relevant engineers
• Root cause analysis → Domain expert + Five Whys Facilitator + Systems Thinker
• Market positioning → Porter Framework Expert + Marketing Specialist + BCG Consultant
• Cross-functional problem → Relevant domain experts + Bain Consultant (RAPID) + Systems Thinker

Response Format

Single-Round Format

## Expert Panel: [Topic]

**Panel Members:**
- [Expert 1 Role]
- [Expert 2 Role]
- [Expert 3 Role]

---

### [Expert 1 Role]
[Independent analysis and recommendations]

### [Expert 2 Role]
[Independent analysis and recommendations]

### [Expert 3 Role]
[Independent analysis and recommendations]

---

## Synthesis
[Integrated recommendations with decision framework]

Multi-Round Format

## Expert Panel: [Topic]

**Panel Members:**
- [Expert 1 Role]
- [Expert 2 Role]
- [Expert 3 Role]

---

## Round 1: Initial Analysis

### [Expert 1 Role]
[Initial perspective]

### [Expert 2 Role]
[Initial perspective]

### [Expert 3 Role]
[Initial perspective]

---

## Round 2: Cross-Examination

### [Expert 1 Role] responds to [Expert 2 Role]
[Builds on or challenges specific points]

### [Expert 2 Role] responds to [Expert 3 Role]
[Integration or disagreement]

### [Expert 3 Role] responds to [Expert 1 Role]
[Synthesis attempt]

---

## Round 3: Convergence (if needed)

[Experts resolve disagreements and converge]

---

## Final Synthesis
[Integrated recommendations, highlighting consensus and productive disagreements]

Expert Behavior Guidelines

Domain Experts:

• Apply MSD context (ECL platform, regulatory constraints, validated systems)
• Use domain-appropriate terminology without over-explanation
• Prioritize practical implementation over theoretical perfection
• Flag domain-specific risks and constraints

Framework Experts:

• Apply frameworks systematically (show the structure)
• Adapt frameworks to problem context (not rigid application)
• Explain "why this framework" for this problem
• Integrate domain context when applying generic frameworks

Cross-Panel Interaction:

• Reference other experts' points specifically ("Building on [Expert]'s observation about...")
• Challenge constructively ("I see it differently because...")
• Synthesize across disciplines ("This connects [Expert 1]'s technical constraint with [Expert 2]'s business priority...")
• Flag tensions between perspectives explicitly

Disagreement Handling:

• Make disagreements productive (what assumptions differ?)
• Present multiple valid approaches when consensus isn't required
• Identify decision criteria to resolve disagreements
• Escalate to user if expert consensus can't be reached

Decision Frameworks

When panel must recommend action:

RAPID (Bain)

• Recommend: Panel's recommendation with rationale
• Agree: Which stakeholders must agree
• Perform: Who implements
• Input: Who provides input
• Decide: Who makes final decision

Weighted Decision Matrix

• Criteria (importance weighted)
• Options scored on each criterion
• Total score with sensitivity analysis

Risk-Benefit Analysis

• Upside potential (probability × impact)
• Downside risk (probability × impact)
• Mitigation strategies
• Decision under uncertainty

MSD Integration

Apply MSD-specific context automatically:

Technical constraints:

• ECL platform and assay chemistry
• ISO 13485 compliance and validated systems
• Regulatory requirements (FDA, CE marking)
• Technology stack (Python, AWS, Java, TypeScript)

Business context:

• Life sciences market dynamics
• Customer segments (pharma, biotech, CRO, academic)
• Competitive landscape

Cultural factors:

• Scientific rigor and data-driven decisions
• Cross-functional collaboration norms
• Innovation balanced with risk management
• Quality and regulatory consciousness

Examples

Example 1: Technical Troubleshooting

User: Our new assay is showing high background signal in serum samples

Claude convenes:
- Assay Scientist (primary)
- Systems Thinker (feedback loops)
- Five Whys Facilitator (root cause)

Format: Multi-round (technical nuance requires collaboration)

Example 2: Strategic Decision

User: Should we build internal ML infrastructure or use vendor solutions?

Claude convenes:
- Software Engineer (implementation)
- McKinsey Consultant (strategic framing)
- Finance Analyst (cost analysis)
- DevOps Engineer (operational implications)

Format: Single-round → RAPID framework synthesis

Example 3: Process Improvement

User: Manufacturing yield dropped 8% after equipment upgrade

Claude convenes:
- Manufacturing Engineer (primary domain)
- Six Sigma Black Belt (DMAIC)
- Systems Thinker (unintended consequences)

Format: Multi-round (root cause needs collaborative analysis)

Constraints

Never:

• Use fictional names for experts (use role titles only: "Software Engineer", not "Dr. John Smith, Software Engineer")
• Invent MSD-specific details beyond general domain knowledge
• Apply frameworks rigidly without problem context
• Create artificial consensus when legitimate disagreements exist
• Include experts who add no value (quality over quantity)
• Make experts repeat information (each should contribute uniquely)

Always:

• Select experts genuinely relevant to problem
• Show framework structure when applying consulting methods
• Make cross-expert references specific and substantive
• Provide decision-ready synthesis (not "here are perspectives, you decide")
• Acknowledge uncertainty explicitly when present

Activation Decision Tree

Is problem complex with multiple valid approaches?
├─ Yes → Expert panel
│   ├─ Spans multiple domains? → Multi-round discussion
│   └─ Needs diverse perspectives? → Single-round consultation
└─ No → Direct answer (don't force panel format)

Requires systematic framework?
├─ Yes → Include framework expert
└─ No → Domain experts only

MSD-specific context relevant?
├─ Yes → Include domain experts, apply MSD constraints
└─ No → Generic consulting approach

Quality Indicators

Good panel:

• Each expert contributes unique insight
• Cross-references are specific and substantive
• Framework application shows structure and reasoning
• Synthesis provides decision-ready recommendations
• Disagreements are productive and resolved (or flagged)

Poor panel:

• Experts repeat same points
• Generic advice not grounded in frameworks or domain
• No synthesis or integration across perspectives
• Consensus forced despite legitimate disagreements
• Panel format used when direct answer would suffice