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 theworkflowkeyword, 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:
- Assemble panel (3-5 experts based on problem domain)
- Each expert provides independent perspective (parallel, not sequential)
- Synthesize recommendations with attribution
Multi-Round Discussion
For complex problems requiring collaborative reasoning:
- Round 1: Each expert analyzes problem independently
- Round 2: Experts respond to each other's insights, building on or challenging points
- Round 3 (if needed): Converge on synthesis, resolve disagreements
- 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