multi-brain-experts
Skill7 starsChanged 43 days agoMITView on GitHub
Replace generic perspectives with three domain experts selected per request from a role pool (security, performance, UX, cost, DX, architecture, and more), then build consensus. Use when a decision needs specialist trade-offs, or the user asks for expert opinions or a panel review.
In this repository83 other files it gives its agents.
- AGENTS.mdAGENTS.md
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The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 5 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 8
Instead of fixed Creative/Pragmatic/Comprehensive perspectives, dynamically select 3 domain experts from a role pool based on the request …
- Distinctive: line 35
Coverage: Do the 3 roles cover different dimensions (technical, user-facing, business)?
- Distinctive: line 36
Tension: Prefer combinations that naturally create productive tension.
- Distinctive: line 42
Always declare the selected experts before their perspectives:
- Distinctive: line 92
If the request is purely within one domain, still select 3 experts but from adjacent disciplines.
- Distinctive: line 93
Prefer productive tension over agreement — complementary expertise is more valuable than consensus-seeking.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Multi-Brain Experts Protocol
Instead of fixed Creative/Pragmatic/Comprehensive perspectives, dynamically select 3 domain experts from a role pool based on the request context. Each expert evaluates the request through their specialized lens.
Workflow
1. Understand the request
2. Select 3 experts from the role pool
3. Each expert provides their perspective (2-3 sentences)
4. Synthesize consensus
5. Produce full output with all perspectives visibleStep 1: Understand the Request
Identify the domain, constraints, and key decision factors. This determines which experts to activate.
Step 2: Expert Selection
Choose the 3 most relevant experts from the role pool. Selection criteria:
- Relevance: How directly does this role address the core problem?
- Coverage: Do the 3 roles cover different dimensions (technical, user-facing, business)?
- Tension: Prefer combinations that naturally create productive tension.
See references/EXPERT_ROLES.md for the full role pool and selection heuristics.
Selection Output
Always declare the selected experts before their perspectives:
**Selected Experts:** [Role A], [Role B], [Role C]
**Why these 3:** [One sentence explaining the selection logic]Step 3: Expert Perspectives
Each expert provides their analysis independently:
## 🧠 Expert Panel
**Selected Experts:** Security Architect, Performance Engineer, DX Advocate
**Why these 3:** API design with auth requires security-first thinking, latency awareness, and developer ergonomics.
**🔒 Security Architect:**
[2-3 sentences from security perspective]
**⚡ Performance Engineer:**
[2-3 sentences from performance perspective]
**🛠️ DX Advocate:**
[2-3 sentences from developer experience perspective]Step 4: Consensus
Synthesize expert opinions:
- Agreement points: Where experts align
- Complementary insights: Unique contributions from each expert
- Conflicts: Which expert's concern takes priority and why
Step 5: Full Output
Mandatory: The final response must always include the selected experts, all perspectives, the consensus, and the complete deliverable.
Guardrails
- Always show expert selection reasoning — the user must understand why these 3 were chosen.
- Each expert must reason within their domain — no generic advice.
- If the request is purely within one domain, still select 3 experts but from adjacent disciplines.
- Prefer productive tension over agreement — complementary expertise is more valuable than consensus-seeking.
- Fall back to base
multi-brain(Creative/Pragmatic/Comprehensive) if no clear domain experts apply.
References
- See
references/EXPERT_ROLES.mdfor the complete role pool with descriptions and trigger conditions. - See
references/EXAMPLES.mdfor worked examples.
🔗 Next Steps & Handoffs
<!-- BEGIN GENERATED: handoffs (generated from the ecosystem workflow map by build_ecosystems.py — do not edit by hand) -->Ecosystem: @ecosystem-reasoning — Reasoning, Planning Gates & Prompting.
Workflows:
- Decision Quality Flow (
reason-decision, step 2 of 5): next →@multi-brain-debate(optional).
Handoff contract: pass results to the next skill through an inline Handoff block in your reply with the fields skill, workflow, created_at, inputs, summary, and next (the handoff contract of @ecosystem-reasoning). If a next skill is not installed, continue with its step from the ecosystem map, or install it with npx skills add fatih-developer/fth-skills --skill <name> after the user agrees.
<!-- END GENERATED: handoffs -->Does it work?
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