consensus
Auto-activate when evaluating architectural decisions, comparing technology choices, weighing design trade-offs, assessing feature proposals, making build-vs-buy decisions, choosing between competing approaches, when a decision has significant long-term consequences, when multipl
What it does
Consensus
Structured decision evaluation through stance rotation — analyze from advocate, critic, and neutral perspectives, then synthesize into a confidence-rated recommendation with concrete next steps.
<workflow>Workflow
Step 1: Select Mode
| Decision Scope | Mode | Reason |
|---|---|---|
| Bounded, reversible | Sequential (default) | All perspectives in one pass — fast |
| Multi-month or irreversible | Subagent | Three isolated subagents prevent cross-contamination |
| Perspectives suspiciously aligned | Escalate to Subagent | Lack of genuine disagreement signals contamination |
Use subagent mode when: the decision impacts more than 3 months of work, multiple teams are affected, or sequential perspectives align too easily (suspiciously low disagreement likely signals contamination — isolated subagents are required to get genuine divergence).
See references/consensus-strategy.md for full escalation criteria.
Step 2: Stance Rotation
Rotate through three perspectives (see references/stance-rotation.md for detailed prompts):
- Neutral — state the decision, list all factors (technical, organizational, timeline, risk), note missing information, present assessment without leaning toward a conclusion.
- Advocate — build the strongest case FOR: what problems does it solve, what synergies does it create, how can challenges be overcome? Subject to ethical guardrails — refuse to advocate if fundamentally harmful.
- Critic — rigorous scrutiny: real risks, overlooked complexities, simpler alternatives, flawed assumptions? Subject to ethical guardrails — acknowledge if the proposal is genuinely sound.
In subagent mode, dispatch three isolated subagents (one per stance) with identical context. Subagents must NOT see each other's output.
Step 3: Synthesize
Weigh all three perspectives and produce a recommendation:
- Points of agreement — where all perspectives align (strong signal)
- Points of disagreement — where they diverge and why
- Recommendation — with confidence level: low / medium / high
- Would change if — conditions that would flip the recommendation
- Next steps — concrete actions based on the recommendation
Validation Checkpoint
Before delivering the synthesis, verify:
- Each perspective contributed at least one unique point not raised by the others
- The critic identified at least one genuine risk (not manufactured disagreement)
- The recommendation confidence level is justified by the degree of inter-perspective agreement
- If all three perspectives agree too easily, escalate to subagent mode
Example
Decision: "Should we migrate from REST to GraphQL?"
| Perspective | Key Finding |
|---|---|
| Neutral | Current REST API has 47 endpoints; clients use ad-hoc field filtering. GraphQL would reduce over-fetching but adds schema maintenance. |
| Advocate | Mobile clients would cut payload size ~60%. Single endpoint simplifies versioning. Strong ecosystem tooling available. |
| Critic | Team has no GraphQL experience — 2-3 month learning curve. Caching is harder. Existing REST clients need migration path. |
Synthesis:
- Agreement: Current API has over-fetching problems worth solving.
- Disagreement: Whether the learning curve cost is justified given timeline.
- Recommendation: Adopt GraphQL for new endpoints only (confidence: medium).
- Would change if: Team had prior GraphQL experience (→ high confidence, full migration) or deadline is <3 months (→ stay REST).
- Next steps: 1) Prototype one high-traffic endpoint. 2) Measure payload reduction. 3) Decide on full migration after prototype.
References
- Consensus Strategy — Mode selection and escalation criteria
- Stance Rotation — Detailed rotation steps, subagent dispatch, synthesis framework
- Stance Prompts — Advocate, critic, neutral prompts with ethical guardrails (from perspectives skill)
Add guardrails instructions here. </guardrails>
Capabilities
Install
Quality
deterministic score 0.46 from registry signals: · indexed on github topic:agent-skills · 11 github stars · SKILL.md body (4,270 chars)