consensus
Use when comparing architectural choices, technology options, build-vs-buy decisions, feature proposals, high-impact tradeoffs, multi-team decisions, hard-to-reverse choices, or risk-heavy alternatives.
Best use case
consensus is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when comparing architectural choices, technology options, build-vs-buy decisions, feature proposals, high-impact tradeoffs, multi-team decisions, hard-to-reverse choices, or risk-heavy alternatives.
Teams using consensus should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/consensus/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How consensus Compares
| Feature / Agent | consensus | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when comparing architectural choices, technology options, build-vs-buy decisions, feature proposals, high-impact tradeoffs, multi-team decisions, hard-to-reverse choices, or risk-heavy alternatives.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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): 1. **Neutral** — state the decision, list all factors (technical, organizational, timeline, risk), note missing information, present assessment without leaning toward a conclusion. 2. **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. 3. **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: 1. **Points of agreement** — where all perspectives align (strong signal) 2. **Points of disagreement** — where they diverge and why 3. **Recommendation** — with confidence level: **low** / **medium** / **high** 4. **Would change if** — conditions that would flip the recommendation 5. **Next steps** — concrete actions based on the recommendation </workflow> <validation> ### 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 </validation> <example> ## 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. </example> ## References - **[Consensus Strategy](references/consensus-strategy.md)** — Mode selection and escalation criteria - **[Stance Rotation](references/stance-rotation.md)** — Detailed rotation steps, subagent dispatch, synthesis framework - **[Stance Prompts](../perspectives/references/stances.md)** — Advocate, critic, neutral prompts with ethical guardrails (from perspectives skill) <guardrails> ## Guardrails Add guardrails instructions here. </guardrails>
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