structured-consensus

name	structured-consensus
description	Structured Consensus Campaign — converge multiple perspectives into shared agreement through iterative structured dialogue using Delphi variants, NGT, RAND/UCLA, Consensus Conference methods.
execution	campaign
dependencies	{"strategies":["appropriateness-bounding","argument-crystallization","convergence-distillation","disagreement-cartography","futures-calibration"],"campaigns":["convergence-multi-criteria-scoring"],"sops":["context-checkpoint","context-init","convergence-multi-stakeholder-simulation","convergence-saturation-detection"]}

Structured Consensus

Converge multiple independent perspectives into shared agreement through iterative structured dialogue. This campaign orchestrates Delphi variants, Nominal Group Technique, RAND/UCLA Appropriateness Method, and Consensus Conference protocols to systematically reduce disagreement while preserving legitimate dissent.

Strategy Routing

Signal	Strategy
Iterative convergence to single answer / establish guidelines / determine threshold	convergence-distillation
Map disagreement structure / wicked problems / value conflicts	disagreement-cartography
Aggregate probability judgments / technology timeline / market forecast	futures-calibration
Establish acceptability standards / medical guidelines / regulatory standards	appropriateness-bounding
Distill strongest arguments / policy deliberation / interdisciplinary dispute	argument-crystallization

Manifest

Strategies

Strategy	Method Family	Purpose
convergence-distillation	Classic Delphi, Modified Delphi, NGT	Iterative convergence to single answer
disagreement-cartography	Policy Delphi, Argument Delphi, SAST	Map disagreement structure
futures-calibration	Real-Time Delphi, Prediction Markets	Aggregate probability judgments
appropriateness-bounding	RAND/UCLA Appropriateness, Consensus Conference	Establish acceptability standards
argument-crystallization	Argument Delphi, Dialectical Delphi	Distill strongest arguments

Tactics

Tactic	Purpose	SOPs
iterative-convergence-round	Collect → feedback → revise → check → decide	judgment-collection, feedback-distribution, consensus-measurement, round-decision
disagreement-mapping	Collect → cluster → extract arguments → visualize	judgment-collection, cluster-analysis, argument-extraction, disagreement-visualization
threshold-calibration	Adjust thresholds → observe consensus changes	threshold-sweep, consensus-classification, consensus-measurement

SOPs

SOP	Input	Output
judgment-collection	question, perspectives[]	judgments[]
feedback-distribution	judgments[], round_n	feedback_report
consensus-measurement	judgments[]	consensus_score, method_used
round-decision	consensus_score, round_n, stability	continue/stop
cluster-analysis	judgments[]	clusters[], cluster_characterization[]
argument-extraction	cluster, judgments[]	arguments[]
disagreement-visualization	clusters[], arguments[]	disagreement_map
threshold-sweep	judgments[], threshold_range	threshold_curve
consensus-classification	judgments[], threshold	consensus_items[], dissensus_items[]
consensus-synthesis	rounds_history, final_judgments	consensus_report

Budget Table (M Tier)

Parameter	Constraint
Perspectives/experts	>=4 independent perspectives
Iteration rounds	2-4 rounds (until consensus threshold or stability)
Consensus threshold	>=70% agreement or IQR <= 1
Dissent documentation	All non-consensus items must document reasons

MCP Tools

• mcp__semantic-scholar__relevanceSearch — find methodological references
• mcp__wiki-vault__vault_search — retrieve prior consensus results from vault

Context Management

• Each round's judgments are stored in state and passed forward
• Feedback reports summarize prior round without exposing individual identities
• Final synthesis aggregates all rounds into a single consensus report
• Non-consensus items are explicitly documented with dissent rationale

Available Strategies

Optional, no fixed order; the final leaf is always a sop.

Strategy	When to use
appropriateness-bounding	Establish acceptability standards through RAND/UCLA Appropriateness Method or Consensus Conference protocols.
argument-crystallization	Distill the strongest arguments from each perspective through Argument Delphi or Dialectical Delphi methods.
convergence-distillation	Iterative convergence to a single answer through Classic Delphi, Modified Delphi, or Nominal Group Technique rounds.
disagreement-cartography	Map the structure of disagreement across perspectives using Policy Delphi, Argument Delphi, or SAST methods.
futures-calibration	Aggregate probability judgments across perspectives using Real-Time Delphi or prediction market mechanisms.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
context-checkpoint	Append research process and results to the current Phase's context file. Covers both process and results with genuine substance. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase.
context-init	Create a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed.
convergence-multi-stakeholder-simulation	Simulates diverse stakeholder perspectives and their strongest objections/support arguments. Shared across steel-manning and consensus campaigns.
convergence-saturation-detection	Determines when to stop iterating — coverage threshold met or marginal returns diminishing. Shared across all campaigns.

Available Campaigns

Optional, no fixed order; the final leaf is always a sop.

Campaign	When to use
convergence-multi-criteria-scoring	Multi-Criteria Scoring Campaign — evaluate and rank candidates against multiple weighted criteria using AHP, BWM, TOPSIS, VIKOR, ELECTRE, PROMETHEE, MAUT methods.