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Decisions are not made in the moment of choosing — they are made in the structure of evaluation. A bad framework produces confident wrong answers. A good framework surfaces the right trade-offs and lets the decision survive scrutiny.

🎯 Convergence

Universal Convergence Engine for Research Decision-Making

Transforms unstructured candidate sets into ranked selections, balanced portfolios, and validated decisions through 6 parallel convergence campaigns spanning scoring, ranking, consensus, feasibility, optimization, and adversarial verification.


⚡ What It Does

  • 📊 Multi-criteria scoring — score and rank candidates against weighted criteria using AHP, TOPSIS, ELECTRE, PROMETHEE, and non-compensatory screening methods
  • 🔄 Pairwise ranking — produce global rankings via systematic pairwise comparisons with consistency checking and convergence detection
  • 🤝 Structured consensus — resolve disagreements between multiple perspectives using Delphi, Nominal Group Technique, and dialectical synthesis
  • 🔬 Feasibility assessment — evaluate real-world viability using TRL, NASSS, Stage-Gate, TRIZ, TOC, and parametric estimation
  • 💼 Portfolio optimization — select balanced combinations using Markowitz, Knapsack, Pareto, Real Options, MAP-Elites, and minimax regret
  • ⚔️ Steel-manning — adversarial verification via Devil's Advocacy, Pre-mortem, Red Teaming, and Dialectical Inquiry

🏗️ Architecture

ENTRY.md (campaign router)
  → Campaign (6): self-contained convergence paradigm
    → Strategy: selected by convergence intent/scenario
      → Tactic: multi-step orchestration pattern
        → SOP: single operation (subagent or import)

Campaign Routing

Signal Campaign
score/rank candidates against multiple criteria multi-criteria-scoring
produce global ranking via pairwise comparisons pairwise-ranking
multiple perspectives disagree, need convergence structured-consensus
assess feasibility/readiness of candidates feasibility-assessment
select a balanced portfolio from candidates portfolio-optimization
verify rejected candidates, stress-test winners steel-manning

Multi-Campaign Orchestration

CC composes campaigns autonomously:

  • Serial: scoring → steel-manning → portfolio
  • Parallel: scoring + pairwise → take intersection
  • Backtrack: steel-manning rejects → re-enter scoring
  • Nested: consensus determines weights → scoring uses those weights
  • Skip: if only 3 candidates with clear criteria, pairwise alone suffices

📦 Manifest

Campaign Strategies Tactics SOPs
multi-criteria-scoring 5 3 10
pairwise-ranking 5 3 9
structured-consensus 5 3 10
feasibility-assessment 5 3 10
portfolio-optimization 5 3 10
steel-manning 5 3 9
Total 30 18 58

Plus 3 shared SOPs (saturation-detection, sensitivity-analysis, multi-stakeholder-simulation) and 5 import SOPs (web-search, web-research, paper-overview, paper-search, paper-research).


🔌 Dependencies

Dependency What It Provides
web-browsing web-search + web-research (import SOPs)
literature-engine paper-overview + paper-search + paper-research (import SOPs)
subagent-spawning Subagent dispatch conventions
context-management context-init + context-checkpoint
wiki-vault MCP Knowledge persistence to graph

🧪 Testing

# Integration test scenarios (7 end-to-end)
tests/integration-prompt.md

Each scenario validates routing, output structure, budget enforcement, and hard-gate compliance.


📄 License

Apache-2.0

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Universal Convergence Engine — transforms unstructured candidate sets into ranked selections, balanced portfolios, and validated decisions via 6 parallel convergence campaigns

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