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Meta-orchestrator that selects optimal reasoning patterns based on problem characteristics. Analyzes 11 dimensions and recommends ToT, BoT, SRC, HE, AR, DR, AT, RTR, or NDF patterns.
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| name | integrated-reasoning-v2 |
| description | Meta-orchestrator that selects optimal reasoning patterns based on problem characteristics. Analyzes 11 dimensions and recommends ToT, BoT, SRC, HE, AR, DR, AT, RTR, or NDF patterns. |
| metadata | {"clawdbot":{"requires":{"env":"[Truncated]"}}} |
| user-invocable | true |
| homepage | https://github.com/anthropics/claude-code |
Meta-orchestration guide for choosing optimal reasoning patterns. Analyzes problem characteristics and recommends which cognitive methodology to use.
Invoke when facing complex problems and unsure which reasoning approach fits best. IR-v2 scores 11 dimensions and selects the optimal pattern.
| Pattern | Best For | Key Strength |
|---|---|---|
| ToT (Tree of Thoughts) | Find THE best among known options | Systematic evaluation |
| BoT (Breadth of Thought) | Explore ALL possible approaches | Exhaustive coverage |
| SRC (Self-Reflecting Chain) | Step-by-step with validation | Error correction |
| HE (Hypothesis-Elimination) | Find root CAUSE of issues | Diagnostic precision |
| AR (Adversarial Reasoning) | Stress-test solutions | Robustness validation |
| DR (Dialectical Reasoning) | Synthesize opposing views | Trade-off resolution |
| AT (Analogical Transfer) | Novel problems, no precedent | Creative solutions |
| RTR (Rapid Triage Reasoning) | Time-critical decisions | Speed optimization |
| NDF (Negotiated Decision Framework) | Multi-stakeholder alignment | Consensus building |
"I need the BEST option" → ToT
"I need ALL options" → BoT
"I need to trace step by step" → SRC
"I need to find THE CAUSE" → HE
"I need to VALIDATE a solution" → AR
"I'm stuck between two approaches" → DR
"This is completely novel" → AT
"I need to decide NOW" → RTR
"Multiple stakeholders must agree" → NDF
Before selecting a pattern, score these dimensions:
ToT = (CriteriaClarity × 0.35) + (SingleAnswer × 0.30) + (SolutionSpaceKnown × 0.20) + (SequentialDeps × 0.15)
BoT = (1-SingleAnswer × 0.35) + (ProblemNovelty × 0.30) + (1-CriteriaClarity × 0.20) + (SequentialDeps × 0.15)
SRC = (SequentialDeps × 0.45) + (CriteriaClarity × 0.25) + (EvidenceAvailable × 0.20) + (RobustnessRequired × 0.10)
HE = (EvidenceAvailable × 0.40) + (CriteriaClarity × 0.30) + (SequentialDeps × 0.20) + (RobustnessRequired × 0.10)
AR = SolutionExists >= 3 ? (RobustnessRequired × 0.45) + (EvidenceAvailable × 0.25) + (CriteriaClarity × 0.20) + (1-TimePressure × 0.10) : 0
DR = (OpposingValidViews × 0.50) + (CriteriaClarity × 0.20) + (1-SingleAnswer × 0.15) + (1-TimePressure × 0.15)
AT = (ProblemNovelty × 0.45) + (1-SolutionSpaceKnown × 0.30) + (1-CriteriaClarity × 0.15) + (EvidenceAvailable × 0.10)
RTR = (TimePressure × 0.50) + (CriteriaClarity × 0.25) + (RobustnessRequired × 0.15) + (SequentialDeps × 0.10)
NDF = StakeholderComplexity >= 3 ? (StakeholderComplexity × 0.50) + (OpposingValidViews × 0.25) + (1-TimePressure × 0.15) + (CriteriaClarity × 0.10) : 0
When top 2 patterns score within 0.3 of each other:
User: "Should we use microservices or monolith for our new app?"
IR-v2 Analysis:
- Sequential Dependencies: 2 (independent evaluation)
- Criteria Clarity: 3 (some clear, some subjective)
- Solution Space Known: 5 (two options)
- Single Answer Needed: 5 (must pick one)
- Opposing Valid Views: 4 (both have merit)
Top Patterns:
1. DR = 3.85 (opposing valid views present)
2. ToT = 3.60 (clear options to evaluate)
Recommendation: Use DR to synthesize trade-offs, then ToT to score final decision.
When invoked, provide:
Self-improving agent architecture using ChromaDB for continuous learning, self-evaluation, and improvement storage. Agents maintain separate memory collections for learned patterns, performance metrics, and self-assessments without modifying their static .md configuration.
Guide for manually creating custom skills from scratch with templates and validation. Use when designing NEW skills with specific requirements. For auto-generating skills from existing git repos, use /generate-skills instead.
Display QAVR (Q-Value Augmented Vector Retrieval) system status including mode, interaction counts, top memories by Q-value, and configuration.