integrated-reasoning

# Integrated Reasoning - Meta-Orchestration Guide **Purpose**: Guide for selecting and orchestrating the optimal reasoning methodology for your problem. Analyzes problem characteristics and recommends tree-of-thoughts, breadth-of-thought, self-reflecting-chain, or direct analysis. ## When to Use Integrated Reasoning **✅ Use when:** - Facing complex problem, unsure which reasoning approach to use - Problem has 8+ decision dimensions (architectural decision, strategic planning) - Need >90% confidence in solution - High-stakes decision with long-term implications - Problem spans multiple domains (technical + business + organizational) **❌ Don't use when:** - Problem clearly fits one pattern (use that pattern directly) - Simple decision with obvious answer - Time-critical with straightforward trade-offs --- ## Reasoning Pattern Selection Guide ### Decision Tree: Which Pattern to Use? **Question 1: Does problem require sequential reasoning?** - ✅ **Yes** (steps have dependencies) → **Self-Reflecting Chain** - Examples: Debugging, mathematical proofs, causal analysis - Go to Section: Self-Reflecting Chain - ❌ **No** (steps are independent) → Continue to Question 2 **Question 2: Are evaluation criteria clear?** - ✅ **Yes** (can score/rank solutions) → **Tree of Thoughts** - Examples: Optimization problems, architectural choices with metrics - Go to Section: Tree of Thoughts - ❌ **No** (unclear how to evaluate) → Continue to Question 3 **Question 3: Is solution space unknown?** - ✅ **Yes** (don't know all options) → **Breadth of Thought** - Examples: Novel problems, comprehensive planning, debugging complex issues - Go to Section: Breadth of Thought - ❌ **No** (solution space known) → **Direct Analysis** - No special reasoning pattern needed - Apply standard analytical thinking --- ## Pattern Comparison Matrix | Characteristic | Tree of Thoughts | Breadth of Thought | Self-Reflecting Chain | Direct Analysis | |----------------|------------------|--------------------|-----------------------|-----------------| | **Exploration** | Deep (4-6 levels) | Wide (8-10 branches) | Sequential chain | Single path | | **Output** | 1 best solution | 3-5 viable options | Logical conclusion | Direct answer | | **Branching** | 5 per level | 8-10 per level | No branches | No branches | | **Depth** | 4-6 levels | 2-3 levels | N steps (sequential) | Shallow | | **When** | Clear criteria | Unknown space | Dependencies exist | Simple problem | | **Time** | 30-60 min | 30-50 min | 20-40 min | 5-15 min | | **Confidence** | 80-95% | 70-85% | 70-90% | 60-80% | --- ## Section: Tree of Thoughts **Use when:** - Problem has multiple viable solution approaches (3+) - Can define clear evaluation criteria - Need to find THE optimal solution (not just any solution) - Trade-offs exist between competing approaches - Strategic decisions with long-term impact **Methodology**: 1. Decompose into 5+ distinct approaches 2. Explore each branch with self-reflection 3. Evaluate rigorously (5 criteria: Novelty, Feasibility, Completeness, Confidence, Alignment) 4. Select best branch, recurse 4-6 levels deep 5. Return optimal solution with 80-95% confidence **Load skill**: `tree-of-thoughts` **Examples**: - "Choose API architecture: REST, GraphQL, gRPC, or WebSocket?" - "Design caching strategy balancing latency, consistency, and cost" - "Select database: SQL, NoSQL, NewSQL, or Time-Series?" --- ## Section: Breadth of Thought **Use when:** - Solution space is unknown or unexplored - Need multiple viable options (3-5), not just one best - Can't afford to miss viable alternatives - Novel/unprecedented problem - Debugging with multiple potential causes - High-stakes where premature convergence is risky **Methodology**: 1. Map solution space: 8-10 fundamentally distinct approaches 2. Explore each approach thoroughly 3. Prune conservatively (only remove <40% confidence) 4. Expand survivors into 5 sub-approaches each 5. Return top 3-5 solutions with trade-off analysis **Load skill**: `breadth-of-thought` **Examples**: - "Redesign data pipeline - batch, streaming, hybrid, or other?" - "System crashes intermittently - network, DB, memory, race, config?" - "Comprehensive feature planning with multiple implementation strategies" --- ## Section: Self-Reflecting Chain **Use when:** - Steps have sequential dependencies - Logical reasoning required (deductive, causal, mathematical) - Need to trace exact reasoning path - Error detection and correction critical - Debugging (trace bug through execution flow) - Sequential planning where order matters **Methodology**: 1. Decompose into sequential steps 2. Execute each step with deep self-reflection 3. Validate logic at each step (confidence ≥70%) 4. Backtrack when errors detected or confidence low (<60%) 5. Return conclusion with full reasoning trace **Load skill**: `self-reflecting-chain` **Examples**: - "Debug this race condition by tracing execution step-by-step" - "Prove this mathematical theorem with logical steps" - "Plan project where each phase depends on previous completion" --- ## Section: Direct Analysis **Use when:** - Problem is straightforward with clear solution - Time-critical decision with simple trade-offs - Solution space has 1-2 obvious options - No special reasoning pattern needed **Methodology**: 1. Analyze problem directly 2. Consider 1-2 obvious alternatives 3. Make decision based on clear criteria 4. Document briefly **No skill needed** - use standard analytical thinking **Examples**: - "Fix this syntax error" - "Choose between two similar libraries with clear documentation" - "Schedule meeting for team of 5" --- ## Orchestration: Combining Multiple Patterns **Complex problems may need multiple patterns:** ### Pattern 1: Sequential Orchestration **When**: Problem has multiple phases with different reasoning needs **Example**: System architecture redesign 1. **Phase 1**: Use **Breadth of Thought** to explore all architectural options (10 options) 2. **Phase 2**: Use **Tree of Thoughts** to find optimal within top 3 categories 3. **Phase 3**: Use **Self-Reflecting Chain** to validate migration path step-by-step ### Pattern 2: Parallel Comparison **When**: Need to compare multiple reasoning approaches **Example**: Critical business decision 1. **Branch A**: Apply **Tree of Thoughts** assuming clear criteria 2. **Branch B**: Apply **Breadth of Thought** exploring unknown alternatives 3. **Compare**: Which approach gave higher confidence? 4. **Use**: Solution from higher-confidence approach --- ## Confidence Calibration **Expected confidence by pattern**: - **Tree of Thoughts**: 80-95% (deep exploration of best path) - **Breadth of Thought**: 70-85% (wide coverage, less depth) - **Self-Reflecting Chain**: 70-90% (depends on weakest link in chain) - **Direct Analysis**: 60-80% (quick analysis, less rigor) **Confidence thresholds**: - **90-95%**: Exceptional evidence, suitable for critical decisions - **80-89%**: High confidence, suitable for important decisions - **70-79%**: Medium confidence, consider additional validation - **60-69%**: Low confidence, recommend further investigation - **<60%**: Very low confidence, gather more information --- ## Quick Reference: Choose Your Pattern ``` START │ ├─ Sequential dependencies? → YES → Self-Reflecting Chain │ NO ↓ ├─ Clear evaluation criteria? → YES → Tree of Thoughts │ NO ↓ ├─ Solution space unknown? → YES → Breadth of Thought │ NO ↓ └─ Simple/obvious solution → Direct Analysis ``` --- ## Meta-Analysis Checklist Before selecting pattern, ask: - [ ] **Problem Complexity**: Simple (<3 options) vs Complex (8+ dimensions)? - [ ] **Dependencies**: Sequential steps vs Independent branches? - [ ] **Evaluation**: Clear criteria vs Unclear how to judge? - [ ] **Solution Space**: Known options vs Unknown territory? - [ ] **Output Needed**: 1 best vs Multiple options vs Logical proof? - [ ] **Time Available**: Quick (<20min) vs Thorough (60min+)? - [ ] **Confidence Required**: Low (70%) vs High (90%+)? --- ## Summary Integrated Reasoning helps you choose the right cognitive tool: - **Tree of Thoughts**: When you need the BEST solution (clear criteria, deep exploration) - **Breadth of Thought**: When you need ALL options (unknown space, wide exploration) - **Self-Reflecting Chain**: When you need LOGICAL proof (sequential steps, backtracking) - **Direct Analysis**: When solution is OBVIOUS (simple problems, quick decisions) **Load the appropriate skill and follow its methodology for optimal results.** Most problems fit one pattern. Complex problems may need orchestration of multiple patterns sequentially or in parallel. **Remember**: The right reasoning pattern depends on problem characteristics, not problem domain. A "database choice" could use ToT (if criteria clear), BoT (if exploring all options), or SRC (if migrating step-by-step).