Deep Analysis — Structured Reasoning Engine

Multi-step reasoning through the sequential-thinking MCP server. Decomposes complex problems into discrete thinking steps with branching, revision, and hypothesis verification.

When to Use

• Architectural decisions with multiple valid approaches

• Performance diagnosis where the bottleneck is unclear

• Technology selection requiring trade-off evaluation

• Complex debugging (use /investigate for full root cause protocol)

• System design with many interconnected parts

• Migration strategies with risk assessment

Do NOT use for: Simple lookups, straightforward implementations, well-established patterns, or tasks where the answer is obvious.

Protocol

1. Frame the Problem

Start the sequential-thinking chain with a clear problem statement and all known constraints.

mcp__sequential-thinking__sequentialthinking({ thought: "PROBLEM: <clear statement>. CONSTRAINTS: <known limits>. Let me decompose this...", thoughtNumber: 1, totalThoughts: 10, // Initial estimate — adjust as needed nextThoughtNeeded: true })

2. Reason Through Steps

Each thought builds on the previous. Adjust totalThoughts up or down as understanding deepens.

mcp__sequential-thinking__sequentialthinking({ thought: "Step 2: Analyzing option A. Strengths: ... Weaknesses: ...", thoughtNumber: 2, totalThoughts: 10, nextThoughtNeeded: true })

3. Branch When Alternatives Exist

Explore competing approaches without losing the main thread.

mcp__sequential-thinking__sequentialthinking({ thought: "BRANCH: What if we use approach B instead? Let me evaluate...", thoughtNumber: 5, totalThoughts: 12, nextThoughtNeeded: true, branchFromThought: 3, branchId: "approach-B" })

4. Revise When Evidence Changes

Don't force a conclusion — revise earlier thinking when new evidence contradicts it.

mcp__sequential-thinking__sequentialthinking({ thought: "REVISION: My assumption in step 3 was wrong. Evidence shows X instead of Y...", thoughtNumber: 7, totalThoughts: 14, nextThoughtNeeded: true, isRevision: true, revisesThought: 3 })

5. Conclude with Verification

Final thought must verify the conclusion against the original problem and constraints.

mcp__sequential-thinking__sequentialthinking({ thought: "CONCLUSION: Approach A is recommended because [evidence]. Verified against constraints: [check]. Risks: [list].", thoughtNumber: 10, totalThoughts: 10, nextThoughtNeeded: false })

Key Parameters

Parameter Type Purpose

thought

string Current reasoning step

thoughtNumber

int Current step (1-based)

totalThoughts

int Estimated total steps (adjustable)

nextThoughtNeeded

bool false only when truly done

isRevision

bool Revising a previous thought

revisesThought

int Which thought number to revise

branchFromThought

int Branching point for alternatives

branchId

string Label for the branch

needsMoreThoughts

bool Need more steps than estimated

Thinking Budget

• Up to 31,999 tokens per reasoning chain

• Typical analyses: 8-15 steps

• Adjust totalThoughts dynamically — don't force exactly N steps

• Balance depth vs response time

Integration with Other Skills

Situation Use

Bug with unknown root cause /investigate (calls deep-analysis in Phase 4)

Multi-step implementation goal /execute (may call deep-analysis for complex sub-tasks)

Architecture decision only /deep-analysis directly

Trade-off evaluation only /deep-analysis directly

References

• Reasoning Patterns — hypothesis testing, design space exploration, root cause templates

• Integration Guide — pairing with agents and other skills