Sequential Thinking

Quick Summary

Goal: Solve complex problems through structured, reflective thought sequences with dynamic adjustment and revision.

Workflow:

1. Estimate — Start with loose thought count, adjust as understanding evolves
2. Structure Thoughts — One aspect per thought; state assumptions and uncertainties
3. Revise/​Branch — Mark revisions of earlier thoughts; branch for alternative approaches
4. Hypothesize & Verify — Generate solution hypothesis, test it, iterate until verified
5. Complete — Mark final only when solution verified and confidence achieved

Key Rules:

• Dynamically expand/​contract thought count as complexity changes
• Explicitly mark revisions with original reasoning and why it changed
• Can apply explicitly (visible markers) or implicitly (internal methodology)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Sequential Thinking

Structured problem-solving via manageable, reflective thought sequences with dynamic adjustment.

When to Apply

• Complex problem decomposition
• Adaptive planning with revision capability
• Analysis needing course correction
• Problems with unclear/​emerging scope
• Multi-step solutions requiring context maintenance
• Hypothesis-driven investigation/​debugging

Core Process

1. Start with Loose Estimate

Thought 1/​5: [Initial analysis]

Adjust dynamically as understanding evolves.

2. Structure Each Thought

• Build on previous context explicitly
• Address one aspect per thought
• State assumptions, uncertainties, realizations
• Signal what next thought should address

3. Apply Dynamic Adjustment

• Expand: More complexity discovered → increase total
• Contract: Simpler than expected → decrease total
• Revise: New insight invalidates previous → mark revision
• Branch: Multiple approaches → explore alternatives

4. Use Revision When Needed

Thought 5/​8 [REVISION of Thought 2]: [Corrected understanding]
- Original: [What was stated]
- Why revised: [New insight]
- Impact: [What changes]

5. Branch for Alternatives

Thought 4/​7 [BRANCH A from Thought 2]: [Approach A]
Thought 4/​7 [BRANCH B from Thought 2]: [Approach B]

Compare explicitly, converge with decision rationale.

6. Generate & Verify Hypotheses

Thought 6/​9 [HYPOTHESIS]: [Proposed solution]
Thought 7/​9 [VERIFICATION]: [Test results]

Iterate until hypothesis verified.

7. Complete Only When Ready

Mark final: Thought N/​N [FINAL]

Complete when:

• Solution verified
• All critical aspects addressed
• Confidence achieved
• No outstanding uncertainties

Application Modes

Explicit: Use visible thought markers when complexity warrants visible reasoning or user requests breakdown.

Implicit: Apply methodology internally for routine problem-solving where thinking aids accuracy without cluttering response.

Scripts (Optional)

Optional scripts for deterministic validation/​tracking:

• scripts/​process-thought.js - Validate & track thoughts with history
• scripts/​format-thought.js - Format for display (box/​markdown/​simple)

See README.md for usage examples. Use when validation/​persistence needed; otherwise apply methodology directly.

References

Load when deeper understanding needed:

• references/​core-patterns.md - Revision & branching patterns
• references/​examples-api.md - API design example
• references/​examples-debug.md - Debugging example
• references/​examples-architecture.md - Architecture decision example
• references/​advanced-techniques.md - Spiral refinement, hypothesis testing, convergence
• references/​advanced-strategies.md - Uncertainty, revision cascades, meta-thinking

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[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

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AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path. Keep domain concepts out of generic/​shared/​infrastructure layers. A reusable layer (shared library, framework, infra module) must reference NO consumer-specific domain concept — tenant/​customer/​product IDs, business entities, feature rules. The leak compiles and runs, so it passes review silently while coupling the "reusable" layer to one consumer. Push domain fields/​logic down into the consumer via subclass or composition.

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Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

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MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

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MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

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Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.