sequential-thinking

name	sequential-thinking
version	1.0.0
description	[AI & Tools] Use when you need to apply structured, reflective problem-solving for complex tasks requiring multi-step analysis, revision capability, and hypothesis verification.
license	MIT

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.

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

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.

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.

MUST ATTENTION apply critical + sequential thinking — every claim needs appropriate traced evidence (file:line for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence.

MUST ATTENTION apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting

IMPORTANT MUST ATTENTION — Protocols in force (concise digest of the SYNC/shared blocks this skill carries):

• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.
• Critical Thinking: critical+sequential thinking; traced file:line proof, confidence >80% to act.

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.