# Thinking

> Activate when facing complex problems, multi-step decisions, high-risk changes, complex debugging, or architectural decisions. Activate when careful analysis is needed before taking action. Provides explicit step-by-step validation. Use when this capability is needed.

- Skill: `tomevault-io/thinking-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/thinking-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/thinking-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/thinking-2

---


# Thinking Skill

Structured problem-solving through explicit step-by-step analysis.

## When to Use

- Decisions are complex or multi-step
- Changes are high-risk or irreversible
- Debugging requires systematic exploration
- Architectural decisions with tradeoffs
- Planning before significant implementation

## Core Guidance

- **Break problems into explicit steps** - Don't jump to conclusions
- **Validate assumptions before acting** - Question what you think you know
- **Prefer planning before execution** - Map the approach first
- **Document reasoning** - Make the thought process visible

## Decision Matrix

### Work Triggers (require planning)
- Action verbs: implement, fix, create, deploy
- @Role work: "@Developer implement X"
- Continuation: testing after implementation

### Information Patterns (direct response)
- Questions: what, how, why, status
- @Role consultation: "@PM what story next?"

### Context Evaluation
- **Simple**: Single question, surface-level → direct response
- **Complex**: Multi-component, system-wide impact → use thinking

## Thinking Process

1. **Identify the problem** - What exactly needs to be solved?
2. **Gather context** - What information is relevant?
3. **List options** - What approaches are possible?
4. **Evaluate tradeoffs** - What are pros/cons of each?
5. **Select approach** - Which option best fits constraints?
6. **Plan execution** - What are the steps to implement?
7. **Identify risks** - What could go wrong?
8. **Define validation** - How will success be measured?

## Memory Integration (AUTOMATIC)

### Before Analysis
```bash
# Search for similar problems solved before
node ~/.claude/skills/memory/cli.js search "relevant problem keywords"

IF similar analysis found:
  - Review the approach
  - Adapt or reuse patterns
  - Note differences in context
```

### After Significant Analysis
```bash
# Store valuable analysis patterns
node ~/.claude/skills/memory/cli.js write \
  --title "Analysis: <problem type>" \
  --summary "<approach that worked, key tradeoffs>" \
  --tags "analysis,<domain>" \
  --category "patterns" \
  --importance "medium"
```

This is **SILENT** - builds knowledge for future analysis without user notification.

## Sequential Thinking MCP Tool

For complex analysis, use the `mcp__sequential-thinking__sequentialthinking` tool:
- Break into numbered thoughts
- Allow revision of previous thoughts
- Support branching for alternative approaches
- Track hypothesis generation and verification

---
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<!-- tomevault:4.0:skill_md:2026-04-11 -->