- name
- sequential-thinking
- description
- Structured reasoning through sequential thinking — break complex problems into steps, solve each independently, verify consistency, synthesize conclusions with confidence scoring. Use for complex analysis, debugging, and multi-step reasoning.
- homepage
- https://www.agxntsix.ai
- license
- MIT
- compatibility
- Python 3.10+, OpenRouter API key
- metadata
- {"openclaw": {"emoji": "\�\�", "requires": {"env": ["OPENROUTER_API_KEY"]}, "primaryEnv": "OPENROUTER_API_KEY", "homepage": "https://www.agxntsix.ai"}}
🧩 Sequential Thinking
Structured reasoning through sequential thinking. Break complex problems into logical steps, solve each independently, verify consistency, and synthesize a final answer with a confidence score.
Why Sequential Thinking?
LLMs often rush to conclusions. This skill forces step-by-step decomposition:
- Decompose — Break the problem into discrete steps
- Solve — Address each step independently
- Verify — Check consistency between steps
- Synthesize — Combine into a final answer with confidence
Usage
# Basic sequential reasoning
python3 {baseDir}/scripts/sequential_think.py "What would happen to Earth's climate if the Moon disappeared?"
# Limit to 5 steps
python3 {baseDir}/scripts/sequential_think.py "Design a sustainable city for 1M people" --steps 5
# Enable self-verification
python3 {baseDir}/scripts/sequential_think.py "Is P=NP?" --verify
# Use a specific model
python3 {baseDir}/scripts/sequential_think.py "Explain quantum computing" --model anthropic/claude-sonnet-4
# JSON output
python3 {baseDir}/scripts/sequential_think.py "Compare React vs Vue" --json
# Verbose mode (show all intermediate reasoning)
python3 {baseDir}/scripts/sequential_think.py "Solve this logic puzzle..." --verboseFlags
| Flag | Default | Description |
|---|---|---|
--steps | 7 | Maximum number of reasoning steps |
--verify | off | Enable self-verification pass |
--model | anthropic/claude-sonnet-4 | Model to use |
--json | off | Output structured JSON |
--verbose | off | Show full intermediate reasoning |
--temperature | 0.3 | Temperature for reasoning (lower = more focused) |
Output Format
🧩 Sequential Thinking: "Your question here"
══════════════════════════════════════════
Step 1/5: [Step Title]
→ [Reasoning and conclusion for this step]
Step 2/5: [Step Title]
→ [Reasoning and conclusion for this step]
...
✅ Verification: [Pass/Fail — consistency notes]
📋 Synthesis:
[Final combined answer]
🎯 Confidence: 85% (High)How It Works
- Decomposition prompt asks the model to identify the key sub-questions
- Step-solving prompts address each sub-question with context from prior steps
- Verification prompt (optional) checks for contradictions between steps
- Synthesis prompt combines all step conclusions into a coherent answer
- Confidence scoring based on step agreement, verification results, and hedging language
Credits
Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.
📅 Need help setting up OpenClaw for your business? Book a free consultation