Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Scores every incoming request on complexity dimensions like multi-step logic, ambiguity, and code architecture, then automatically enables extended thinking when the score warrants it. Appends visual indicators (🧠 or 🧠🔥) to signal when reasoning mode is active. Runs silently as a preprocessing step with no user intervention required.
Avoids the manual overhead of toggling reasoning mode by making the decision automatically based on a consistent scoring rubric.
When to use it
- Debugging a race condition in a distributed system
- Designing a caching strategy with conflicting constraints
- Answering a nuanced trade-off question about system architecture
- Quickly responding to simple lookups without wasting tokens
- Auto-downgrading after a complex task when follow-up is trivial
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: 'Debug why this distributed system has race conditions under load'
- 1Score the request on complexity dimensions: multi-step logic (+3), code architecture (+2), high stakes (+1) = score 9
- 2Threshold ≥8 met, activate extended thinking via /reasoning on
- 3Analyze concurrency patterns, shared state, and timing assumptions in the described system
- 4Produce a detailed diagnosis with root causes and remediation steps
- 5Append 🧠🔥 at the end of the response
Detailed race condition analysis with identified root causes and fixes, ending with 🧠🔥