Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Spontaneity tuning: gate 1.5->1.0, baseline 2.0->1.5, threshold 10->6. First spontaneous event in ~16-24h instead of ~80h
What This Skill Does
Prioritized action selection engine for AI agents using 10 configurable needs with time-decay and tension scoring. Each cycle calculates which needs are most deprived and selects concrete actions ranked by urgency. Replaces idle heartbeat loops with a decision framework that adapts to agent state over time.
Instead of polling for tasks or waiting for user input, agents get a ranked action list derived from measurable deprivation levels, decay curves, and cross-need cascades.
When to use it
- Running an AI agent on a regular heartbeat schedule with meaningful next steps
- Preventing an autonomous agent from cycling without purpose between tasks
- Tuning an agent's priorities for research-focused versus social-facing work
- Auditing what actions an agent took and why over the past week
- Detecting when a low-priority need has been neglected for too long
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Run the Turing Pyramid cycle for my agent
- 1Reads current satisfaction values from assets/needs-state.json
- 2Applies time-decay to each need based on hours elapsed and the configured day/night multiplier
- 3Calculates tension scores (importance × (3 - satisfaction)) for all 10 needs
- 4Selects highest-tension needs using probability tables and impact range matrices
- 5Outputs ranked action suggestions with mark-satisfied.sh commands for each
A prioritized list of 2-3 concrete actions with tension scores, impact values, and follow-up mark-satisfied commands
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.