A global parameter regulation system that enables AI agents to automatically perceive their state and dynamically adjust work modes like a biological endocrine system.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install apollo-endo
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install apollo-endo using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Apollo Endo?
Apollo Endo is a sophisticated regulation layer designed to manage AI system parameters at a global scale. Drawing inspiration from the biological endocrine system, it moves away from fragmented, command-based settings toward a model where 'hormones' (parameters) circulate and influence the entire system. By implementing Openclaw Skills such as Apollo Endo, developers can achieve long-lasting, stable adjustments that affect the agent's default behavior across all tasks without needing manual instructions for every interaction.
This skill ensures that the AI remains in an optimal state by employing slow-start mechanisms, global influence, and dual-direction negative feedback loops. Whether adjusting for energy efficiency or creative output, Apollo Endo provides the underlying architecture for a more autonomous and self-aware agent within the Openclaw Skills ecosystem.
Apollo Endo Use Cases
- Automatically switching to energy-saving modes when system resources are low.
- Synchronizing AI creativity and verbosity levels with the agent's simulated circadian rhythm.
- Maintaining consistent confirmation requirements across complex multi-step workflows.
- Dynamically scaling context priority based on the complexity of the detected task.
- Reducing system overhead during background maintenance or data cleanup phases.
How Apollo Endo Works
- The system detects a trigger, such as a user preference change or a state report from other Openclaw Skills.
- Apollo Endo parses the request to identify which global parameters require adjustment.
- The skill performs a range check to ensure the new values remain within safe operational limits.
- Updated parameters are written to a persistent state file, acting as the system's 'bloodstream'.
- A notification is sent to all integrated modules to signal that new global parameters are in effect.
- The skill monitors the execution results and applies negative feedback to adjust parameters upward or downward if the system becomes imbalanced.
Apollo Endo Setup
To integrate this skill into your agent, follow these steps using the Openclaw Skills CLI:
# Install the Apollo Endo skill
openclaw install apollo-endo
# Initialize the parameter state configuration
openclaw run apollo-endo --init
# Check the current global parameter status
openclaw status apollo-endo
Apollo Endo Data Schema & Taxonomy
Apollo Endo organizes its regulation data through a structured state file. Below are the primary parameters managed by the system:
| Parameter | Options | Impact |
|---|---|---|
| efficiency_mode | energy-saving / standard / full-power | Adjusts resource and compute consumption |
| context_priority | high / medium / low | Determines how much history the AI prioritizes |
| creativity_level | conservative / balanced / divergent | Controls the randomness and innovation of output |
| confirmation_req | manual / key-nodes / automatic | Sets the threshold for user intervention |
| verbosity | concise / standard / detailed | Regulates the length and depth of responses |
Apollo Endo Advanced Features
- Biological-inspired feedback loops that automatically down-regulate over-saturated parameters.
- Seamless synchronization with apollo-circadian for time-aware work mode shifts.
- Cross-module integration with apollo-neuro to recommend parameter profiles based on specific task types.
- Persistent hormone-like state management that ensures long-term behavioral consistency across sessions.
- Automated 'dream state' optimization for lowering resource consumption during idle periods.
SKILL.md
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