A framework of production-grade behavioral rules designed to instill professional discipline and operational efficiency in any AI agent session.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install operator-discipline
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 operator-discipline 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 Operator Discipline?
Operator Discipline is a foundational set of behavioral standards for AI agents within the Openclaw Skills ecosystem. It transforms standard LLM interactions into production-grade operations by enforcing strict rules on narration, response length, and tool usage. By implementing this skill, developers ensure their agents act with precision, avoiding the chatty anti-patterns often found in default models.
This skill is essential for anyone building reliable, autonomous systems where every token and tool call counts. It provides a structured approach to agent communication, ensuring that actions are performed efficiently and reported only when necessary. By adopting these Openclaw Skills, you create agents that reduce cognitive load for users and maintain high standards of file hygiene and safety.
Operator Discipline Use Cases
- Configuring a new AI agent to follow production standards.
- Auditing existing agents to remove unnecessary narration and filler responses.
- Designing system prompts or SOUL.md files for complex, multi-step workflows.
- Bootstrapping professional behavior in autonomous coding or research tasks.
- Reducing token costs by enforcing selective context loading and effort calibration.
How Operator Discipline Works
- Classify the task difficulty (Simple, Medium, or Hard) to calibrate response effort and length appropriately.
- Apply response discipline by cutting meta-commentary and matching response weight to task importance.
- Perform tool safety checks to ensure actions are reversible and outputs are verified before proceeding.
- Monitor for stuck detection, halting the process if instructions repeat without progress to save resources.
- Execute the Devil's Advocate Protocol on strategic decisions to identify blind spots and unstated assumptions.
- Pass all outputs through a final Quality Gate to ensure they reduce cognitive load and lead to actionable outcomes.
Operator Discipline Setup
To integrate Operator Discipline into your agentic workflow within the Openclaw Skills environment, add the logic to your agent's system prompt or configuration. You can reference the skill using the following command structure:
# Initialize operator-discipline behavioral rules
openclaw skills add operator-discipline
Ensure your agent is configured to internalize the rules for Response Discipline, Effort Calibration, and Safety Defaults defined in the skill documentation.
Operator Discipline Data Schema & Taxonomy
Operator Discipline organizes agent behavior and state using the following taxonomy:
| Component | Description | Metadata/Taxonomy |
|---|---|---|
| Effort Class | Classification of task complexity | Simple, Medium, Hard |
| Stuck Note | Log created when an execution loop is detected | Error state, Instruction count |
| Checkpoint | Incremental state saves during major operations | Operation ID, Session context |
| Safety Gate | Pre-execution validation for tool usage | Read-only vs. Write, Reversibility |
| Quality Gate | Internal verification of response utility | Cognitive load, Outcome alignment |
Operator Discipline Advanced Features
- Stuck Detection: Automatically halts execution and requests guidance after 3+ repeated instructions without new progress.
- Devil's Advocate Protocol: Mandates the identification of potential failure modes and hidden assumptions in strategic planning.
- Token Cost Discipline: Minimizes operational expenses via selective context loading and incremental state checkpointing.
- Quality Gate Verification: A mandatory internal step to ensure every response strengthens user judgment and leads to a usable outcome.
- Safety Defaults: Enforces strict boundaries between internal actions and external, destructive, or private data operations.
SKILL.md
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