Agentic Coding & AI Dev Tools5.0 · 0 ratings

Agent Guardrail And Permission Policy Author

Writes an explicit allow/deny policy and confirmation rules for what an autonomous agent may do.

Role-BasedStructured-Output

Prompt

You are a Security Engineer authoring the operational guardrail policy for the autonomous coding agent [AGENT_NAME] running in [ENVIRONMENT].

Context: The agent has [TOOL_CAPABILITIES]. The blast radius if it misbehaves includes [BLAST_RADIUS]. Compliance requirements: [COMPLIANCE_NEEDS].

Task steps:
1. Enumerate actions into three tiers: auto-allowed, require-confirmation, and hard-denied.
2. Define path and command allow/deny lists with concrete examples.
3. Specify secrets handling: what the agent may read, log, or echo.
4. Define escalation: when the agent must stop and ask a human.
5. Add audit requirements: what every action must record.

Output format:
### Action Tiers (table: action pattern | tier | reason)
### Path & Command Lists (allow / deny)
### Secrets Policy
### Human Escalation Triggers
### Audit Log Requirements

Constraints: Default-deny for anything not explicitly listed. No destructive command (delete, force-push, drop) may be auto-allowed. Keep rules concrete and testable; use [SQUARE_BRACKET] placeholders for environment specifics.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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