prompt
FreeTwo-layer permission classifier prompt for safe agent autonomy
FreeFree tier
Inputs: textOutputs: text
About prompt
A specialized system prompt designed to guide AI agents in implementing a two-layer permission classifier for autonomous operation. The prompt, part of the ai-boost/awesome-prompts repository on GitHub, instructs the agent to build a Fast Heuristic Filter (sub-millisecond) for low-risk actions and a Model-Based Risk Classifier (millisecond-scale) for boundary cases, aiming to eliminate confirmation fatigue while preserving safety for destructive or exfiltrative operations. It includes design principles such as deny-by-default heuristics, versioned rules, and continuous threshold tuning using action history and audit logs.
Key Features
Two-layer architecture: Fast Heuristic Filter (sub-millisecond) and Model-Based Risk Classifier (millisecond-scale)
Immediate-block rules for system writes, credential stores, network egress to untrusted domains, bulk deletions
Deny-by-default heuristic design with versioned rules and regression testing on audit logs
Model classifier uses action type, resource scope, reversibility, blast radius, and content sensitivity as input features
Continuous threshold tuning via agent action history, user overrides, and audit logs
Detailed rubric for risk thresholds and escalation paths to human review
Pros & Cons
Pros
- Reduces permission fatigue by automating approval for low-risk actions
- Preserves mandatory human approval for high-risk or irreversible operations
- Two-layer design catches edge cases a single rule set might miss
- Supports continuous improvement through audit logs and user overrides
- Free and open-source, easily integrable into any agent setup
Cons
- Requires careful configuration of heuristic rules and model thresholds to avoid false positives/negatives
- Dependent on the quality of the underlying risk classification model
- May need adaptation for different agent environments or custom tool sets
- Deny-by-default approach may block necessary actions if rules are too restrictive
Best For
Designing safe autonomous agent workflows that auto-approve common low-risk actions (e.g., file reads, git status)Configuring AI coding assistants (like Claude Code) with custom permission levelsBuilding risk-aware agent systems that require human approval only for destructive or exfiltrative operationsExperimenting with two-tier safety architectures for open-source AI agents
FAQ
What is the goal of this prompt?
The prompt instructs an AI agent to design a two-layer permission classifier that lets agents operate quickly on low-risk actions while preserving mandatory human approval for high-risk or irreversible operations. The aim is to eliminate confirmation fatigue without eliminating safety.
How does the two-layer classifier work?
Layer 1 is a fast heuristic filter (sub-millisecond) that passes obviously-safe actions and immediately blocks obviously-unsafe ones using rules like deny-by-default for non-allowlisted categories. Layer 2 is a model-based risk classifier (millisecond-scale) that judges boundary cases using input features such as action type, resource scope, reversibility, blast radius, and content sensitivity.
What are some examples of pass-through rules?
Examples include read operations on files below a size threshold in non-sensitive paths, standard CLI introspection (git status, ls, ps, env — read-only), and tool invocations with no side effects and no network egress.
What actions are immediately blocked?
Immediate-block rules include writes to system directories, credential stores, or SSH keys; network egress to non-allowlisted domains; execution of binaries not in a pre-approved hash list; and bulk deletions above a file-count or size threshold.
Is this prompt free to use?
Yes, the prompt is hosted on GitHub in the ai-boost/awesome-prompts repository, which is publicly available and free to use under open-source terms.