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cody-aigov
by cody-aigov

ai_safety_screen

Evaluate AI system prompts for safety risks using SAF-001 and SAF-002 controls, returning a structured analysis for the host to complete.

Instructions

Screen an AI system's configuration for safety risks (SAF-001).

Evaluates a system prompt against the SAF-002 output validation control. Returns a structured analysis framework for the host to complete.

Args: system_prompt: The system prompt or configuration to screen. context: Optional deployment context (e.g. "customer-facing chatbot for a bank").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
system_promptYes
contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that it evaluates against SAF-002 and returns a framework for the host to complete, but does not detail the evaluation process, side effects, or whether it runs actual checks. No annotations were provided to supplement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus a clean Args block. Efficient but could condense further. Information is well front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists, description does not need to detail return format. Covers core behavior and parameters. Could elaborate on output usage or integration with other safety tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description includes an Args section explaining both parameters (system_prompt and context) with practical examples, adding meaning beyond the schema which only provides titles and types. Schema coverage is effectively 100% via description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool screens an AI system's configuration for safety risks (SAF-001) and evaluates a system prompt against a control. Differentiates from siblings (ai_red_team, ai_risk_classify) by focusing on prompt screening versus red teaming or risk classification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage for safety screening but does not explicitly specify when to use this tool versus siblings. Lacks 'when-not-to-use' instructions or conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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