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explain_policy

Parse CSL policies to generate structured Markdown summaries showing domains, variables, constraints, and configurations for AI safety analysis.

Instructions

Parse a CSL policy and return a structured Markdown summary.

Shows: domain name, all variables with types/ranges, all constraints with triggers and actions, and configuration settings. Does NOT compile or verify — use verify_policy for that.

Args: csl_content: The complete CSL policy source code as a string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csl_contentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by describing the tool's behavior: it parses and returns a structured Markdown summary, listing exactly what it shows (domain name, variables, constraints, settings) and clarifying it doesn't compile or verify. However, it doesn't mention potential limitations like error handling or performance characteristics.

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

Conciseness5/5

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

The description is perfectly structured and concise: purpose statement first, followed by what it shows, what it doesn't do with alternative, and parameter explanation. Every sentence earns its place with zero waste.

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

Completeness5/5

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

Given the tool's moderate complexity, no annotations, but the presence of an output schema, the description is complete enough: it explains the tool's purpose, usage guidelines, behavior, and parameter meaning. The output schema will handle return value documentation, so the description appropriately focuses on other aspects.

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?

With 0% schema description coverage, the description compensates well by explaining the single parameter's purpose: 'The complete CSL policy source code as a string.' This adds crucial semantic meaning beyond the bare schema, though it doesn't specify format requirements or constraints.

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?

The description clearly states the tool's purpose with specific verbs ('parse', 'return') and resource ('CSL policy'), explicitly distinguishing it from sibling tools by stating what it does NOT do (compile or verify) and naming the alternative tool (verify_policy).

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool vs alternatives: it states 'Does NOT compile or verify — use verify_policy for that', clearly indicating when not to use this tool and naming the specific alternative for verification tasks.

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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