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scaffold_policy

Generate a CSL policy scaffold from a plain-English description, producing a ready-to-edit .csl template with CONFIG, DOMAIN, VARIABLES, and placeholder constraints.

Instructions

Generate a CSL policy scaffold from a description.

Returns a ready-to-edit .csl template with CONFIG, DOMAIN, VARIABLES, and placeholder constraints.

Common CSL patterns: WHEN amount > 1000 THEN role MUST BE "ADMIN" WHEN risk_score > 0.8 THEN action MUST NOT BE "TRANSFER" ALWAYS True THEN tool MUST NOT BE "DELETE" WHEN user_age < 18 AND category == "ALCOHOL" THEN allowed MUST BE "NO"

Variable types: amount: 0..100000 (integer range) role: {"ADMIN", "USER"} (enum / string set) score: 0..1 (numeric range)

Args: domain_name: Name for the policy domain (e.g., "PaymentGuard", "AgentSafety"). description: Plain-English description of what the policy should enforce. variables: Optional comma-separated variable hints (e.g., "amount, role, risk_score").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domain_nameYes
descriptionYes
variablesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It explains the output (ready-to-edit .csl template) and non-destructive nature, but does not explicitly confirm idempotency or absence of side effects.

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?

Well-structured with front-loaded purpose, followed by output description, common patterns, variable types, and parameters. Slightly verbose but each section adds value.

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?

Covers purpose, parameters, output, and provides usage examples. Given complexity (3 params, no annotations, but output schema exists), the description is sufficiently complete for an AI agent.

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?

Schema coverage is 0%, so description compensates well. Provides examples and clarifies each parameter: domain_name and description get context, variables is described as 'optional comma-separated variable hints' with examples.

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?

Description clearly states 'Generate a CSL policy scaffold from a description' with specific verb, resource, and scope. It distinguishes from siblings like explain_policy and verify_policy by emphasizing scaffold creation.

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

Usage Guidelines4/5

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

Includes common CSL patterns and variable types but does not explicitly state when to use this tool over alternatives, such as for creating new policies versus modifying or verifying existing ones.

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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