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

Annotations declare readOnlyHint, idempotentHint, openWorldHint=false, destructiveHint=false, covering safety. The description adds that this is a prerequisite read step before generating predictions, which is useful sequencing context, but doesn't disclose more (e.g., format, caching, limits).

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

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

Two short sentences, front-loaded with what it returns and followed by when to use it. No waste, though could be slightly more structured.

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

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

For a zero-param read tool with annotations and no output schema, the description covers the main content and the sequencing. It's adequate; no return value details needed since no output schema, but the description could enumerate the fields more clearly.

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

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

Zero parameters, so baseline is 4 per rules. The description doesn't need to cover parameters, and schema coverage is moot.

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

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

States a specific resource being retrieved ('extraction rules, output schema, suite scope and commercial availability') and the verb 'get'. It distinguishes itself from siblings like score_order_batch or list_order_cases, though it doesn't explicitly name alternatives.

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

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

Provides clear timing guidance: 'Read before generating predictions,' which tells the agent when to call it. No explicit exclusions or named alternatives, but the sequencing instruction is concrete.

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