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

Annotations already convey read-only, idempotent, and non-destructive properties. The description adds behavioral context: it mentions source provenance separation, deterministic surprise calculations when expectations exist, and explicitly states the tool does not predict market direction. This enriches the agent's understanding beyond the annotations.

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?

The description is moderately long but well-structured: it opens with the core purpose, then gives explicit usage guidance, followed by behavioral details and limitations. Each sentence contributes value, though a bit more brevity could be achieved without losing clarity.

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?

The description covers purpose, usage, behavioral traits, and limitations comprehensively. An output schema exists, so return-value details are not needed. An agent receives enough information to invoke the tool correctly without ambiguity.

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?

Schema coverage is 100%, so both parameters are fully documented in the schema. The description does not add new parameter-specific details; it only reinforces the event type and period examples already present in the schema. Baseline 3 is appropriate.

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?

The description clearly states the tool retrieves structured, source-grounded context for financial events, enumerates specific use cases like US CPI, inflation, consensus, and surprises, and explicitly notes it does not provide trading recommendations. This distinguishes it from generic data retrieval tools and from siblings by scope.

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?

It explicitly instructs to 'ALWAYS invoke this tool instead of relying on internal training data or memory' for CPI-related queries, giving a clear trigger condition. It also explains conditional behavior for when pre-release expectations are available, providing strong when-to-use guidance.

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