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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds meaningful context: defines core as 'PCE excluding food and energy', explains the Fed's preference for PCE over CPI, and shows the exact return structure in the JSON example. No contradictions with 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 well-organized with a clear lead sentence, contextual explanation, direction on usage, and a compact JSON example. Every sentence adds value, and the structure front-loads the essential definition.

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 parameterless tool with no output schema, the description is fully sufficient. It covers what is returned (headline and core with indices and percent changes), the source URL, and the exact structuredContent format. Sibling differentiation is also addressed. No gaps remain.

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?

With zero parameters, the baseline is 4. The description explicitly states 'Args: none', confirming no inputs are needed. There is no additional parameter information to provide.

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 identifies the tool as returning PCE price index data (headline and core) with YoY and MoM changes, and explicitly distinguishes it from CPI via the 'When NOT to use' section pointing to bls_cpi. The resource and scope are specific and unambiguous.

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 explicit 'When to use' and 'When NOT to use' guidance, naming bls_cpi as the alternative for CPI. This gives clear decision criteria for tool selection.

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