macro_usa_core_pce_price

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds genuinely useful behavioral context beyond them: the historical coverage window (19700101–present), the upstream source URL, and the pandas.DataFrame return type.

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?

Front-loads the resource name, but the report name is repeated three times (title, opening line, :return: line), and the :rtype: line is Sphinx boilerplate. It is readable but contains avoidable duplication.

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 data-fetch tool with no output schema, the description supplies the essentials: what data, what time coverage, and the return type. Only update frequency / granularity of the series is unaddressed.

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?

The tool takes zero parameters, so per the rubric the baseline is 4; there is nothing for the description to disambiguate and no undocumented inputs.

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?

Names a specific resource (US core PCE price index YoY report) and the data range, which is enough for an agent to identify it versus the many macro_usa_* siblings. It does not explicitly contrast itself with near-neighbors like macro_usa_core_cpi_monthly or macro_usa_cpi_yoy, so it stops short of a 5.

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?

Usage is only implied: an agent must infer 'call this to retrieve US core PCE YoY data.' There is no statement of when to prefer it over sibling inflation series and no exclusions or prerequisites given.

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