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

No annotations are provided, so the description carries the full behavioral burden. It does describe the shape of the returned records (ids, unit, level, periods, source table, caveats) and the coverage window (YYYY-MM from 2024-01, base 2022=100), which is genuinely useful. However, it never states that this is a side-effect-free read, whether results are paginated or filtered, or anything about caching/limits, leaving inference to the agent for a listing endpoint.

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-loaded with purpose and return shape, then the routing sentence closes it out. The indicator enumeration is long and somewhat run-on, but each item earns its place by telling the agent which series are discoverable rather than anything irrelevant.

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?

There is no output schema, so the description must describe return content itself, and it does so thoroughly: field-by-field composition of each indicator record plus the period/base-year conventions. Combined with the explicit next-step routing, an agent has everything needed to call this and act on the result.

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 there is nothing for the description to disambiguate at the argument level. Baseline 4 applies. It does helpfully note which indicator coverage exists (TPT, IPM, wages, GRDP per capita, inflation/cpi variants), which functions as latent selector knowledge for the follow-up calls.

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 names a specific resource (BPS regional statistics indicators) and enumerates exactly what each entry carries: indicator id, unit, level, periods, source table and caveats. It also names the sibling tools it complements (get_stat_values, get_stat_series), so an agent can distinguish it without opening any schema.

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?

Explicit sequencing guidance: 'Start here, then call get_stat_values or get_stat_series.' The condition for using this tool (discovery of available indicators) versus the follow-up value-fetching tools is stated outright.

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