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

With no annotations, the description carries the full burden. It usefully discloses a data-quality behavior (unreliable publisher values withheld, raw_value retained) and that reference periods and publishing schedules vary, which is real behavioral context beyond the schema. It does not cover auth requirements, pagination via limit, or what 'reviewed' guarantees, so coverage is only partial.

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 resource list is front-loaded, but two dense sentences carry heavy jargon ('observation-bound evidence', 'national qualifiers', 'complete geography cohort') that slows parsing. It is not bloated but it is not tightly economical either.

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 12-parameter tool with no annotations and no output schema, the description covers the primary access modes but leaves many parameters and return-shape expectations unaddressed. It is minimally adequate rather than complete.

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 only 17% (just as_of and revision documented), so the description must compensate. It adds meaning for catalog, series_id, latest, and geo (browse vs cohort vs history), but says nothing about from, to, limit, format, recorded, or generation, leaving roughly half the parameters unexplained across both sources.

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 verb (Read) and concrete resources (reviewed GDP, inflation, jobs, trade, production, energy, credit packs), so the agent knows this retrieves reviewed economic data. It is clear on its own, but it does not explicitly differentiate itself from siblings like get_series_data or search_data, leaving the boundary to inference.

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 describes two operating modes (catalog=true to browse, or a series_id with latest/geo for retrieval), which is useful implied usage. However, it never names an alternative sibling or states which condition should route the agent elsewhere, so the when-not guidance is absent.

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