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

The readOnly/idempotent/non-destructive annotations already establish the safety profile, so the description's job is to add operational context. It contributes real value by disclosing the cost ('Costs 1 credit') and that ECB values are returned exactly as published, but says nothing about pagination behavior or return shape beyond what the schema implies.

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?

One dense sentence front-loads the core purpose and packs the platform variations and cost without filler. It is efficient, though the parenthetical enumeration makes it slightly hard to scan for a quick read.

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, and the tool has a nested filters object plus a required platform enum, so the description carries meaningful burden. It covers platform-specific filter semantics and cost well; the main gap is it does not explain the filters object relationship (that it should mirror data_list_sources) beyond the schema's own hint.

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 80%, so the baseline is 3. The description does add some meaning beyond the schema by clarifying that 'from'/'to' are years for World Bank but dates for ECB and that GDELT uses q + measure + timespan, though it never names these as parameters explicitly.

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 and resource ('Get a time series') and enumerates the three data platforms it serves (World Bank, ECB, GDELT), which lets an agent recognize it as the series-fetch tool distinct from data_get/data_get_author. It stops short of explicitly contrasting itself with those siblings, so it lands at a clear-but-not-differentiating 4.

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?

The description gives per-platform selection context (World Bank takes country/indicator with years, ECB takes a quote filter with dates, GDELT takes q plus a measure and timespan), which is exactly the routing guidance an agent needs when choosing how to call it. It offers no explicit when-not-to-use or named alternative (e.g. data_get / data_list_sources), so it is contextual rather than fully prescriptive.

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