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

While annotations declare readOnlyHint=true and destructiveHint=false, the description adds valuable behavioral context beyond those: it warns that stale/partial/unavailable coverage rows are not suitable for real-time analysis, lists supported currencies, and clarifies that output is slug strings for downstream calls. No contradiction 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 three sentences, front-loaded with purpose, then guidance, then supported currencies. It is slightly dense but every sentence earns its place. It does not repeat schema details, staying efficient.

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?

Given the presence of a detailed input schema and output schema, the description covers usage flow, coverage caveats, and supported currency scope. It does not explain return values (covered by output schema) but provides sufficient context for agent decision-making. The only minor gap is not mentioning pagination or large result size, but this is not critical for a catalogue listing tool.

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 input schema already provides 100% coverage with detailed descriptions, examples, and defaults for all four parameters. The description adds only marginal parameter-related semantic value, mainly the emphasis on checking the 'coverage' field, but this is more usage guidance than parameter semantics. Baseline 3 is appropriate.

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 opens with a specific verb and resource: 'List every macroeconomic indicator FXMacroData publishes for a currency', and immediately names the metadata fields (units, frequency, coverage/freshness). It further distinguishes itself from siblings by explicitly naming downstream tools (indicator_query, release_calendar, indicator_visual_artifact) which helps disambiguate it from those alternatives.

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 provides explicit instruction on when to invoke: 'ALWAYS call this first when the user asks about a country's macro data'. It also provides conditional guidance for using coverage data before calling indicator_query, and states which tools to pass the returned slugs to. This is a textbook example of when-to-use vs alternatives.

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