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

Annotations already declare the tool read-only and idempotent; the description supplements this with the data source, quarterly cadence, typical publication lag, verified latest observation, and units. This gives the agent valuable context about data freshness and provenance beyond the safety profile.

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 dense but every sentence earns its place: data scope, breakdowns, source, cadence, lag, verified latest value, and units. It is front-loaded with the core resource and delivers supporting context efficiently.

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 read-only, single-parameter tool with no output schema, the description provides all necessary operational context: source, time span, frequency, lag, units, and sector breakdowns. An agent can invoke it correctly and assess data suitability without further clarification.

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 schema description covers the only parameter fully (quarters: default 8, max 40). The description adds that data is quarterly and notes the lag, which helps interpret the quarter parameter, but it does not add syntactic or formatting details beyond the schema.

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 clearly identifies the specific data product (China's gross external debt position by sector from SAFE), details the breakdowns by maturity and institutional sector, and specifies units and time span. This goes well beyond the tool name and distinguishes it from siblings like china_balance_of_payments and china_fx_reserves by subject matter.

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 provides clear context for when to use this tool (when external debt data by sector is needed) and includes cadence and lag details that help an agent assess relevance. It does not explicitly list alternatives or exclusions, but the focused scope makes the intended use obvious.

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