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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description goes beyond this by disclosing the output format (a natural-language paragraph plus structured series, FX, derived, and signals fields), which informs the agent about the tool's rich return structure. No contradiction with annotations exists.

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 compact—two sentences—with the primary function front-loaded in the first sentence. The second sentence adds the key use case (LLM injection). Every clause earns its place; there is no fluff or repetition of schema/annotation content.

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 parameterless tool with a rich output schema, the description fully covers what the agent needs to know: what the tool returns (natural-language brief plus structured fields) and why it's useful. The indicator categories are sufficiently enumerated, and the output schema handles the detailed return fields. No important contextual gap remains.

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 has zero parameters and the schema is empty (100% coverage), so the description does not need to explain parameter behavior. Per the baseline for 0-parameter tools, a 4 is appropriate since no additional parameter semantics are required.

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 states the tool's function with a specific verb ('Returns') and resource ('a pre-formatted natural-language paragraph summarizing 15+ economic indicators'). It distinguishes itself from sibling bundles by naming the indicator categories (rates, inflation, employment, mortgage market, energy, FX) and explicitly framing it as an 'economic context brief' ready for LLM prompts.

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 a clear usage context: the returned brief is 'ready to inject directly into an LLM prompt as economic context.' This tells the agent exactly when this tool is valuable. However, it does not explicitly contrast it with sibling analysis bundles (e.g., get_bundle_macro) or state when NOT to use it, so it falls short of a 5.

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