Get macro dashboard

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

Annotations already provide readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds value beyond this by disclosing what the response contains — regime, indicators, macroStress, sectorRotation with valid GICS names, calendar, and themes — which is useful behavioral context given there is no output schema. It does not mention data freshness or response size, but with annotations present the bar is lower.

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?

Two sentences, front-loaded with the primary purpose. The first sentence is dense but well-organized, listing all components in a readable list. The second sentence provides usage context. No wasted words; every clause earns its place.

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 0-parameter, read-only dashboard with safety annotations, the description is nearly complete. It explains the aggregated nature, enumerates all six return components, and gives a practical usage guideline (first call before drilling into stocks). Minor gaps exist — e.g., what 'macroStress' measures or how 'favored' sectors are determined — but these are not critical given the tool's simplicity.

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?

With 0 parameters, the baseline is 4. The schema has no properties, and the description correctly does not invent parameter semantics. Instead, it clarifies the return semantics (which fields the dashboard includes), which compensates for the absence of an output schema and helps the agent understand what the tool produces.

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: 'Full top-down macro picture in one call' with an explicit enumeration of contents (regime, indicators, macroStress, sectorRotation, calendar, themes). This distinguishes it from granular siblings like stoquant_get_market_regime or stoquant_get_macro_indicator by framing it as the aggregate dashboard.

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: 'Best first call for "what's the macro backdrop" before drilling into stocks.' This tells the agent when to use it (as a top-down starting point) and implies when not to (for stock-specific questions). However, it does not explicitly name alternative sibling tools or exclusion cases, stopping 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.