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

Beyond the annotations, the description discloses important behavioral details: only derived aggregates are published, index level and change are excluded, stale data behavior is defined, and the tool is self-caching. These details materially improve the agent's ability to interpret results and understand fallback behavior.

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 front-loaded with the resource and returned metrics, then adds only necessary behavioral caveats about index-level omission, stale data, caching, and parameter count. There is no filler or repetition.

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 that there is no output schema and the tool has no parameters, the description provides a complete list of returned metrics plus stale and caching behavior. An agent has enough context to invoke and interpret the tool correctly.

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 takes zero parameters, and the description explicitly states 'No parameters,' matching the empty schema. With no parameters to document, the baseline for this dimension is satisfied.

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 a specific resource: S&P 500 market breadth and its exact derived aggregates, including moving-average percentages, zones, advancers/decliners, and highs/lows. It does not explicitly differentiate this tool from the sibling tools such as get_market_health_history or get_market_valuation, so it falls short of a 5.

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 explains what the tool returns but gives no guidance on when to use it instead of alternatives. It does not mention sibling tools, use cases, or conditions for selecting this breadth read over related market-health tools.

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