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

With no annotations, the description carries the full burden of behavioral disclosure. It honestly states the returned fields, but it does not mention error behavior (e.g., invalid/unknown slug), rate limits, or any side effects (though as a 'get' operation, mutation is unlikely). This is adequate for a simple read-only tool, but lacks richer context.

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 a single, front-loaded sentence that states the action, scope, and what is returned. No filler or redundant phrasing, making it exceptionally concise and well-structured.

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 simple one-parameter lookup tool without an output schema, the description adequately covers inputs and outputs. However, 'full market data' is vague and could be more explicit about the exact structure, and there is no mention of not-found behavior. Still, it is sufficiently complete for typical usage.

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 describes the slug parameter fully ('Market slug (from URL or search results)'), and the description merely says 'by slug' without adding new syntactic or semantic details. At 100% schema coverage, the baseline is 3, and the description does not exceed it.

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 states a specific verb ('Get'), resource ('market'), and identifier ('by slug'). It clearly enumerates the returned data (probabilities, volume, liquidity, outcomes, full market data), which distinguishes it from sibling tools like search_markets or analyze_market.

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 phrase 'by slug (from URL or search results)' implies a workflow where a user first searches for markets and then uses get_market with the resulting slug. However, it does not explicitly contrast this tool with alternatives such as analyze_market or search_markets, so usage guidance is only implicit rather than explicit.

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