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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds useful context: the data is from the podcast-inference pipeline, is the 'latest', and supports filtering, which informs ordering and scoping expectations. No contradiction with annotations.

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 two compact sentences with zero filler. The core purpose and return fields are front-loaded, followed immediately by the filter options, making it efficient for an agent to process.

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 listing tool with three fully documented optional parameters and strong annotations, the description adequately covers source, output fields, and filtering. There is no output schema, but the description lists the key fields. Minor gaps remain around the meaning of 'lean' and 'line context' and the default limit, but the schema handles the limit.

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?

Schema description coverage is 100%, and the description only restates the team and tip_type filters without adding syntax or format details. It does mention output fields like 'probability' and 'lean', but those are return-value attributes rather than parameter semantics, so it does not elevate the score above baseline.

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?

States a specific resource (latest 0to100 betting tips), the source pipeline (podcast-inference), and the returned attributes (pick, probability, lean, line context), plus filters. It is clearly distinct from most sibling tools (injury, roster, odds), though it does not explicitly differentiate from get_consensus_board even though 'consensus board' appears as a tip_type example.

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?

Provides clear context: use this tool to retrieve recent betting tips, optionally narrowed by team or tip type. The tip_type examples hint at subcategories like 'single-game sample' and 'consensus board', which helps an agent choose, but it stops short of explicit when-not-to-use guidance or naming alternatives.

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