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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds actionable behavioral context beyond this: membership is sourced from the same heuristic headline label as get_recent(category=model_release), and the list may be incomplete, so titles should be verified before quoting it as complete. This directly operationalizes the openWorldHint.

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 dense sentences with no filler. The core action and default are front-loaded, the returned data shape is summarized compactly, and the important completeness caveat is delivered at the end without bloating the definition.

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 single-optional-parameter read-only tool with an output schema and rich annotations, the description fully covers what an agent needs: what the tool returns, the default window, the grouping behavior, and a concrete data-quality caveat. Nothing critical is missing.

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?

There is only one parameter, days, and the schema already documents it as 'Look back N days (default 30)' at 100% coverage. The description repeats the default and lookback semantics but adds no new parameter-level meaning beyond the schema, so the high-coverage baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'List AI model releases from the last N days.' It differentiates itself by detailing the returned fields (model names, provider companies, release dates, feature summaries, source URLs) and grouping behavior, and it explicitly references the closely related sibling get_recent(category=model_release), so an agent can distinguish it.

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: a default 30-day lookback, grouped-by-importance output, and a specific relationship to get_recent(category=model_release). It does not explicitly state when to prefer an alternative over this tool, but the reference to get_recent gives the agent a fork to consider, and the caution about verifying completeness guides appropriate use.

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