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

With no annotations, the description carries the burden and discloses useful behavior: normalization from multiple sources, deduplication per model, a status of official or pending review, and a since/latest polling contract. It omits auth, rate limits, and failure behavior, but covers the important traits for a read-only change feed.

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?

Three sentences front-load the purpose, then add provenance/deduplication behavior and polling instructions without significant fluff. The source list is slightly long, but each clause contributes.

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 tool with no output schema and no annotations, the description covers purpose, sources, and polling, but leaves the response item shape largely implicit beyond `latest` and a status marker. An agent can call it, but would benefit from knowing what fields each change entry contains.

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 schema already describes limit, model, and since; the description adds little per-parameter value beyond framing `since` as a polling cursor. It enumerates change categories which partially supports the undocumented `type` enum, but omits `open_source_surge`, so it does not fully compensate for the 25% schema coverage gap.

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 that the tool returns changes across AI models (new releases, price changes, API changes, deprecations) and cites its data sources, so the core purpose is clear. It does not explicitly contrast itself with siblings such as get_price_history or search_models, so differentiation is left to inference.

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?

It gives explicit polling guidance: call with `since` in unix seconds and feed the returned `latest` back next time. It does not state when to avoid this tool or name alternatives, so there is clear context but no exclusions.

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