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

No annotations are provided, so the description carries the full burden. It usefully discloses that input may be free-form text (code/config/IDs) and that output is capped at 10 matches, which is meaningful context. It does not address read-only safety, how truncated input is handled, or what fields each found model carries, leaving real behavioral gaps for a zero-annotation tool.

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?

A single compact sentence with a bracketed topic tag up front, stating domain and action before the constraint. No wasted clauses, though the bracket tag is decorative rather than informative.

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 one-parameter detection tool with no annotations and no output schema, the description covers the input shape and the result count, which is close to adequate. It omits what the returned model records contain (e.g., replacement suggestions, shutdown dates) and any boundary behavior, so an agent cannot fully predict the response.

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 a single parameter `text` with 0% schema description coverage, so the schema itself explains nothing. The description compensates by saying the parameter accepts pasted code, config files, or a model ID list, which is genuine added meaning, but gives no format expectations or size limits beyond the 10-result cap.

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 verb+resource: scan pasted code, config, or model-ID lists to detect models that are deprecated or about to be deprecated, plus the result cap of 10. This is clearly distinguishable from sibling list-style tools such as ai_model_shutdown_calendar or upcoming_ai_model_shutdowns, which surface the calendar rather than scanning user input. It stops short of naming those siblings explicitly.

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 tells the agent what to feed in (code, config file, or model ID list) and that only up to 10 matches are returned, which implies the usage scenario. However, it never states when to prefer this over models__ai_model_shutdown_calendar, models__upcoming_ai_model_shutdowns, or models__find_ai_model_replacement, so routing guidance is left implicit.

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