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

Annotations provide readOnlyHint and openWorldHint, indicating a safe read operation with dynamic results. The description adds value by disclosing that it returns safety status (safe/deprecated/retired) and migration info, and by specifying input exactness. This goes beyond the annotations without contradicting them.

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: purpose+output, input examples, usage guideline. Front-loaded with primary action. No unnecessary words, every sentence adds distinct value. Highly 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?

Given a simple tool with one param, no output schema, and annotations covering read-only/open-world, the description covers the purpose, input format, output summary (status+migration), and usage context. It is nearly complete; a minor gap is that 'what to migrate to' is mentioned but not explicitly stated as a replacement ID. Still very good.

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 describes the single 'model' parameter with examples. The tool description reinforces this with additional examples ('gpt-4o', etc.) and emphasizes exact string usage. Schema coverage is 100%, so baseline is 3; the extra examples and clarity push it to 4.

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 uses a specific verb ('Check') and clearly identifies the resource (LLM model id lifecycle status). It distinguishes from sibling tools like 'list_retiring_models' or 'suggest_replacement' by emphasizing it checks a single exact model id string. The examples and usage directive further clarify its unique role.

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 explicitly states when to use the tool: 'Call this before writing or changing any hardcoded model id.' It does not explicitly state when not to use it, but the sibling context and focus on a single model id imply alternatives like 'list_retiring_models' for broader checks. The guidance is clear and actionable.

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