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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the returned content (statuses, dates, migration target, URL), which is useful. However, it does not disclose error behavior for unknown model_ids, what 'days until shutdown' returns for active/preview models (null vs zero), date formatting, caching, or any rate limits. For a read-only query tool this is a moderate gap, not a critical one, hence a 3.

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 a single dense sentence that front-loads the core purpose and then lists the deliverable fields compactly. The leading 'FREE.' is a minor token that adds no clear value and slightly muddies structure, but the rest is efficient with no redundancy. It earns a 4 rather than 5 due to that stray prefix.

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, no-output-schema tool with no annotations, the description does a solid job enumerating what the caller receives, which is the primary thing an agent needs. The gaps are error handling for invalid model_id and edge-case semantics of 'days until shutdown' for non-deprecated models. These are worth noting but not severe enough to drop below a 4 given the tool's low complexity.

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 coverage is 100%, with model_id well documented via canonical examples in the schema itself. The description adds only that the tool covers a single model's lifecycle, lightly reinforcing that model_id selects which model. Since the schema already carries the parameter detail, the description adds no meaningful syntax or format information beyond it, so the baseline 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 specifies the resource ('one AI model') and enumerates the returned fields (status, dates, days until shutdown, migration target, source URL), which makes the purpose clear. The singular framing implicitly distinguishes it from siblings like get_model_lifecycle_all (all models) and upcoming_deprecations (future events), though it never names them explicitly. It lacks a strong verb, using a noun phrase ('Lifecycle of...') instead, which costs it a 5.

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?

Usage context is implied but not stated: the singular 'one AI model' suggests this tool is for querying a specific model's full lifecycle, while siblings get_model_lifecycle_all, is_model_live, and upcoming_deprecations cover other cases. No alternative tools are named and no when-to-use/when-not-to-use guidance or exclusions are given. The 'FREE' prefix hints at cost behavior but is not explained. An agent must infer the boundary against siblings on its own.

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