spine_recommend_animation_params

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

With no annotations provided, the description carries the full burden. It discloses the tool's fallback to built-in defaults when knowledge is missing and lists the output components. It does not contradict any annotations since none exist.

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 concise, consisting of three sentences. The purpose is stated first (front-loaded), followed by return value summary, then a clear negative constraint. Every sentence adds value without redundancy.

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 no output schema, the description adequately covers return values. The fallback behavior is explained. Parameter schema covers inputs well. However, it lacks details on how knowledgeDir defaults work or the role of availableAssetRoles beyond schema, which could be more explicit.

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 description coverage is 100%, so the schema already documents all parameters. The description adds high-level context ('using learned corpus presets and naming rules') but does not provide additional per-parameter meaning beyond what the schema already contains. 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 clearly states the tool converts a user goal into recommended BasicAnimationRequest parameters using learned corpus presets and naming rules. It includes a specific verb ('turn') and resource ('BasicAnimationRequest parameters'), and distinguishes itself from sibling tools that build, export, or analyze spines.

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 negative guidance ('Do not use it to write files, call Spine CLI, or build projects directly') but lacks positive guidance on when to use this tool over alternatives like spine_build_animation_from_json or spine_generate_animation_json. Usage context is implied but not explicitly contrasted with siblings.

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