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

Annotations already mark this as read-only and idempotent, and the description adds substantial behavioral context: the meaning of kind_directed, the semantics of empty relations ('not researched yet' rather than 'no relatives'), and the presence of source_url and rationale. This goes far beyond the structured hints.

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 dense but well-structured, with each clause adding necessary semantic detail. It front-loads the core purpose, then explains the return shape AnimationEffect, edge cases for directionality and empty results, all 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?

Despite having no output schema, the description fully specifies the return structure, nested fields, optional fields, and special-case semantics. It gives an agent everything needed to interpret results correctly and understand the tool's behavior in unusual cases.

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 fully documents both parameters with 100% coverage)SkipIt, including precedence between model_id and series_id. The description adds value by explaining that either parameter returns the whole series' relationships, which clarifies that the two ids are not independent scopes.

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 a specific verb and resource: getting relationships between generations, enumerating the relationship kinds (succession, sibling, derivation, spiritual successor). It clearly distinguishes this from the sibling tools by focusing on relationship data rather than sales figures, vehicle details, or search results.

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 and schema make the input rule explicit: pass exactly one of series_id or model_id, with model_id taking precedence. It clarifies that either id yields the whole series' relationships, giving an agent clear usage context, though it does not explicitly name alternatives or state when not to use this tool.

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