GSAP-Animation-Generate

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool provides 'solutions' but doesn't describe how it works—e.g., whether it analyzes code, simulates animations, returns step-by-step fixes, or requires specific inputs beyond the schema. This lack of detail makes it hard for an agent to predict behavior, especially for a debugging tool that might involve complex logic.

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, efficient sentence that front-loads key information ('Expert debugging for GSAP animation problems') and avoids redundancy. Every word earns its place, making it easy to parse quickly without unnecessary elaboration.

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 the tool's complexity (debugging likely involves analysis and solutions), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover how results are returned, what 'solutions' entail, or behavioral traits like error handling. This leaves significant gaps for an agent to use the tool effectively.

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 0%, so the description must compensate for undocumented parameters. It mentions 'GSAP animation problems' but doesn't explain the three parameters (issue, code, expected_behavior)—e.g., what constitutes a valid 'issue' or how 'code' should be formatted. This leaves semantics unclear, failing to add meaningful context beyond the bare schema.

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's purpose as 'Expert debugging for GSAP animation problems with solutions,' specifying the verb ('debugging'), resource ('GSAP animation problems'), and expertise level ('Expert'). It distinguishes from siblings like 'optimize_for_performance' or 'understand_and_create_animation' by focusing on debugging rather than creation or optimization, though it doesn't explicitly name alternatives.

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 no guidance on when to use this tool versus alternatives. It mentions 'GSAP animation problems' but doesn't specify contexts, prerequisites, or exclusions. For example, it doesn't clarify if this is for runtime issues, code errors, or performance problems, leaving the agent to infer usage from the tool name alone.

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