Ultimate GSAP Master MCP Server

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 'expert debugging' and 'solutions,' but doesn't detail how it operates—e.g., whether it analyzes code, suggests fixes, or requires specific inputs beyond the schema. For a debugging tool with no annotation coverage, this is a significant gap in transparency.

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 and front-loaded with key information: 'Expert debugging for GSAP animation problems with solutions.' It uses minimal words to convey the core purpose efficiently, with no wasted sentences. However, it could be slightly improved by adding a bit more structure, such as separating intent from outcome.

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 complexity of debugging tools, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., diagnostic reports, code fixes), behavioral traits like error handling, or how it interacts with GSAP specifics. This leaves significant gaps for an agent to understand the tool's full context and usage.

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 input schema has 100% description coverage, with clear parameter descriptions (e.g., 'Description of the animation problem'). The description adds no additional semantic context beyond the schema, such as examples or usage tips. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

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: 'Expert debugging for GSAP animation problems with solutions.' It specifies the action (debugging), target (GSAP animation problems), and outcome (solutions). However, it doesn't explicitly differentiate from sibling tools like 'get_gsap_api_expert' or 'optimize_for_performance,' which might also address animation issues, so it doesn't reach the highest score.

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 doesn't mention any prerequisites, exclusions, or compare it to sibling tools such as 'understand_and_create_animation' or 'optimize_for_performance.' This lack of context leaves the agent without clear usage instructions.

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