ai_assist

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

The description discloses auth requirements, rate limiting, task-specific behaviors (e.g., jam merges and auto-plays, suggest returns text), and the optional audio analysis for feedback. However, it does not detail error handling or side effects of invalid inputs.

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 (7 sentences), front-loaded with the overall purpose, and structured clearly by task. No redundant information.

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 the tool (8 parameters, 3 tasks), the description covers all tasks, authentication, sibling alternatives, and provides a usage example. It adequately compensates for the lack of output schema by describing return behaviors.

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?

Input schema has 100% coverage, so baseline is 3. The description adds meaning by explaining how parameters relate to each task (e.g., includeAudio for feedback, layer for jam) and provides context beyond the 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 is a Gemini-backed pattern assistant with three distinct tasks (feedback, suggest, jam). It differentiates from siblings by recommending generate_part for non-AI generation and compose for full compositions.

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?

Explicit guidance is provided: when to use each task, prerequisites (GEMINI_API_KEY), and alternatives (generate_part, compose). An example invocation is given.

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