generate_service

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

With no annotations, the description carries the full burden. It mentions the tool generates a service handling events and telemetry, and clarifies the default behavior with layout_json. However, it does not disclose side effects (e.g., file creation), error scenarios, or required permissions, leaving gaps 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 with a clear first sentence stating the core purpose, followed by a brief default behavior note and a structured Args block. Every sentence adds value with no 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?

Considering the tool has an output schema and one parameter, the description is adequate but missing context about prerequisites (e.g., existence of a buffer), success outputs, or error handling. It covers the main function but not all aspects an agent might need for correct invocation.

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 coverage is 0%, but the description includes an Args section that explains layout_json as optional and defaulting to the working buffer. This adds meaning beyond the schema, though it lacks details like expected format or constraints.

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 it generates a runnable Python MeshSocket service that interacts with a layout, handling events and emitting telemetry. This distinguishes it from sibling tools like generate_adapter or generate_theme, which serve different purposes.

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 explains when to omit layout_json (defaults to working buffer) but provides no guidance on when to choose this tool over other generation tools or when not to use it. No explicit alternatives or exclusions are mentioned.

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