list_presets

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It discloses that experimental presets are hidden unless includeExperimental is true, and that each preset includes a description and maturity. This goes beyond the schema's scope, though it doesn't address error cases or prerequisites.

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 three sentences, each earning its place: the first states purpose with examples, the second explains the experimental preset filter, and the third gives usage advice. There is no fluff or 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?

Given the absence of an output schema, the description sufficiently explains what is returned (presets with description and maturity). It also covers the experimental hiding behavior and offers selection guidance. It could mention how the results integrate with generate_project, but for a 2-parameter list tool, this is quite complete.

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 already describes both parameters (100% coverage), so the baseline is 3. The description adds real value by providing examples of preset names (ts-lib, py-lib, etc.) that clarify the nature of the generator parameter, and reinforces the effect of includeExperimental. This helps the agent understand expected parameter values.

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 function: 'List the presets a generator offers' with concrete examples (ts-lib, react-lib, node-service, py-lib, py-cli) for different generators. It also distinguishes itself from sibling list_generators by focusing on presets of a specific generator rather than the generators themselves.

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 guidance is implied: 'Choose a preset that matches the shape the user wants instead of guessing' suggests using this tool for preset selection. However, it does not explicitly state when not to use it or mention alternatives like list_generators or get_generator_schema, so the usage context is not fully explicit.

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