List Discovery Platforms

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

With no annotations, the description carries the behavioral burden and does disclose a useful trait: all catalog data is bundled offline with no docs.runwhen.com access required, clarifying latency/permission expectations. It omits return-shape detail, but an output schema exists to cover that.

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 purpose is front-loaded and the sequencing guidance is high value, but the embedded Skills list and skill URI references add length not strictly needed to call a zero-argument lister.

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?

For a zero-param catalog lookup with an output schema and a workflow dependency on render_codecollection_skill, the description supplies exactly the sequencing and follow-up routing an agent needs; nothing material is missing.

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 tool takes zero parameters, so per the rubric the baseline is 4; there are no parameter semantics to add beyond what the empty schema already shows.

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 opening sentence gives a specific verb ('List') and resource ('supported generation-rule platforms and default render settings'), which an agent can immediately distinguish from siblings like list_indexed_resource_types or render_codecollection_skill.

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?

It states explicitly when to call it ('before render_codecollection_skill when the user has not confirmed workspace-scoped vs per-resource discovery'), names the alternatives (runwhen/kubernetes/azure/aws/gcp), and points to the follow-up tool list_indexed_resource_types(search=...).

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