Get Backend Capabilities

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

The description goes well beyond the annotations: it explains open-world semantics ('missing advertisement is unknown, not unsupported'), warns that advertised features still require permission and budget, and discloses that no model is created and capabilities are not cached across callers. This meaningfully informs how the agent should treat the result.

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?

Four compact sentences, each earning its place: when to use, what it returns, how to interpret missing/advertised features, and what side effects to expect. The key guidance is front-loaded.

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?

With zero parameters, rich annotations, and an output schema present, the description is fully sufficient for an agent to select and invoke the tool correctly. It covers timing, interpretation, permission nuance, and non-caching behavior.

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?

There are zero parameters, so the description carries no parameter burden. The baseline of 4 applies, and the description still helps set expectations about what the returned result represents.

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 uses a specific verb and resource: 'Discover this caller's connected backend features' and clarifies it returns only backend advertisements for model families, transformations, priors, and workflow operations. This clearly differentiates it from the many sibling tools by scope and intent.

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 explicitly says to use this before planning work and explains how to interpret missing advertisements ('unknown, not unsupported'). It does not name exclusions or alternative tools, but none of the siblings compete with this capability-discovery role.

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