list_models

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

Annotations indicate readOnlyHint=true, so the read-only nature is already disclosed. The description adds useful context about aggregating all providers and the intended use with configure_council, but does not go beyond that to describe return format or any behavioral quirks.

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 two concise sentences, front-loading the core purpose and then providing a practical directive. The provider enumeration is verbose but informative and earns its place.

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 simple read-only list tool with full schema coverage and annotations, the description sufficiently explains what the tool does, the scope of providers, and how to use the results. No output schema exists, but the description covers the essential return value usage.

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 description coverage is 100%, so the filter_provider parameter is fully documented. The description does not add additional parameter-specific meaning beyond what the schema already provides, but it correctly implies the returned model IDs are for passing to configure_council.

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 lists all AI models across every configured provider, enumerating specific providers. This distinguishes it from sibling tools like configure_council or ask_council, which serve different functions.

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 explicitly ties usage to configure_council by saying 'Use the returned model IDs when calling configure_council.' This gives clear context for when to use it, though it does not explicitly state when not to use it or mention alternatives.

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