list_providers

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool lists providers and models, but doesn't disclose key traits like whether it's read-only, requires authentication, has rate limits, or what the output format looks like. This is a significant gap for a tool with zero annotation coverage.

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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 tool has no annotations and no output schema, the description is incomplete. It doesn't explain behavioral aspects like safety, permissions, or return values, which are crucial for an AI agent to use it correctly. The mention of 'brainstorming' adds some context but doesn't compensate for the lack of structured information.

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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, but it does mention the scope ('for brainstorming'), providing slight contextual value. Baseline is 4 for zero parameters, as the schema fully covers the lack of inputs.

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 verb ('List') and resource ('all configured AI providers and their default models'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'add_provider' or 'brainstorm', which would require mentioning this is a read-only listing operation versus creation or usage tools.

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 implies usage for 'brainstorming' context, suggesting when this tool might be relevant, but it doesn't provide explicit guidance on when to use it versus alternatives like 'add_provider' or 'brainstorm'. No exclusions or clear alternatives are stated, leaving usage context somewhat vague.

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