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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that the workspace's API key configuration is included, but does not disclose additional behavioral traits such as pagination, rate limits, or return format. This is a moderate addition beyond annotations.

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. The first sentence states the action and output, and the second sentence adds relevant context. Every word has purpose, with no 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 tool's simplicity (0 parameters, no output schema), the description fully covers its function and provides meaningful context about why it matters (enabling external model nodes in flows). It is complete for its complexity level.

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 has zero parameters, so the description does not need to explain parameter details. Baseline for 0 params is 4, and the description adds no unnecessary parameter-related information.

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 'List available LLM providers and whether your workspace has configured API keys for them.' This uses a specific verb (List) and resource (LLM providers), and distinguishes itself from sibling tools like list_models and list_flows by focusing on providers rather than models or flows.

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 provides context by noting 'Configured providers enable external model nodes in flows,' which suggests when to use this tool (when you need to verify configured providers for flow building). However, it does not explicitly mention alternatives or when to avoid using it, so it falls short of a 5.

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