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

With no annotations provided, the description carries the safety burden and explicitly states 'Read-only, free.' This tells the agent the operation has no side effects and no credit cost. It could add more about response shape, but for a simple list operation this is solid behavioral disclosure.

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?

Two short sentences with no wasted words. The core purpose is front-loaded, and the behavioral note 'Read-only, free' is compact and valuable.

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-parameter, read-only list tool, the description provides all essential context: what is listed, the workspace scope, the CRM attribution semantic, and the side-effect/cost profile. No output schema exists, but the return value is naturally inferable as a list of agents.

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 baseline for parameter semantics is 4. The description adds meaningful context about what the returned agents are used for, though no parameter-level detail is needed.

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 states a specific verb and resource: 'List the AI agents in this workspace that CRM leads can be attributed to.' This clearly distinguishes it from generic sibling tools like list_agents and list_agents_with_stats by scoping it to CRM-attributable agents.

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 intended use context is clear: use this tool when you need the set of workspace agents eligible for CRM lead attribution. It does not explicitly name alternatives or exclusions, but the CRM-specific scope makes the appropriate selection obvious among sibling list tools.

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