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

Annotations declare readOnlyHint=false and idempotentHint=false, but the description adds that it returns a run_slug and can be synchronous or asynchronous, and that it should be followed by result/export tools. This conveys the execution flow and side-effect potential. It stops short of detailing all behavioral nuances (e.g., callback semantics, resource usage), but since annotations already cover the core mutation nature, the added context is above average.

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 well-structured with labeled sections (WHEN TO USE, WHEN NOT TO USE, RETURNS, WORKFLOW) and each sentence provides essential operational context. It avoids repetition and unnecessary details, earning a top score for clarity and efficiency.

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 tool with no output schema and a complex execution action, the description covers purpose, usage boundaries, expected return, and follow-up workflow. It lacks some depth on the actual execution side effects, but the workflow hint and return description make it sufficiently complete for an agent to invoke correctly.

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 covers 100% of parameters with descriptions, including examples and defaults. The tool description itself doesn't add further parameter-level detail, only clarifying the primary parameter (worker_task_id) represents a 'saved' task. This is sufficient, meeting the baseline for high schema coverage.

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 opens with a clear verb+resource: 'Run a saved CoreClaw worker task.' It distinguishes from siblings by stating this is for 'configured task rather than supply ad-hoc worker input,' and clarifies the return type ('run_slug or synchronous result fields'). This fully differentiates it from adjacent tools like run_worker.

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?

Explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections provide clear guidance, including the exact scenario (executing a configured task) and exclusions (no public web/code search for private data, no internal APIs). The 'WORKFLOW' section even suggests follow-up tools, giving an implementation path.

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