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

With no annotations, the description carries the transparency burden. It discloses that the tool returns 'kind + label' for each specialist, which clarifies the output structure. As a simple, non-mutating list tool, this is sufficient disclosure for safe invocation.

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 concise sentences with the action front-loaded ('list the specialist agents') and no filler. The secondary sentence provides use-case context and return-value details, every word 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?

The tool is simple (no params, no output schema), and the description covers the purpose, usage triggers, and return format. It gives the caller enough information to decide when to use it and what to expect.

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 cannot add parameter-level detail. The baseline for a no-parameter tool is 4, and the description appropriately focuses on the tool's output and purpose.

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 specialist agents ChiefLab can delegate to, enumerating specific categories (design/video/research/outreach/seo/analytics). This uses a specific verb+resource and differentiates from sibling tools like chieflab_request_specialist by framing it as a prerequisite listing action.

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 usage triggers are provided: 'USE WHEN the user asks...' and 'before calling chieflab_request_specialist'. While it names a related tool, it doesn't explicitly list exclusions or alternatives beyond that, so it stops 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.