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

No annotations provided, so description carries the burden. It describes the output as a plain-English paragraph and implies a read operation, but does not explicitly state it is read-only, safe, or free of side effects. Lacks clarity on mutability and permissions.

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?

Description is three sentences, front-loaded with usage triggers, then output content, then sibling reference. No wasted words; highly efficient and structured.

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 absence of output schema, the description explains the return value in detail (launch count, channels, etc.). However, it does not address edge cases like empty brains or required parameters, and the workspaceId is assumed but not explicitly noted as likely required.

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?

Schema coverage is 50% (tenantId is described in schema, workspaceId is not). The description adds no parameter meaning beyond the schema, and the purpose of tenantId vs workspaceId is not clarified. For two parameters, more guidance would help the agent.

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?

Description clearly states 'Returns a plain-English paragraph summarizing what the per-workspace brain has accumulated' and lists specific content like launch count, top channels, etc. It distinguishes from sibling chieflab_brain_read by mentioning it provides raw structured data, making the purpose specific and differentiated.

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?

Explicitly states 'USE WHEN the user asks...' with example queries and pairs with an alternative tool for raw data. This gives clear context on when to use and when not to, satisfying the dimension fully.

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