workspace_chat

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

No annotations are provided, so the description carries the full burden. It discloses that the tool sends the message to the RunWhen workspace AI agent with ~25+ internal tools, and describes the return format. However, it does not explicitly state whether the tool is read-only or if it has side effects, though the context implies it is investigative. This is a minor gap but well-covered overall.

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 clear sections: purpose, usage guidance, alternatives, and return format. It is front-loaded with the core purpose and every sentence adds value without redundancy. The bullet points for return fields are efficient.

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 complexity as a chat interface to an AI agent with many internal tools, the description is highly complete. It covers purpose, usage scenarios, alternatives, internal capabilities, and return format. The presence of an output schema (not shown but referenced) further supports completeness.

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 description coverage is 100%, so the baseline is 3. The description does not add additional context for individual parameters beyond what the schema already provides, but the schema descriptions are clear and sufficient. The description's main value is in the overall tool behavior rather than parameter details.

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's purpose: 'Ask the RunWhen AI assistant about your infrastructure' and positions it as the PRIMARY tool for investigating infrastructure. It distinguishes from sibling tools by explicitly listing them and explaining when to prefer this tool over direct read/query tools.

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 explicit guidance on when to use this tool (prefer for any question involving searching by topic, keyword, or context) and when to use direct tools instead (for executing tasks, task authoring, registry operations, chat config CRUD, KB mutations, or when raw structured JSON is needed). Examples are given.

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