Workspace Chat

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: it searches by keyword/semantic/fuzzy, correlates across resources/SLXs/issues/sessions/KB, and returns markdown reports, diagrams and tables. It does not cover permissions, auth requirements, rate limits, or latency, which are the remaining behavioral gaps for a chat/agent tool.

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?

Front-loaded with the core purpose and routing guidance, then cleanly sectioned with a 'Returns:' block. It is somewhat long, and the return-value enumeration is largely redundant since an output schema exists, which slightly undercuts economy.

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 complex AI-assisted query tool, the description covers purpose, routing against numerous siblings, internal behavior, and usage conditions. Since a full output schema is present, the extra return-value prose is redundant but harmless, and nothing an agent needs to invoke it correctly is missing.

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 message, session_id, persona_name, and workspace_name are already documented in the schema. The description adds essentially nothing to parameter meaning (e.g., it does not explain session continuation semantics beyond what the schema says), so the baseline 3 is appropriate.

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?

States a specific verb+resource ('Ask the RunWhen AI assistant about your infrastructure') and elaborates on the internal search/correlation behavior. It explicitly distinguishes itself from siblings by naming get_workspace_issues, get_workspace_slxs, search_workspace, and run_slx, so an agent can route correctly without opening any schema.

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?

Provides explicit when-to-use ('any question that involves searching by topic, keyword, or context') with concrete examples, plus a when-NOT-to-use list ('executing tasks, task authoring, registry operations, chat config CRUD, KB mutations, or raw structured JSON'). It also names the alternative tools to use instead, leaving nothing to inference.

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