dispatch_get_brief

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

Beyond annotations (readOnlyHint, idempotentHint), the description discloses that the brief is cached and periodically regenerated, helping agents understand possible staleness. No contradictions with annotations.

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 front-loaded with the core purpose, followed by the synthesis details, caching behavior, and a structured return format. It is concise with no extraneous content, earning its keep with every sentence.

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 description covers input (none), output (detailed textual schema), behavioral details (caching), and usage examples. It adequately equips an agent to understand and invoke the tool, though a formal output schema JSON would further enhance 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?

With zero parameters (baseline 4), the description doesn't need to elaborate on parameter details. It instead explains the return format and provides usage examples, which is helpful but not required for parameter semantics.

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 identifies the tool as retrieving an AI-generated daily operational brief for CS Executive Services, specifying the synthesized components (TFR, weather, CPS, alerts, ops plan) and its use case (morning standup/client briefing). This distinguishes it from sibling tools that retrieve individual components.

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 states the brief is suitable for morning standup or client briefing, and examples imply it's for high-level summaries. While it doesn't explicitly contrast with siblings, the synthesis context makes it clear when to use this aggregated view versus specific tools like dispatch_get_cps.

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