refresh_brand

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

Annotations provide readOnlyHint=false and openWorldHint=true but the description adds substantial behavioral detail: it returns immediately with run IDs rather than results, results arrive asynchronously in 30-60 seconds, and it only executes engines with configured API keys. This is meaningful context beyond what the annotations convey, explaining the async nature and dependency requirements.

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?

Three sentences that each earn their place: the first states the primary function and scope, the second provides usage triggers when to invoke, the third explains the async return behavior. No fluff, no repetition of schema content, and the most important information (what it does) is front-loaded.

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 relatively simple with only 2 parameters and full schema coverage. An output schema exists so return-value documentation is not needed. The description covers the action, the engines involved, when to use it, the immediate return behavior, and the async timing of results. For a trigger-style tool, this is complete and well-suited to its complexity level.

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 schema already documents both parameters well (brand_id as stable identifier, engines with its enum values and omission semantics). The description reinforces engine behavior by naming the concrete engines and noting the 'optional engine filter' default behavior of refreshing all configured engines. The description adds minimal value beyond the schema since coverage is complete, justifying the baseline 3.

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 what the tool does: 'Manually trigger a fresh AI visibility scan for a tracked brand.' It names the specific action (refresh/scan), the resource (brand), and enumerates the engines covered (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews). It also distinguishes its context from sibling tools like get_visibility_history (which reads history) and check_visibility (which checks current state) by focusing on the on-demand refresh 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?

The description provides explicit usage triggers: 'Use when the user asks refresh my data, rerun the scan, or I want fresh data right now.' It explains behavioral constraints (only runs engines with API keys configured, runs against current prompt set) and clarifies what happens upon invocation (returns run IDs immediately, results in 30-60 seconds). This gives strong when-to-use guidance with clear context.

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