Brand Snapshot Across Platforms

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: it is a read-only aggregate snapshot, clarifies that omitting brand_id returns a rollup of all brands, and documents the response structure. This goes beyond the annotations without contradicting them.

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 and concise: a summary sentence, the key questions answered, a bulleted args section, a return structure code block, and examples. Every part adds value and is correctly front-loaded with the most important information. No fluff or redundancy.

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?

With no output schema, the description provides a clear return structure, explains aggregation behavior, and gives practical examples. The combination of args, returns, and examples makes the tool self-contained and complete for an agent to select and invoke correctly. The tool's complexity is low (2 optional params), and the description fully covers it.

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?

The description significantly enhances the brand_id parameter, explaining that omitting it returns a rollup across all brands, which is not in the schema. The response_format parameter is only described as 'Output format', though the schema already provides a fuller description with enum values and default. With 50% schema coverage, the description compensates for brand_id but could also add a bit more detail about response_format, so a 4 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?

The description clearly states the tool's function: providing per-brand status across sigscheCore with specific counts (queued, sent, library items, brand cards, platform registration). It also frames the purpose around concrete questions ('is this brand ready to broadcast' and 'where are we still unregistered'), which distinguishes it from sibling tools like baatjie_signal_queue or baatjie_dashboard.

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 explicitly mentions the tool answers two key questions, giving clear context for when to use it. It also explains how to use the optional brand_id (omit for a rollup) and includes examples. However, it does not explicitly contrast with alternative tools or state when not to use it, though the questions provide strong implied guidance.

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