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

Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds valuable behavioral context about the tool's output structure (what it returns) and its prerequisite (needs a tool name from tools/list). It doesn't contradict 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 compact and front-loaded, with the first sentence summarizing the tool's function and the second providing usage guidance. Every sentence carries information; no filler 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?

Despite the absence of an output schema, the description enumerates the key return categories comprehensively, enabling the agent to know what to expect. It also covers prerequisites and usage context, making it complete for a simple one-parameter tool.

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 input schema has full coverage: tool_name is described as 'Exact tool name from tools/list.' The description reinforces this by mentioning tools/list, but provides no additional semantic detail beyond the schema. With 100% schema coverage, 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?

The description clearly states the tool provides guidance for another tool on the MCP facade, enumerating the specific categories of information it returns (usage, refusals, examples, limits, outputs, provenance, next calls, interaction contract). This distinguishes it from sibling tools like get_catalog, get_pack, and query_dataset, which serve different purposes.

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 gives explicit usage guidance: use tools/list to find tool names, then call this before an unfamiliar tool. It provides clear context for when to use the tool, but does not explicitly state when not to use it or name alternatives (though the guidance implies it's for unfamiliar tools only).

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