get_search_filters

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

No annotations are provided, so the description carries the disclosure burden. It explains the returned faceted structure and how to use values (option.value vs range 'min;max'), which is meaningful behavioral context. Lacks only details about failures or empty results, but the core behavior is well covered.

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 deliver a precise structure definition, usage example, and workflow. All sentences are high-value with no redundant filler; the format example is compact and informative.

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?

Given the tool's simplicity (one parameter), the presence of an output schema, and the detailed usage flow, the description is complete. Agents know what to send and how to interpret results, including value formats.

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 coverage is 100% for the query parameter, and the description reinforces that it must be the same search text used previously. This adds practical context beyond the schema's description, ensuring agents pass the correct value.

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 returns facets available for a query, with structure {name, key, type, options|range}. It distinguishes itself from sibling tools like search by explaining it provides filter metadata, not search results.

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?

Explicitly describes the flow: search → get_search_filters → search(filters), and explains how to apply returned filters with the search tool. This gives the agent clear when-to-use and integration guidance beyond mere existence.

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