faceted_search

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

With no annotations, the description carries the full burden of behavioral disclosure. It only describes filtering capability without mentioning read-only nature, side effects, result format, or pagination. The description is too minimal for safe invocation.

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 brief (three sentences) and to the point, with no redundant information. It could be slightly more structured (e.g., listing parameters explicitly), but overall it is efficient.

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 omits return value information (no output schema), does not mention max_results and tags parameters, and lacks details on behavior like default limit or sorting. Given the tool has 4 parameters and nested objects, this is inadequate.

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?

Despite 100% schema coverage (baseline 3), the description adds value by giving concrete examples of facet types and values (e.g., SID, LDA, $D000) that go beyond the schema's generic example. However, it does not cover other parameters like max_results or tags.

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 it is for searching with faceted filtering and provides concrete examples of filter types (hardware, assembly instructions, memory registers). However, it does not explicitly differentiate from sibling search tools like fuzzy_search or semantic_search, so clarity is strong but not fully distinguished.

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 implies usage for narrowing down to specific technical domains, but lacks explicit guidance on when to use this tool versus alternatives. No exclusions or when-not-to-use scenarios are mentioned, leaving the agent to infer context from the examples.

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