sf_semantic_search

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

With no annotations provided, the description carries full burden. It discloses that the tool 'analyzes your query to extract entities, intent, and synonyms' and returns 'section-level matches with header paths,' which are meaningful behavioral details. It omits any side effects, but as a search tool, read-only behavior is implied. No contradictions detected.

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 three sentences, front-loaded with the core purpose. Each sentence contributes new information (capability, behavioral detail, usage examples). It is concise without being terse, and no unnecessary words are present.

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 moderate complexity (3 parameters, no annotations, no output schema), the description provides the essential context: what it does, how it works, what it returns, and example queries. It does not explain parameter semantics beyond the schema, but the schema covers that. Overall, it is sufficiently complete for an agent to select and invoke correctly.

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 baseline is 3. The description reinforces that the query parameter should be natural language, but does not add significant meaning beyond the schema's field descriptions and examples. The limit and domain parameters are not addressed in the description, but the schema covers them adequately.

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 a specific verb+resource: 'semantic search' with NLP query understanding, distinguishing it from regular 'sf_search'. It also describes the output ('section-level matches with header paths') and provides concrete query examples, making the tool's purpose unmistakable.

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 instructs to use this tool for natural language questions and gives examples, providing clear context. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of the highest benchmark.

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