vector_search

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the technology (embeddings + Chroma) and optional filtering, but doesn't describe important behavioral traits like: whether this is read-only or has side effects, performance characteristics, error conditions, authentication requirements, or what the output format looks like. For a search tool with no annotation coverage, this leaves significant gaps.

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 extremely concise at just two short sentences with zero wasted words. The first sentence establishes core functionality, the second adds important parameter context. Every element earns its place, and the information is front-loaded with the primary purpose stated immediately.

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 3 parameters with 0% schema coverage, no annotations, no output schema, and a nested object parameter ('where'), the description is incomplete. It doesn't explain what the search returns, how results are ranked, what metadata can be filtered, or any limitations. For a semantic search tool with these contextual factors, the description should provide more operational context.

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?

With 0% schema description coverage, the description must compensate for all parameter documentation. It explicitly mentions the 'where' parameter's purpose ('metadata filter') and implies 'query' is for semantic search. While it doesn't mention 'topK', the description of 'Semantic search' combined with the parameter name strongly suggests it controls result count. This provides meaningful context beyond the bare schema.

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 performs 'Semantic search using embeddings + Chroma' which is a specific verb (search) with technology context. It distinguishes from sibling tools 'embed_text' (creating embeddings) and 'index_documents' (adding to index) by focusing on retrieval/search functionality. However, it doesn't explicitly contrast with these siblings in the description text itself.

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 context through 'Semantic search using embeddings' and mentions 'Optional metadata filter via `where`' which suggests when to use the where parameter. However, there's no explicit guidance on when to choose this tool versus alternatives like traditional keyword search tools that might exist elsewhere, nor does it mention prerequisites like needing indexed documents first.

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