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Query your local files using natural language to find semantically related documents. Retrieves conceptually matched content offline using vector embeddings.

Instructions

Search for similar content using semantic search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query text
top_kNoNumber of results to return (default: 8)
filterNoOptional filters for the search
Behavior3/5

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

With no annotations provided, the description must carry full behavioral burden. It successfully discloses the semantic/vector similarity mechanism but fails to describe return format, result ranking logic, or whether the search is approximate/exact. No mention of latency implications for semantic search.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no redundancy. Front-loaded with primary action. However, extreme brevity leaves gaps in contextual information (resource type, return values) that a slightly longer description could address.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacking output schema, the description should ideally characterize results. Omits explicit mention that this searches 'documents' (the apparent domain from siblings) and gives no hint about result structure or scoring. Adequate minimum but clear gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% (all 3 parameters well-documented), establishing baseline 3. The description adds no additional parameter guidance, but none is needed given comprehensive schema coverage including the nested filter.doc_ids structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States the action (search) and mechanism (semantic) clearly, and distinguishes from 'list_documents' sibling by specifying 'similar content' via semantic search. However, it fails to specify the target resource (documents), which must be inferred from sibling tool names.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no guidance on when to use this tool versus siblings. Does not clarify when semantic search is preferred over 'list_documents' filtering, nor mention any prerequisites like existing document embeddings.

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

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