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Semantically search a text collection and retrieve the top-k most relevant chunks with a cosine similarity score.

Instructions

Semantic search a collection. Returns the top-k chunks with a 0-1 cosine score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes
collectionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions semantic search and returns chunks with scores, indicating a read operation. However, it does not disclose permissions, rate limits, or whether it is read-only (though likely). The description is adequate but lacks depth.

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

Conciseness5/5

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

The description is extremely concise with two sentences containing no unnecessary words. It efficiently conveys the core functionality and output format.

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

Completeness2/5

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

Given the output schema exists, return values are covered externally. However, with 0% schema description coverage and no parameter explanations, the description is incomplete. It does not clarify the meaning of 'chunks', sorting order, or how the score is used, leaving gaps for an AI agent.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should explain parameters. It does not describe 'k', 'query', or 'collection' beyond their presence in the schema. 'query' and 'collection' are self-explanatory but could benefit from format hints, while 'k' default of 5 is not justified. The description adds minimal value over the schema.

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

Purpose5/5

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 on a collection and returns top-k chunks with a cosine score. The verb 'search' and resource 'collection' are specific, and it distinguishes from siblings like delete_collection, ingest_text, and list_collections, which manage collections rather than search them.

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

Usage Guidelines3/5

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

The description implies usage for semantic search, but it does not explicitly state when to use this tool versus alternatives. Since it is the only search tool among siblings, usage is clear, but there is no guidance on when not to use it or any prerequisites.

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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