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NavinAnik

mcp-knowledge-server

by NavinAnik

similar_documents

Find similar documents by chunk ID, filter by collection, and control the number of results returned.

Instructions

Find documents similar to a given chunk.

    Args:
        chunk_id: The chunk ID to find similar documents for.
        collection: Optional collection to search in.
        top_k: Number of similar results to return.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_kNo
chunk_idYes
collectionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description should disclose behavioral traits like read-only nature, side effects, or authentication needs. It only lists parameters, which duplicates the schema, and does not explain behavior such as ordering or failure modes.

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 concise and front-loaded with a clear purpose, followed by a neatly formatted Args section. Every sentence earns its place with no redundancy.

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

Completeness4/5

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

The output schema exists, so return format is handled. The description covers the core functionality and all parameters adequately for a relatively simple tool, though it does not explain the notion of similarity or any edge cases.

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

Parameters4/5

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

Despite zero schema description coverage, the description adds meaning to each parameter: 'Optional collection to search in' clarifies that collection is optional, and 'Number of similar results to return' explains top_k. This goes beyond mere parameter names, though it briefly stays close to self-evident definitions.

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 'Find documents similar to a given chunk', which uses a specific verb and resource. It distinguishes itself from sibling tools like 'search_documents' by emphasizing similarity to a chunk rather than a query.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or preferred scenarios, leaving the agent to infer usage context.

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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