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MilosJova

serve7-mcp-connectors

by MilosJova

Retrieve Knowledge

retrieve_knowledge

Search a knowledge base for articles matching a customer's question, returning top hits with relevance scores and source URLs to ground and cite responses.

Instructions

Search the knowledge base for articles relevant to a customer's question. Returns the top matches with a relevance score and source URL so responses can be grounded and cited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topKNoMax number of articles to return
queryYesNatural-language question or topic to search for
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It makes clear this is a read-only search that returns top matches with relevance scores and URLs, so the agent understands its output and non-destructive nature. It does not go into details like empty-result behavior or ranking beyond 'top matches'.

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 only two sentences and front-loads the core action before the output and use intent. Every sentence contributes meaningful information and there is no redundant filler.

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?

For a two-parameter retrieval tool with no output schema, the description covers the core use case, the result format, and the purpose. It is slightly incomplete only in that it does not explicitly explain relevance cutoff, sorting, or tell the agent to prefer it over sibling lookup tools.

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%, so the input schema already explains that 'query' is the natural-language search and 'topK' is the maximum result count. The description does not add further parameter-level guidance, so it stays at the baseline.

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?

Description uses a specific verb and resource: 'Search the knowledge base for articles'. It also states what the tool returns, including relevance score and source URL, making it clearly distinct from sibling tools like customer_lookup or create_support_ticket.

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

Usage Guidelines4/5

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

The description gives clear context for use: it is for answering a customer's question with grounded, citable knowledge articles. It does not explicitly mention sibling alternatives or when not to use the tool, so it misses the strict when-not guidance needed for a 5.

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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