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associate_knowledge_to_agent

Link knowledge base documents to an AI agent by replacing its current document associations with specified IDs. Use to update or clear agent knowledge sources.

Instructions

Associates (links) knowledge base document IDs to an agent. Replaces the current list of knowledgeDocumentIds on the agent. Use list_knowledge_documents to get valid document IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentIdYesThe MongoDB ID of the agent to update
documentIdsYesArray of knowledge document IDs to associate with the agent. Pass an empty array to remove all.
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it states the tool performs a replacement operation ('replaces the current list'), specifies that an empty array removes all associations, and mentions the need for valid document IDs from another tool. It doesn't cover aspects like permissions or error handling, but for a mutation tool with zero annotation coverage, this is above the baseline.

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 front-loaded with the core purpose in the first sentence, followed by critical behavioral details and usage guidance in the second. Every sentence adds value without redundancy, making it efficient and well-structured for quick comprehension.

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?

Given the complexity of a mutation tool with no annotations and no output schema, the description is reasonably complete: it covers the purpose, behavior, and usage guidelines. However, it lacks details on return values or error cases, which would be helpful for full contextual understanding. It compensates well with the guidance provided.

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?

The input schema has 100% description coverage, providing clear details for both parameters. The description adds some semantic context by explaining that 'documentIds' are 'knowledge base document IDs' and that an empty array removes all, but this mostly reinforces what the schema already states. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding beyond 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 specific action ('associates/link knowledge base document IDs to an agent') and the resource ('agent'), distinguishing it from siblings like 'update_agent' or 'list_knowledge_documents'. It explicitly mentions the replacement behavior, which differentiates it from tools that might append or modify partially.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool vs alternatives: it specifies to use 'list_knowledge_documents' to get valid document IDs, and it clarifies the replacement behavior ('replaces the current list'), which helps avoid misuse with tools like 'update_agent' that might handle other aspects. It also implies usage for updating agent knowledge associations.

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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