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Add knowledge to an agent

create_knowledge_base
Destructive

Add knowledge to an agent

Text knowledge, linked to the agent: the agent's AI context is rebuilt in the background, usually within a minute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
tagsNo
contentYesStored and given to the AI exactly as sent; send plain text. The dashboard shows content as rich text, so text shaped like an HTML tag, such as a placeholder in angle brackets, does not appear there and is lost if someone edits the entry in the dashboard.
agent_idYesThe agent the resource belongs to. Another company's agent, or the nil UUID, is `404 agent_not_found`; an agent outside the key's agent list is `403 agent_not_authorized`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, idempotentHint=false and openWorldHint=false, so the safety profile is largely covered. The description adds one genuinely useful behavioral fact the annotations don't convey — the AI context is rebuilt in the background, usually within a minute — but says nothing about duplicate creation, the effect on existing knowledge, or auth requirements beyond what the schema carries.

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

Conciseness3/5

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

Very short and the useful latency detail is present, but the first line duplicates the tool title verbatim, so roughly half the text is redundant rather than informative.

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?

For a 4-parameter mutation tool with no output schema, the description answers the important post-call question (background rebuild timing) but leaves the created resource's identity and its relationship to replace_knowledge_base undefined. Annotations partially compensate for the missing behavioral depth.

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 only 50%: content and agent_id are richly documented in the schema, but name and tags have no descriptions anywhere. The description's 'Text knowledge' only loosely reinforces the plain-text nature of content and adds nothing for the other two parameters.

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?

Clear verb+resource: it adds text knowledge to a specific agent, and the name/title pair is coherent. However it never distinguishes itself from the close sibling replace_knowledge_base (or get/list_knowledge_base), so an agent can't tell from the description whether this creates a new entry or appends to an existing knowledge base.

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?

No when-to-use, when-not-to-use, or alternative-tool guidance. With replace_knowledge_base sitting right next to it in the sibling list, the description's silence on the create-vs-replace choice is a real gap.

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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