@createworker/mcp

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Create knowledge doc

knowledge_create

Create a text knowledge document that workers can reference, such as API docs. The document is chunked and embedded asynchronously for efficient retrieval.

Instructions

Create a text knowledge document (chunked/embedded asynchronously). Use this to give workers reference material — e.g. your API docs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "title": "<title>",
      "content": "<content>"
    },
    "name": "knowledge_create"
  }
}

Input Schema

Name	Required	Description
`title`	Yes	document title
`content`	Yes	the document text
`categoryId`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jun 30, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions asynchronous chunking/embedding, which is key behavioral information. However, it omits other important traits like authentication requirements, rate limits, or what happens if the tool is called multiple times. The description adds some value but is not comprehensive.

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 two sentences long, front-loading the core purpose and an example. Every sentence adds value with no redundancy.

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?

The description gives the basic purpose and usage but lacks details about return behavior, error handling, or parameter dependencies. Given no output schema and moderate schema coverage, the description could be more complete. It is adequate but leaves gaps.

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 67% (title and content have minimal descriptions, categoryId has none). The description does not explain any parameter meaning beyond the schema's own text. It fails to add context for categoryId or clarify the expected format of content. Since coverage is not high, the description should compensate but does not.

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 verb ('Create'), the resource ('text knowledge document'), and the asynchronous processing ('chunked/embedded asynchronously'). It effectively distinguishes from siblings like knowledge_get or knowledge_delete by being the only creation tool.

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 explicit usage guidance: 'Use this to give workers reference material — e.g. your API docs.' While it doesn't explicitly state when not to use it or list alternatives, the context is clear and helps an agent decide when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.