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Obsidian MCP Server

Create Document with Properties

create_document_with_properties

Automatically generate and add metadata properties to Obsidian markdown files by analyzing document content, enabling structured organization and enrichment.

Instructions

Initiates an integrated workflow to read a document, guide an AI to generate properties, and then write those properties to a file.

This tool acts as a workflow manager for an AI agent. It reads the content of a specified document and returns a structured, multi-step plan. The AI agent must follow this plan by first calling the 'generate_obsidian_property' tool to get the document's content for analysis, and then, after generating the properties, calling the 'write_obsidian_property' tool to save them.

Use this tool to start the end-to-end process of enriching a document with AI-generated metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourcePathYesThe path to the source markdown file to read and analyze (e.g., "draft/my-article.md")
outputPathNoThe path where the processed file with properties will be saved. If not provided, the source file will be updated in place.
overwriteNoIf set to true, existing properties will be overwritten by the AI-generated content. Default: false.
aiGeneratedPropertiesNoAI-generated properties based on content analysis. If provided, these will be used instead of internal analysis.
quietNoIf true, the final write operation will return a minimal success message.
Behavior4/5

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

Annotations only provide openWorldHint=true, leaving the description to carry most behavioral disclosure. The description effectively explains that this is a workflow manager that returns a structured plan requiring follow-up tool calls, which is valuable context beyond annotations. However, it doesn't mention potential side effects like file system changes or error handling, leaving some behavioral aspects unclear.

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

Conciseness4/5

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

The description is well-structured with three paragraphs that progressively explain the tool's role, operational flow, and usage context. Each sentence adds value, though the second paragraph could be slightly more concise. Overall, it's appropriately sized for a complex workflow tool without unnecessary repetition.

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 tool's complexity (workflow manager with 5 parameters, nested objects, no output schema), the description provides good context about the multi-step process and sibling tool dependencies. However, it doesn't explain what the 'structured, multi-step plan' output looks like or mention error scenarios, leaving some gaps for a tool with this level of complexity.

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?

With 100% schema description coverage, the schema already documents all 5 parameters thoroughly. The description adds no specific parameter information beyond what's in the schema, so it meets but doesn't exceed the baseline. It implies parameters through context (e.g., 'specified document' relates to sourcePath) but provides no additional syntax or usage details.

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 tool's purpose: 'Initiates an integrated workflow to read a document, guide an AI to generate properties, and then write those properties to a file.' It specifies the verb ('initiates'), resource ('document'), and scope ('integrated workflow'), distinguishing it from simpler sibling tools like 'generate_property' or 'write_property' which handle only parts of this process.

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: 'Use this tool to start the end-to-end process of enriching a document with AI-generated metadata.' It also specifies the exact sequence of operations (call 'generate_obsidian_property' then 'write_obsidian_property'), making it clear when to use this tool versus using the sibling tools individually for more granular control.

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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