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by dongood
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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markdown_markdown_to_adf

Convert Extended Markdown to Atlassian Document Format (ADF), supporting Confluence extensions like panels, expands, media mentions, and status indicators.

Instructions

Convert Extended Markdown to Atlassian Document Format (ADF). Supports standard markdown plus ADF extensions like panels, expands, media placeholders, mentions, and status indicators.

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": {
      "markdown": "<markdown>"
    },
    "name": "markdown_markdown_to_adf"
  }
}

Input Schema

NameRequiredDescriptionDefault
markdownYesThe markdown text to convert to ADF.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly specifies the conversion behavior and enriches it with a list of supported extensions (panels, expands, media placeholders, mentions, status indicators), indicating the tool's capabilities. It does not mention error handling or side effects, but for a conversion tool the core behavior is transparent.

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, front-loaded with the primary purpose and followed by a succinct list of supported extensions. Every word contributes meaning, and there is no redundancy or fluff.

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 tool with one parameter and no output schema, the description is adequately complete. It identifies the input format, output format (ADF), and supported extensions. Minor gaps include not explicitly stating the output is JSON or any error behavior, but these are not critical for a conversion tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the parameter has a clear description. The tool description adds value by specifying that the input is 'Extended Markdown' and listing supported extensions, going beyond the schema's generic 'markdown text' description. This enriches parameter understanding.

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 converts Extended Markdown to ADF, using a specific verb ('Convert') and resource ('Extended Markdown to Atlassian Document Format'). This distinguishes it from sibling tools like markdown_adf_to_markdown, which performs the reverse conversion.

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

Usage Guidelines3/5

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

The description implies usage for markdown-to-ADF conversion and lists supported extensions, but it does not explicitly state when to use this tool over alternatives or mention the reverse tool. No exclusions or alternative references are provided, so usage guidance is implied rather than explicit.

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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