convert_markdown_to_html
Transform Markdown text into HTML code for web content creation and formatting.
Instructions
Convert Markdown to HTML
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| markdown | Yes | Markdown content to convert to HTML |
Transform Markdown text into HTML code for web content creation and formatting.
Convert Markdown to HTML
| Name | Required | Description | Default |
|---|---|---|---|
| markdown | Yes | Markdown content to convert to HTML |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false (implying mutation) and a title, but the description adds no behavioral context beyond the basic operation. It doesn't mention what happens with invalid markdown, whether HTML output is sanitized, performance characteristics, or any side effects. With annotations covering only basic safety, the description carries significant burden and adds minimal value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words with zero wasted language. It's front-loaded with the core functionality and contains no unnecessary elaboration. While potentially too brief for complete understanding, it earns maximum points for conciseness within this dimension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a data transformation tool with no output schema and minimal annotations, the description is inadequate. It doesn't explain what HTML format is produced (e.g., full document vs fragment), whether styling is preserved, or what happens with complex markdown features. The combination of sparse description and missing output schema leaves significant gaps in understanding the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with a clear parameter description for 'markdown'. The tool description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert Markdown to HTML' clearly states the verb (convert) and resource (Markdown to HTML), making the basic purpose understandable. However, it doesn't differentiate from sibling tools like 'convert_html_to_markdown' or 'format_html' beyond the obvious directionality. The description is functional but lacks specificity about scope or limitations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'convert_html_to_markdown' and 'format_html', there's no indication of when markdown-to-html conversion is preferred over other formatting or conversion tools. No context about prerequisites, input constraints, or typical use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/wrenchpilot/it-tools-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server