html_to_markdownConvert HTML to clean Markdown: headings, links, images, lists, tables, code blocks, emphasis. Strips scripts, styles, and comments. POST { html } (max 500KB). Price: $0.005/call with credits key; free demo without (2KB input cap).
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | HTML document or fragment, max 500KB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It discloses key behavioral traits: strips scripts/styles/comments, size limits (500KB, 2KB demo), and pricing. This goes beyond a basic statement and informs the agent about side effects and constraints. However, it does not mention error handling or output format, so a 4 is appropriate.
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 two sentences and front-loads the core function, then provides essential usage details. Every word adds value—no redundancy or filler. Perfectly concise and well-structured.
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?
The tool is simple (one parameter, no output schema), and the description covers input, function, side effects, size limits, and pricing. It lacks explicit return value description but the purpose implies the output is Markdown. Given the simplicity, this is complete enough, but not exhaustive, so a 4.
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 schema fully describes the 'html' parameter, so baseline is 3. The description adds value by specifying the POST body structure '{ html }' and the demo 2KB cap, which are not in the schema. This enhances parameter semantics beyond the schema, warranting a 4.
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 clearly states 'Convert HTML to clean Markdown' with specific element coverage (headings, links, images, etc.), which is a specific verb+resource and distinguishes from the sibling markdown_to_html tool. This is a clear, unambiguous purpose statement.
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 clear context about when to use (converting HTML to Markdown) and includes invocation details (POST, size limits, pricing), but it does not explicitly mention alternatives or when not to use. This is 'clear context, no exclusions', hence a 4.
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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Each tool has a unique, non-overlapping purpose. Even closely related tools like html_to_markdown and markdown_to_html are clearly inverses, and read_page combines fetching and conversion, so no two tools could be confused for the same task.
All names are lowercase with underscores, maintaining a consistent syntactic style. However, there is no strict verb-noun pattern: some names are nouns (cron, diff, qr, timezone), others are verbs (convert, extract), and word order varies (email_verify vs validate_ids), which is a minor deviation.
With 13 tools, the count is well within the ideal 3-15 range. Each tool provides a distinct paid utility, and none feel redundant or out of place for a general-purpose vending machine API.
The tool surface covers a broad range of common utilities—format conversion, validation, extraction, formatting, and time handling. There are minor gaps like missing YAML conversion or raw HTML fetching, but these are not critical for the server's stated purpose as a collection of paid utilities.