extractPull structured data out of raw text: emails, URLs, IPv4/IPv6, phone numbers, dates. Deduplicated with counts. POST { text } (max 500KB). Price: $0.003/call with credits key; free demo without (2KB input cap).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Raw text, max 500KB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries the disclosure burden. It discloses deduplication with counts, input size caps, and pricing model. However, it lacks details about the response structure or error behavior, which is important given no output schema.
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?
Three dense sentences with no filler. Front-loaded with purpose, then behavior, then cost. Efficient.
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?
Good coverage of purpose, input, and cost. Missing explicit return format details, though 'deduplicated with counts' hints at it. For a single-param tool with no output schema, more detail on output fields would improve completeness. Still, context is largely adequate.
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?
Schema covers 100% (text required). Description adds value by noting the demo cap (2KB) vs full 500KB, and by confirming the POST body format. This goes beyond the schema's static max size.
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?
Clearly states action 'Pull structured data out of raw text' and lists specific entity types (emails, URLs, IPs, phone numbers, dates). This distinguishes it from sibling tools like convert or html_to_markdown. Title 'Extract Pack' is vague but description clarifies.
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?
Provides clear context: for raw text input, with size limits and pricing. It doesn't explicitly exclude alternative tools, but no sibling performs entity extraction, so the context is sufficient. However, it doesn't say when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.