feed_to_jsonParse an RSS 2.0 or Atom feed into clean JSON: title, items with link/date/summary, HTML stripped. POST { xml } (max 1MB) or { url } to fetch. Price: $0.004/call with credits key; free demo without (2KB input cap).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Feed URL to fetch instead | |
| xml | No | Feed XML, max 1MB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It explicitly mentions input limits (1MB for xml, 2KB demo cap), input modes (xml or url fetch), output content, and pricing. While it doesn't cover failure modes or auth details, it provides substantial transparency beyond what a schema would convey.
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 three sentences, front-loaded with the core purpose, then input methods, then pricing/limits. Every sentence earns its place with no redundancy or filler, making it efficient and easy to parse.
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 (2 optional params, no output schema), and the description covers purpose, inputs, limits, and output shape. However, it does not explicitly state what happens if both xml and url are provided, or whether they are mutually exclusive. This minor gap prevents a 5, but the description is otherwise complete enough for an agent to invoke correctly.
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 description coverage is 100%, so the baseline is 3. The description reinforces that xml and url are alternative inputs, but the schema already conveys this via the url description ('Feed URL to fetch instead'). The pricing and demo cap are not parameter-specific, so the description adds minimal extra semantic value beyond the schema.
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 the tool's function with a specific verb (Parse) and resource (RSS 2.0 or Atom feed), and specifies the output (clean JSON with title, items, link/date/summary, HTML stripped). This distinguishes it from sibling tools like extract or html_to_markdown, which serve different purposes.
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 for when to use the tool (when you need to parse an RSS/Atom feed) and explains how to invoke it (POST xml or url). It notes a demo cap and pricing, which are usage constraints, but it does not explicitly discuss alternatives or when not to use the tool. This aligns with 'clear context, no exclusions'.
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.