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Coinslot — the vending machine for machines

Read Page

read_page

Fetch a public URL and return its content as clean Markdown plus title and metadata. One call instead of fetch + parse + convert. POST { url, maxBytes? } (default 1MB cap). Price: $0.005/call with credits key; free demo without (2KB input cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL
maxBytesNo

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does a good job: it discloses the POST method, default 1MB cap, and pricing/demo limits. It also notes the tool requires a public URL and returns metadata, but it doesn't detail error handling or rate limits, which keeps it from a 5.

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 three tightly packed sentences: the core purpose, the request structure, and pricing. Every sentence provides distinct, valuable information with no redundancy or filler, and it is front-loaded with the main function.

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 only two simple parameters and no output schema, the description conveys the return type (Markdown plus title/metadata), input constraints, and even pricing. Minor gaps like specific metadata fields and error behavior remain, but overall the description is complete enough for an agent to select and call the tool correctly.

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 coverage is only 50%, so the description adds value by showing the request shape 'POST { url, maxBytes? }' and explicitly mentioning the default 1MB cap. This helps clarify the `maxBytes` parameter beyond the schema's minimum/maximum values, though it doesn't fully explain its meaning as the response size limit.

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 states a specific verb ('Fetch a public URL') and resource, plus the output ('clean Markdown plus title and metadata'). It distinguishes itself from sibling tools by emphasizing 'One call instead of fetch + parse + convert', clearly differentiating from tools like `html_to_markdown` and `convert`.

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

Usage Guidelines4/5

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

The description implies when to use the tool ('One call instead of fetch + parse + convert'), giving context that it replaces a multi-step process. It also mentions the free demo vs. paid credits, which is an important usage consideration, but it doesn't explicitly state when NOT to use it relative to alternatives like `html_to_markdown`.

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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TDQS

A4.1/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness4/5

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.

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