QuickBuild token-saver tools + x402

Summarize URL or text to JSON brief

summarize

Read-onlyIdempotent

[PAID $0.02 USDC per call via x402 on Base; errors are free] Fetch a public web page (or take raw text) and return a structured JSON brief made by Llama 3.3 70B: title, language, contentType, summary, keyPoints, named entities with types, topic tags, concrete facts (prices, dates, versions, limits) as label/value pairs, sentiment and audience. Grounded in the page only, no invented facts. Reads up to 24,000 chars of main content (2 MB HTML, 10 s fetch timeout). All params optional: with none it summarizes https://example.com. GET with query params, or POST a JSON body for long text (up to 200,000 chars accepted, first 24,000 analyzed).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "summarize"
  }
}

Input Schema

Name	Required	Description
`url`	No	Public http(s) URL to read (hostname, not IP; private addresses refused). Optional: defaults to https://example.com. Ignored when `text` is given.
`lang`	No	Optional output language for summary/keyPoints (ISO 639-1, e.g. "en"). Default: same as the content.
`text`	No	Raw text or Markdown to summarize instead of a URL (optional, max 200000 chars, first 24000 analyzed). Prefer POST for long text.
`focus`	No	Optional aspect to emphasize, e.g. "pricing", "API limits", "risks" (max 200 chars).
`length`	No	Summary length: short = 1-2 sentences, medium = 3-4 (default), long = 5-8.
`maxPoints`	No	Max number of keyPoints (default 5).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A4.4/5.0

Behavior5/5

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

With readOnly/idempotent/destructive annotations already covering the safety profile, the description adds substantial operational context the annotations do not: per-call pricing with free errors, a 24,000-char analyzed limit, 2 MB HTML cap, 10 s fetch timeout, refusal of private addresses, and grounding guarantees ('no invented facts'). This is exactly the behavioral detail an agent needs before incurring cost.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the critical cost signal and the core action in the first two clauses; every sentence carries information. It is a dense single paragraph with heavy parentheticals, slightly harder to scan than it could be, but not padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description compensates by enumerating the JSON brief's fields (title, language, contentType, summary, keyPoints, entities, tags, facts, sentiment, audience) plus size/time limits. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents url/lang/text/focus/length/maxPoints boundaries and defaults. The description largely reinforces these (all optional, default URL, POST for long text) rather than adding new per-parameter meaning, so the baseline 3 applies.

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?

States a specific verb and resource ('fetch a public web page or take raw text and return a structured JSON brief') and enumerates the exact output fields, which cleanly separates it from siblings like url_to_markdown, page_metadata, and website_audit. An agent can identify this as the LLM-backed structured-summary tool without opening the schema.

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?

Gives clear operating context: all params optional, no-param default is https://example.com, and POST is preferred for long text. It does not explicitly name alternative tools (e.g., when to prefer url_to_markdown or page_metadata over this) nor state exclusion conditions, so routing among siblings is left to inference.

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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