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by io.github.Nutshell2000
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Summarize text API: short summary and key points from any text

ai_summarize
Read-only

Summarize text with an LLM: send up to 12,000 characters and get a short summary plus bullet key points. Use for long emails, articles, transcripts, meeting notes and tool outputs; for a web page by URL use /summarize. Price $0.01/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>"
    },
    "name": "ai_summarize"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesText to summarize, up to 12,000 characters
sentencesNoSummary length in sentences, 1-8 (default 3)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/destructive/idempotent, and the description adds genuinely new context beyond them: the 12,000-character ceiling, pricing ($0.01/call via x402 USDC or card key), 25 free calls, and that failed calls are free. The note that "each call is charged, so repeats are not free" usefully reinforces idempotentHint=false in operational terms.

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?

Two dense sentences that lead with what the tool does and what you get back, then pack limits, alternatives, and billing. The billing clause is somewhat crammed with semicolons, but each clause carries usable information for an agent deciding whether to call.

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 2-parameter tool with no output schema, the description covers return shape, input size limit, cost, and use cases. Minor gaps remain: it doesn't say whether oversized text is rejected or truncated, and doesn't clarify the overlap with ai_summarize_text.

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 both parameters including the 1-8 sentence range and default. The description repeats the 12,000-character limit (already in the schema) and never mentions the `sentences` parameter, so it adds no meaning beyond the structured data.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Summarize text with an LLM") plus the exact output shape: "a short summary plus bullet key points." The alternative routing sentence refers to an HTTP endpoint "/summarize" rather than the sibling tool name ai_summarize_text, which leaves the differentiation slightly ambiguous even though the intent (URL input goes elsewhere) is clear.

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 concrete positive use cases ("long emails, articles, transcripts, meeting notes and tool outputs") and an explicit exclusion for web pages by URL. It does not address the obvious sibling ai_summarize_text, which appears to overlap heavily, so the when-not guidance is incomplete against the sibling list.

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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