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summarize

summarize
Read-only

3 free MCP calls per day (all tools together), then $0.004 USDC via x402 or card credits (paid in-band: params._meta["x402/payment"]). Text summarizer: summarize up to 12,000 characters into 3-6 bullet points or one paragraph (max_words 20-250, optional output language). Small LLM (Workers AI Llama 3.1 8B), facts only from the text. GET query or POST JSON body. When to use: Use summarize to condense long text into bullets or a paragraph.

Input Schema

NameRequiredDescriptionDefault
langNooptional output language
textYestext to summarize (max 12,000 chars)
styleNo
max_wordsNo20-250, default 80

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

Annotations only declare readOnlyHint and openWorldHint; the description adds substantial context beyond them: quota (3 free calls/day shared across tools), price ($0.004 USDC) and the in-band payment mechanism via params._meta["x402/payment"], the underlying model (Llama 3.1 8B), a facts-only grounding constraint, and both GET and POST invocation forms.

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

Conciseness3/5

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

It is a single dense paragraph with no filler, but it leads with billing rather than the tool's function, and the closing 'When to use' sentence is pure restatement of the earlier definition. Some of the length is duplication rather than information.

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?

An output schema exists, so return values need not be explained, and the description covers the remaining gaps an agent needs: cost, payment path, transport, input limits and the model's grounding behavior. Error or insufficient-payment behavior is the only notable omission.

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 75%, so most parameters are already documented, but the description adds real meaning: the 3-6 bullet output shape that the 'style' enum does not describe anywhere, and the text length ceiling restated as a hard limit. The lang and max_words details largely duplicate the schema.

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 (text summarizer) plus concrete scope: up to 12,000 characters in, 3-6 bullets or one paragraph out, 20-250 words. No sibling tool (classify, entity_extract, translate) does condensing, so the agent can distinguish it 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 Guidelines3/5

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

The 'When to use' sentence only restates the purpose ('condense long text into bullets or a paragraph') rather than giving conditions or naming alternatives. The useful routing context it does supply is commercial: 3 free calls per day across all tools, then paid.

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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