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Summarize Paragraphs

summarize_paragraphs

Condense each paragraph into extractive summaries with an optional shared token limit and per-paragraph sentence cap, making long text easier to scan.

Instructions

Extractively summarize each paragraph; optionally apply a shared approximate token limit.

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": {
      "paragraphs": "<paragraphs>"
    },
    "name": "summarize_paragraphs"
  }
}

Input Schema

Name	Required	Description	Default
`max_tokens`	No
`paragraphs`	Yes
`max_sentences_per_paragraph`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 10, 2026

TDQS

C2.9/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden; it does usefully disclose that summarization is extractive (output is drawn from the input) and that the token budget is shared and approximate across paragraphs. It says nothing about ordering, how truncation is applied per paragraph, or failure behavior on empty input.

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?

One tightly packed sentence with the core verb and unit of work front-loaded and no filler. The terseness is achieved partly by omitting parameter coverage, so it is efficient rather than exemplary.

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

Completeness2/5

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 extractive/shared-budget details are welcome. But for a three-parameter tool with zero schema descriptions and no annotations, leaving max_sentences_per_paragraph unexplained leaves an agent guessing at a key knob.

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

Parameters2/5

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

Schema description coverage is 0% for three parameters, so the description must compensate and only partly does: it clarifies that max_tokens is optional, shared across paragraphs, and approximate. It never mentions max_sentences_per_paragraph or its default of 2, leaving a meaningful control entirely undocumented.

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 mode ("extractively summarize") plus the exact unit of work ("each paragraph"), which meaningfully distinguishes it from a whole-text summarizer. It never names a sibling such as summarize_text, so the differentiation is implied by the word "paragraphs" rather than stated.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance; an agent must infer from "each paragraph" that this is for per-paragraph summarization while summarize_text handles whole documents. The clause about an optional token limit is a capability statement, not routing advice.

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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