DocImprint

Summarize Document

document.summarize

Read-onlyIdempotent

Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts:

"Summarize this financial report and give me the key points."
"What are the main takeaways from this document?"
"Give me a concise summary of this 50-page report."

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Document text to summarize. Obtain via document.extract_text or url.extract. Example: "The Q4 2025 financial report shows revenue growth of 23% year-over-year..."
`max_tokens`	No	Input length cap (1 token ≈ 4 chars). Default ~3000 tokens. Truncates input, not output. Example: 4000

Output Schema

TableJSON Schema

Name	Required	Description	Default
`summary`	Yes
`strategy`	Yes
`truncated`	Yes
`key_points`	Yes
`summary_cited`	Yes
`key_points_cited`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds behavioral details: returns structured output with summary, key_points, truncated flag, and strategy field; truncates input based on max_tokens, not output. No contradictions.

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?

Description is front-loaded with the action, then usage guidelines, output format, and examples. Every sentence adds value—no fluff. Well-structured and easy to scan.

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?

Despite complexity (structured output with citations and truncation), the description covers output schema, typical workflow, and examples. It's complete for an agent to understand how and when to use the tool.

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 100% with good descriptions. The description adds example text, explains max_tokens as input cap with truncation behavior, and provides example prompts. This adds useful context beyond the schema, justifying a score above the baseline of 3.

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 clearly states the tool summarizes document text into a prose summary and key points with citations. It distinguishes from siblings by specifying when to use (after extract_text/url.extract) and when to use alternatives (url.qa, document.extract_structured).

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

Usage Guidelines5/5

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

Explicitly says to use after document.extract_text or url.extract, and provides alternatives for single-sentence Q&A (url.qa) and specific field extraction (document.extract_structured). The typical workflow is described.

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

A4.5/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose, grouped by domain (account, bundle, collection, document, job, receipt, url). Descriptions and naming make it easy to differentiate between similar tools like url.extract vs document.extract_text or collection.search vs collection.ask.

Naming Consistency5/5

All tools follow the same prefix.group_action pattern in snake_case (e.g., account.quota, bundle.get, collection.create). No mixing of conventions, making the API predictable and easy to navigate.

Tool Count5/5

With 22 tools, the server covers a comprehensive set of operations for document and evidence management. Each tool serves a specific purpose, and the count feels well-scoped without being bloated or sparse.

Completeness3/5

The tool surface lacks explicit create and delete operations for bundles and collections. Bundles appear to be created externally, and there is no tool to remove a bundle or collection. This is a notable gap given the server's stated purpose.

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