api

Summarize URL

url.summarize

Read-only

Fetch a public HTTPS URL and return a prose summary with key points. Lean mode — no bundle stored. Use when you need a condensed understanding of a web page. For raw text, use url.extract. For asking a specific question about a page, use url.qa. Returns: { url, summary, key_points: string[], truncated: boolean, word_count } Example prompts:

"Summarize https://en.wikipedia.org/wiki/Artificial_intelligence for me."
"Give me the key points from this blog post: [URL]."
"What is this article about? Summarize [URL]."

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes	Public HTTPS URL to fetch and summarize. Example: "https://en.wikipedia.org/wiki/Artificial_intelligence"
`max_tokens`	No	Input length cap (1 token ≈ 4 chars). Truncates fetched page content, not the output summary. Example: 4000

Output Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes
`summary`	No
`truncated`	Yes
`key_points`	No
`word_count`	No

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds that the tool is 'Lean mode — no bundle stored' (no persistence) and that it truncates fetched page content based on max_tokens. This provides useful behavioral context beyond annotations.

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?

Description is 4 sentences plus a return type list. Core action is front-loaded. Example prompts are helpful but could be condensed. No extraneous 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?

With an output schema present, the description provides sufficient context: usage, alternatives, limitations (truncation), and return structure. Covers all necessary aspects.

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%. The description adds meaning by explaining max_tokens: 'Input length cap (1 token ≈ 4 chars). Truncates fetched page content, not the output summary.' Also provides example prompts showing typical usage.

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 fetches a public HTTPS URL and returns a prose summary with key points. It distinguishes from siblings by mentioning 'Lean mode — no bundle stored' and contrasts with url.extract (raw text) and url.qa (specific questions).

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 states when to use: 'Use when you need a condensed understanding of a web page.' Provides clear alternatives: 'For raw text, use url.extract. For asking a specific question about a page, use url.qa.'

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

A4.4/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose, with no overlap. The category prefixes (account, bundle, collection, document, job, receipt, url) and specific action names (get, notarize, verify, create, list, etc.) ensure that an agent can unambiguously select the correct tool for any task.

Naming Consistency5/5

All tools follow a consistent category.action or category.action_noun pattern using snake_case (e.g., bundle.get, collection.add_document, url.translate). No mixed conventions or irregular names, making the pattern predictable and easy to learn.

Tool Count4/5

With 22 tools, the set is somewhat large but each tool addresses a distinct need within a broad domain (evidence management, document AI, collections, URL processing, job tracking, receipts). The count is slightly above the typical well-scoped range but still reasonable given the scope.

Completeness2/5

The tool surface has notable gaps: there is no tool to create or delete an evidence bundle, nor to update collections or bundles. The core workflow of creating a bundle from a document is missing, and the lifecycle is incomplete, which would likely cause agent failures in typical use cases.

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