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Compare URLs side-by-side

compare
Read-onlyIdempotent

Fetch 2-5 URLs concurrently and return per-URL excerpts, enabling side-by-side evaluation of multiple sources against a single question in one round trip.

Instructions

Fetch 2-5 URLs concurrently and return per-URL excerpts so the LLM can compare them against a single question in one round trip.

Best for:
- Side-by-side product/feature/article comparisons.
- "Compare X to Y" or "How does A differ from B" queries.
- Triangulating a fact across multiple sources.

Not recommended for:
- >5 URLs -> use `fetch_batch`.
- 1 URL -> use `fetch`.
- Don't have URLs yet -> use `search` or `research` first.

Returns:
- markdown (default): a comparison brief with per-URL sections, each
  containing title, sitename, published date, and a smart-truncated excerpt.
- json: {question, urls, excerpts:[{url, title, excerpt, ...}],
  tokens_estimated}.

Common mistakes:
- Asking `compare` to actually answer the question — it returns material,
  the LLM does the comparison.
- Passing >5 URLs and expecting them all to fit in context — use
  `fetch_batch` for bulk reads.

Args:
    question: The comparison question the LLM will answer using the
        returned excerpts.
    urls: 2-5 absolute http(s) URLs.
    format: "markdown" (default) or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
formatNomarkdown
questionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Even with annotations declaring readOnlyHint and idempotentHint, the description adds valuable behavioral context: concurrent fetching, smart truncation, returned formats (markdown/json), tokens_estimated, and the common mistake that `compare` does not itself answer the question. No contradictions with annotations.

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?

The description is long but every sentence earns its place. It is structured with clear sections (Best for, Not recommended for, Returns, Common mistakes, Args), making it scannable and informative without redundancy.

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?

For a tool with 3 parameters and an output schema, the description covers all necessary context: use cases, limits, return formats, and common pitfalls. It is fully self-contained and an agent can invoke it correctly without needing external information.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates with an 'Args' section explaining each parameter, including the default for `format`, the 2-5 URL constraint, and that `question` is the comparison question. This adds meaning well beyond the bare 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?

The description leads with a specific verb+resource+scope: 'Fetch 2-5 URLs concurrently and return per-URL excerpts'. It clearly differentiates from siblings by explicitly naming use cases and not-recommended cases, such as using fetch_batch for >5 URLs and fetch for 1 URL.

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?

Usage guidance is exemplary: it lists exact scenarios for use ('Compare X to Y', 'Triangulating a fact') and explicitly names alternatives (fetch_batch, fetch, search, research) with conditions. This leaves no ambiguity about when to invoke this tool.

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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