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fetch_batch

Read-onlyIdempotent

Fetch multiple URLs in parallel, with individual error handling. Ideal for reading several pages at once without failing the entire request.

Instructions

Fetch a list of URLs in parallel. Per-URL failures do not raise.

Best for:
- 2+ URLs you want to read in one round-trip.
- Reading the top N results of a previous `search` call.

Not recommended for:
- A single URL -> `fetch` (no list-wrapping overhead).
- "Search and then read" -> `research` collapses both into one tool call.
- PDFs/DOCX -> `read_doc` per file.

Returns:
- markdown (default): each page rendered as a Markdown section, separated
  by horizontal rules; failed URLs become inline error notes.
- json: list[dict], one entry per URL, with `error` set on failures.

Common mistakes:
- Passing a single URL inside a 1-element list — use `fetch` directly.
- Assuming an exception means the whole batch failed; check each item's
  `error` field instead.

Args:
    urls: List of absolute http(s) URLs.
    render: Same as `fetch`.
    format: "markdown" or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
renderNoauto
formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint. Description adds per-URL failure behavior, format-specific return structures, and common mistakes, significantly enriching behavioral context.

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?

Well-organized into sections (main, best for, not recommended, returns, common mistakes, args). Every sentence is informative and earns its place. No 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?

Given the tool's complexity (parallel batch, multiple formats, error handling), the description covers purpose, usage, parameters, return values, and pitfalls comprehensively. Output schema is implied via format descriptions. Annotations and description together provide full context.

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?

With 0% schema coverage, the description fully explains all parameters: 'urls' as absolute http(s) URLs, 'render' as same as fetch, 'format' with markdown vs json including return structure and error handling. Provides value beyond enum defaults.

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?

Description clearly states 'Fetch a list of URLs in parallel' with key behavior 'Per-URL failures do not raise.' This distinguishes it from siblings like 'fetch' (single URL) and 'research' (search+read).

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?

Explicit 'Best for:' and 'Not recommended for:' sections with specific use cases and alternatives ('fetch', 'research', 'read_doc'). Provides clear when-to-use guidance.

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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