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Search + Parallel Extract

search_extract
Read-only

Search Google and extract abstracts or full text from top results. Use abstract mode for a quick relevance survey (~1500 chars per result) or full mode to retrieve complete article texts.

Instructions

One-shot Google search + parallel extract of the top results. Default mode="abstract" returns SERP enriched with ~1500-char abstracts per result -- a cheap survey of what the top results actually contain, far fewer tokens than fetching all bodies. Switch to mode="full" only when you need the actual article texts (slower, much more tokens). Per-page extract failures are isolated. Disabled in cloud mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoExtraction depth per result. `abstract` (default) = cheap survey, ~1500 chars/result, ideal for relevance triage. `full` = whole body per result, slower and far more tokens; only when you actually need the article texts.abstract
limitNoNumber of results to extract (default 5, max 10).
queryYesSearch query.
max_charsNoTruncate each result body. Default depends on mode: ~1500 for abstract, 8000 for full (SURF_EXTRACT_MAX_CHARS, capped at 20000 here).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaNo
errorNo
queryNo
resultsNo
elapsed_msNo
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds valuable behavior beyond this: per-page extract failures are isolated, cloud mode disables the tool, and mode affects token consumption. These details help the agent anticipate failure modes and cost, without contradicting any annotation.

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 three sentences, front-loaded with the core function, then elaborates on mode selection and constraints. Every sentence provides actionable information with no filler or repetition.

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?

The tool has an output schema, annotations, and a description that covers mode differences, token cost, failure isolation, and cloud limitation. This is complete for a combined search+extract tool with good structured metadata; nothing critical is missing.

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

Parameters3/5

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

Schema description coverage is 100%, with detailed descriptions for all parameters including mode trade-offs. The description reinforces the mode semantics but does not add significant meaning beyond what the schema already provides, so the baseline of 3 is appropriate.

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 opens with a specific verb+resource: 'One-shot Google search + parallel extract of the top results.' It clearly distinguishes this tool from siblings like search, search_parallel, and extract by combining both functions. The mode parameter is explicitly tied to the purpose, reinforcing clarity.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use abstract vs full mode, including trade-offs on tokens and speed ('far fewer tokens', 'only when you need the actual article texts'). It also notes that the tool is disabled in cloud mode. It does not name sibling tools as alternatives, but the usage context is clearly implied.

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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