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search_extract

Perform Google searches and extract full article content in parallel. Returns enriched SERP results with markdown text from each page, not just snippets. Isolates per-page failures. Useful for in-depth research without visiting each URL.

Instructions

Google search + parallel content extraction. Returns SERP results enriched with article markdown. Slower than search (extra ~2–5s) but gives you actual page content, not just snippets. Per-page failures are isolated (returned as { error } in that result).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query
limitNoNumber of results to extract (default 5)
max_charsNoTruncate each result content (default 8000)
Behavior4/5

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

With no annotations, the description carries full responsibility and discloses key behaviors: parallel extraction, per-page failure isolation, and a performance overhead estimate. It could further mention if there are any rate limits or authorization requirements, but the provided details are sufficient for understanding the tool's behavior.

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 highly concise, consisting of two sentences that cover the core functionality, a performance comparison, and error handling. Every sentence adds unique value with no redundancy.

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?

Given no output schema and the tool's complexity (search + extraction), the description adequately explains the return format (enriched markdown) and failure handling. It could include more detail about the result structure, but the core information is present.

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?

All three parameters ('query', 'limit', 'max_chars') are fully described in the input schema with types, ranges, and defaults. The description adds no additional meaning to the parameters beyond what the schema provides, meeting the baseline for high schema coverage.

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 performs Google search combined with parallel content extraction and returns SERP results enriched with article markdown. It distinguishes from sibling 'search' by mentioning it provides actual page content instead of snippets, making the purpose unambiguous.

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 explicitly notes it is slower than 'search' by 2-5 seconds, providing a clear trade-off for when to use this tool versus the faster alternative. However, it does not address when to use sibling tools 'extract' or 'search_parallel', leaving some gaps.

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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