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Scrape Grok

scrape_grok
Read-only

Submit a prompt to Grok (xAI) from a chosen country (and optionally US state) and return the answer with cited sources. Use this to see how Grok (xAI) answers a prompt and which brands/sources it mentions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoOptional state code for state-level targeting (e.g. "CA" when country is "US"). Only some countries support this — call list_states for the supported countries and their codes.
promptYesThe prompt to submit to Grok (xAI).
countryYesISO 3166-1 alpha-2 country code to geo-target the request from (e.g. "US"). Use list_countries to see supported codes per model.
includeNoOptional flags to include heavier payload fields in the response. Leave unset for the leanest response.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover readOnlyHint, openWorldHint, and destructiveHint, so the bar is lower. The description adds useful behavioral context beyond those annotations: the prompt is geo-targeted and the response includes cited sources and brand/source mentions. It does not discuss rate limits or payload details, but those are partially covered by the input schema.

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 two tight sentences that immediately state what the tool does and when to use it. There is no filler, repetition, or tangential detail.

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 the schema already documents all parameters and the annotations cover safety traits, the description does enough to orient an agent. It clearly explains result content (answer with cited sources), but does not specify response formatting or the support/country validation workflow beyond the schema. Still, the combination of schema, annotations, and description is reasonably complete.

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?

The input schema provides 100% coverage of parameters with descriptions for prompt, country, state, and include. The tool description adds general behavioral context (geo-targeting and cited sources) but no additional parameter-specific meaning beyond the schema. Baseline 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 clearly names the action (submit/prompt), the target resource (Grok/xAI), and the differentiating characteristic (geo-targeting country/state, returning cited sources). It distinguishes itself from sibling scrape_* tools by specifying Grok as the source.

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?

"Use this to see how Grok (xAI) answers a prompt and which brands/sources it mentions" gives a clear reason to choose this tool. It does not explicitly say when not to use it or name alternatives, but the usage context is strong enough to avoid major confusion with sibling tools.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct engine or product (ChatGPT, Copilot, Gemini, Google, Google News, etc.), and the descriptions clearly specify what each scrape returns. The only potential overlap is between Google search and Google AI Mode, but the descriptions separate them effectively.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern: list_* for metadata and scrape_* for retrieval operations. The engine-specific names like scrape_chatgpt and scrape_google_ai_mode are predictable and easy to group.

Tool Count5/5

Ten tools is a well-scoped size for a geo-targeted search and AI answer scraping server. Each tool covers a meaningful engine or metadata requirement without excessive redundancy.

Completeness4/5

The tool surface covers major AI assistants, Google search variants, news, and supporting geo-targeting metadata. Minor gaps exist such as no standalone Bing/DuckDuckGo scraper or explicit engine model listing, but the core workflows are well supported.

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