Skip to main content
Glama

ask_grok

ask_grok

Ask xAI Grok 4.6 — fast, witty alternative take. ~$0.03.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesYour question

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

The description adds behavioral context beyond the annotations by noting the approximate cost (~$0.03), speed (fast), and tone (witty). It aligns with openWorldHint=true by implying the question is sent to xAI's external service. No contradictions with annotations exist.

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?

At just one sentence, the description is extremely concise and front-loaded, starting with the primary action 'Ask xAI Grok 4.6'. The rest of the sentence adds differentiating and cost info without fluff. Every word contributes value.

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 simple single-parameter tool with an output schema and annotations, this description is sufficient. The output format is presumably in the output schema, and the safety profile is covered by annotations. The cost and personality hints round out the contextual picture.

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 schema already covers the only parameter 'q' with 'Your question' at 100% coverage, so the description doesn't need to add much. The description implicitly defines what the question is by stating 'Ask xAI Grok', but offers no additional constraints or syntax. This meets the baseline for schema-heavy parameter documentation.

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 identifies the tool as an interface to xAI Grok 4.6, using 'Ask' as the verb and the model as the resource. The phrase 'alternative take' distinguishes it from sibling AI tools like ask_gpt and ask_gemini, making its niche obvious. It is specific and not a tautology.

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?

It gives contextual guidance by highlighting 'fast, witty alternative take', implying use when a quick, personality-driven answer is desired. However, it does not explicitly mention when not to use it or name alternatives, so there is room for more guidance. This is a clear context but lacks exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation2/5

Four image generation tools, three video tools, and five 'ask' tools create significant overlap. Although descriptions specify the model, an agent must carefully compare prices and capabilities to choose correctly, making misselection likely.

Naming Consistency3/5

All tool names use snake_case, but patterns are mixed: some start with verbs (remove_bg, scrape_page), some with nouns (crypto_prices, market_snapshot), and many use ai_/ask_ prefixes. Model suffixes like flux, gpt, pro, kling are descriptive but not systematically applied.

Tool Count3/5

24 tools is heavy, inflated by near-duplicate variants for image, video, and LLM queries. While the broad scope justifies a large count, the redundant tools could have been consolidated.

Completeness4/5

The toolset covers a wide range of media and data tasks: image, video, music, voice, vision, LLM, web, crypto, domain, and endpoint discovery. Notable gaps like speech-to-text or image editing exist, but the surface is fairly complete for a general-purpose media toolkit.

Resources