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remote_code_execution

Execute Python code remotely in xAI's server-side sandbox, leveraging Grok to solve tasks securely without local execution.

Instructions

Solve a task by letting Grok write and run Python in xAI's server-side sandbox.

Renamed from code_executor — it invokes xAI's remote code_execution tool; no code runs on this machine.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
max_turnsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoStructured payload for web_search / x_search / code_execution.
textNoHuman-formatted output (includes footers, citations, cost summary).
modelYesActual executing model ID (e.g. 'grok-4.5').
planeNoAPI
routeYesHigh-level route (fast/agentic/research/etc.).
tokensNoTotal tokens consumed.
profileNoInternal routing profile.
cost_usdNoExact USD cost from xAI billing metadata.
responseYesRaw model output or primary content.
citationsNoNative xAI/X citations with URL + snippet.
latency_secNo
finish_reasonNounknown
reasoning_effortNoGrok 4.5+ native reasoning level.
Behavior2/5

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

No annotations provided, so the description must disclose behavioral traits. It mentions server-side sandbox and that no code runs locally, but omits crucial details like destructiveness, security implications, error handling, or execution limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the main purpose. However, the rename note could be omitted or integrated more concisely. Overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the tool's complexity (code execution) demands more context on security, permissions, execution limits, and error handling. The description is too sparse for complete understanding.

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

Parameters1/5

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

Schema description coverage is 0%, yet the description does not explain the 'prompt' (what it expects) or 'max_turns' (its meaning and default null). This fails to add value beyond the schema.

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 lets Grok write and run Python in a sandbox, which is specific and differentiates it from sibling tools like 'agent' or 'chat'. It also notes the rename from 'code_executor' for context.

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

Usage Guidelines3/5

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

The description implies usage for solving tasks via code execution, but lacks explicit when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned despite many 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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