Skip to main content
Glama

oz_agent_run_cloud

Launch a Warp Oz AI agent in the cloud to execute tasks from a natural-language prompt. Returns a run ID immediately for later status polling.

Instructions

Launch a Warp Oz AI agent in Warp's cloud (not on the local machine). ⚠️ CONSUMES WARP CREDITS — confirm with the user before calling. Returns the run id immediately WITHOUT waiting for completion; poll the terminal status and output with oz_run_get, or find the run later via oz_run_list. Requires the oz CLI on PATH and a Warp account with cloud credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoAI model id to use, from `oz_list_models`. Omit to use the configured default.
skillNoAgent skill id (e.g. `5-test-agent`). Omit to auto-select from the prompt.
promptYesNatural-language instruction for the cloud agent.
environmentNoCloud environment id or name to run in. Omit to use the configured default, or the first available environment.
Behavior4/5

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

Discloses key behavioral traits: credits consumed, returns immediately without waiting, requires CLI and account. No annotations to contradict. Could add details on error handling or limits, but covers main points well.

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?

Very concise with three front-loaded sentences covering purpose, warnings, and post-call behavior. No extraneous words.

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?

Covers invocation, post-call polling, and prerequisites. Without output schema, could specify return type more explicitly, but 'returns the run id' is sufficient.

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 has 100% description coverage, so baseline is 3. Description does not add significant meaning beyond what's already in 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?

Clearly states 'Launch a Warp Oz AI agent in Warp's cloud (not on the local machine)', specifying verb, resource, and location distinction from sibling tool oz_agent_run.

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

Usage Guidelines5/5

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

Explicit warning about credit consumption with user confirmation, instructions for post-call polling via oz_run_get, and prerequisites (oz CLI, Warp account with credits). Clearly differentiates from local run.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sena-labs/OzBridge'

If you have feedback or need assistance with the MCP directory API, please join our Discord server