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orgo_list_computers

Read-onlyIdempotent

List computers in a project to retrieve IDs, names, and status for use with action tools like screenshot, click, or bash commands.

Instructions

List all computers in a project.

Returns computer IDs, names, and status with pagination. Use computer_id
with action tools like orgo_screenshot, orgo_click, orgo_bash, etc.

Args:
    params (ListComputersInput): Input parameters containing:
        - project_name (str): Project name from orgo_list_projects
        - limit (int): Maximum results, 1-100 (default: 20)
        - offset (int): Skip for pagination (default: 0)
        - response_format (ResponseFormat): 'markdown' or 'json'

Returns:
    str: Formatted response containing:

    Markdown format:
        # Computers in project-name
        Found X computers (showing Y)

        ## dev-box (`comp_abc`)
        - **Status**: running
        - **OS**: linux
        - **RAM**: 4 GB | **CPU**: 2 cores

    JSON format:
        {
            "total": int,
            "count": int,
            "offset": int,
            "has_more": bool,
            "next_offset": int | null,
            "computers": [{"id": str, "name": str, "status": str, "os": str, "ram": int, "cpu": int}]
        }

Examples:
    - "List computers in my-project" -> params with project_name="my-project"
    - "Show running VMs" -> list then filter by status

Error Handling:
    - Returns "Project 'name' not found" if project doesn't exist
    - Returns "No computers found in project" if empty

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral context: pagination details, error handling for missing projects or empty results, and output format specifics (markdown vs JSON). This goes beyond annotations but doesn't mention rate limits or authentication needs.

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?

Well-structured with clear sections (Args, Returns, Examples, Error Handling) and front-loaded purpose. Some redundancy exists (e.g., repeating parameter details in schema-like format), but most sentences add value. Could be slightly tighter by integrating parameter details more seamlessly.

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?

Given the tool's complexity (listing with pagination and formatting), annotations cover safety, and the description thoroughly explains parameters, usage, output formats, errors, and examples. The output schema is present, so return values are adequately documented. No significant gaps remain for agent understanding.

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

Parameters4/5

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

Schema description coverage is 0%, so the description carries full burden. It documents all 4 parameters (project_name, limit, offset, response_format) with semantics, defaults, and constraints. However, it doesn't explain the ResponseFormat enum values beyond listing them, leaving some schema gaps.

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 specific action ('List all computers in a project') and resource ('computers'), distinguishing it from siblings like orgo_get_computer (single computer) and orgo_create_computer (creation tool). The title 'List Computers in Project' reinforces this purpose.

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 guidance is provided: 'Use computer_id with action tools like orgo_screenshot, orgo_click, orgo_bash, etc.' This tells the agent when to use this tool (as a prerequisite for those actions) and distinguishes it from filtering alternatives (e.g., 'Show running VMs' requires listing then filtering).

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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