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orgo_list_projects

Read-onlyIdempotent

List all projects in your Orgo account with names and IDs to manage computers. Supports pagination and returns results in markdown or JSON format.

Instructions

List all Orgo projects in your account.

Returns project names and IDs with pagination support. Use project names
with orgo_list_computers or orgo_create_computer to manage computers.

Args:
    params (ListProjectsInput): Input parameters containing:
        - limit (int): Maximum results to return, 1-100 (default: 20)
        - offset (int): Number of results to skip for pagination (default: 0)
        - response_format (ResponseFormat): 'markdown' or 'json' (default: markdown)

Returns:
    str: Formatted response containing:

    Markdown format:
        # Orgo Projects
        Found X projects (showing Y)

        ## project-name (proj_123)
        - **Created**: 2024-01-15 10:30:00

    JSON format:
        {
            "total": int,
            "count": int,
            "offset": int,
            "has_more": bool,
            "next_offset": int | null,
            "projects": [{"id": str, "name": str, "created_at": str}]
        }

Examples:
    - "List my Orgo projects" -> orgo_list_projects with defaults
    - "Show next page of projects" -> orgo_list_projects with offset=20

Error Handling:
    - Returns "Error: Invalid API key..." if ORGO_API_KEY is invalid
    - Returns "No projects found" if account has no projects

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 provide readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true. The description adds valuable behavioral context beyond annotations: it explains pagination support, error handling (e.g., invalid API key, no projects), and the two response formats (markdown and JSON), which are not covered by annotations.

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 well-structured with clear sections (Args, Returns, Examples, Error Handling) and front-loaded purpose. It is appropriately sized but could be slightly more concise by integrating some details more tightly, though all sentences add 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?

Given the tool's complexity (pagination, multiple formats), the description is complete: it covers purpose, usage, parameters, return values (including both markdown and JSON formats), examples, and error handling. With annotations and a detailed description, no gaps remain for effective tool use.

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

Parameters5/5

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

With schema description coverage at 0%, the description fully compensates by detailing all parameters (limit, offset, response_format) with their meanings, constraints (e.g., limit 1-100), defaults, and enum values. It provides clear semantics that the schema lacks, making parameters understandable.

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's purpose with specific verb ('List') and resource ('all Orgo projects in your account'), distinguishing it from siblings like orgo_get_project (singular) and orgo_create_project (creation). It immediately communicates the scope and action.

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?

The description provides explicit guidance on when to use this tool versus alternatives: it mentions using project names with orgo_list_computers or orgo_create_computer to manage computers, and includes examples like 'List my Orgo projects' and 'Show next page of projects' that clarify typical use cases.

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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