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Remotion Video Generator

by IBM
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

remotion_list_projects

View all available video projects in your Remotion workspace to manage and select templates for creating professional YouTube content.

Instructions

List all Remotion projects in the workspace.

Returns:
    JSON array of projects

Example:
    projects = await remotion_list_projects()

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/chuk_motion/server.py:341-357 (handler)
    Handler and registration for remotion_list_projects tool. Decorated with @mcp.tool. Returns JSON list of projects by calling project_manager.list_projects().
    @mcp.tool  # type: ignore[arg-type]
async def remotion_list_projects() -> str:
    """
    List all Remotion projects in the workspace.

    Returns:
        JSON array of projects

    Example:
        projects = await remotion_list_projects()
    """

    def _list():
        projects = project_manager.list_projects()
        return json.dumps(projects, indent=2)

    return await asyncio.get_event_loop().run_in_executor(None, _list)

Tool Definition Quality

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the return type ('JSON array of projects') but lacks details on pagination, error handling, permissions, or rate limits. This is inadequate for a tool with zero annotation coverage.

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 front-loaded with the core purpose, followed by return and example sections. It's efficient with minimal waste, though the example could be more informative (e.g., showing output structure).

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?

Given no annotations, no output schema, and a list operation that might involve pagination or filtering, the description is incomplete. It lacks behavioral context and doesn't compensate for the missing structured data, making it insufficient for reliable agent use.

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?

The tool has zero parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add any parameter details, which is appropriate, but it could have mentioned implicit constraints like workspace context. Baseline 4 is applied for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all') and resource ('Remotion projects in the workspace'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling list tools like 'remotion_list_components' or 'remotion_list_themes', which prevents a perfect score.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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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