Skip to main content
Glama
meomeo-dev

shell-as-mcp

by meomeo-dev

ass__smoke_test

Generates a short MP4 test video from an ASS subtitle file using ffmpeg to verify subtitles render correctly. Outputs a JSON summary on success or error details on failure.

Instructions

Render a short test video from an ASS subtitle file to verify renderability. @remarks Uses ffmpeg lavfi virtual color source to generate a background, then overlays the ASS subtitles via the subtitles filter (requires libass support in ffmpeg). Outputs a JSON summary on success or an error payload on failure. @param ass_file_path Path to the ASS subtitle file to render. @param output_path Path for the output MP4 video file. @param output_dir Optional output directory fallback for relative output_path. Falls back to ASS_OUTPUT_DIR or SHELL_AS_MCP_OUTPUT_DIR. @param duration_sec Duration of the test video in seconds (1-300). Default: 10. @param resolution Output video resolution in WxH format. Default: 1920x1080. @param background_color Background color for the test video (ffmpeg color name or hex). Default: black. @param __mcp_response_mode Optional response mode: content (default) or structuredContent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
output_dirNo
resolutionNo
output_pathYes
duration_secNo
ass_file_pathYes
background_colorNo
__mcp_response_modeNocontent
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It does disclose the ffmpeg lavfi virtual color source, the subtitles filter with libass dependency, and the output as a JSON summary or error payload. However, it omits important behavioral details such as whether the output file is overwritten, any permission requirements, or other side effects of writing files.

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 and then adds necessary mechanism and parameter details in a compact, organized structure. Each sentence contributes useful content with no filler, though the parameter list makes it slightly lengthy. Overall it earns its length.

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?

For a tool with 7 parameters and no output schema, the description covers the operation, dependencies, output success/failure format, and parameter semantics with defaults and ranges. It does not detail the JSON summary structure or overwrite policy, but it provides enough for an agent to invoke the tool correctly and understand what will happen.

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?

The input schema provides no descriptions (0% coverage), but the description's @param lines thoroughly document all seven parameters, including types, defaults, allowed ranges, and fallback behavior. For example, duration_sec is defined with a range of 1-300 and default 10, and output_dir's fallback chain is clearly described. This fully compensates for the schema gap.

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 opens with 'Render a short test video from an ASS subtitle file to verify renderability,' which names a specific verb, resource, and intended purpose. This clearly distinguishes it from sibling tools like ffmpeg__burn_subtitles by framing it as a smoke test for renderability rather than a final rendering step.

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

Usage Guidelines4/5

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

The description clearly states the use case: verifying renderability of an ASS subtitle file, and explains the ffmpeg lavfi/libass mechanism behind it. It does not explicitly name alternative tools or when-not-to-use conditions, but the smoke-test framing and sibling tool names provide enough context for an agent to understand when it should be used.

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/meomeo-dev/shell-as-mcp'

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