Skip to main content
Glama
kud
by kud

upload-caption

Upload a caption track from a local file (SRT/VTT/SBV/TTML) to a YouTube video, specifying language, track name, and optional draft status.

Instructions

Upload a new caption track from a local file (SRT/VTT/SBV/TTML). Costs 400 quota units.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesTrack name shown to viewers
isDraftNoWhether the track is unpublished
videoIdYesVideo ID
filePathYesAbsolute local path to the caption file
languageYesBCP-47 language code, e.g. en
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 burden. It discloses a specific behavioral trait—'Costs 400 quota units'—and clarifies the file must be local. However, it omits other important context such as permissions required, whether the upload is irreversible, or what the response (e.g., a track ID) would be. This is partial disclosure, not comprehensive.

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?

The description is a single sentence that immediately states the action and key constraints, with no filler or redundancy. Every element earns its place, and the quota cost is concise and useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, no output schema, and no annotations. The description covers the core purpose and one major behavioral detail (quota cost), but does not explain expected return values, prerequisites (e.g., video existence), or error scenarios. Given its complexity, the description is adequate but not fully complete.

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?

The input schema covers 100% of parameters with individual descriptions, so the baseline is 3. The tool description adds context about supported file formats (SRT/VTT/SBV/TTML) and that the file is local, which slightly enriches filePath but does not materially alter understanding of the other parameters. The schema already does the heavy lifting.

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 action ('Upload a new caption track'), the resource ('caption track'), and the source ('from a local file'), listing supported formats. It distinguishes this from sibling tools like list-captions, update-caption, download-caption, and delete-caption by specifying it creates a new track.

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 provides clear context: use this when uploading a new caption track from a local file, with supported formats and quota cost. It does not explicitly mention alternatives or exclusions (e.g., use update-caption for existing tracks), but the 'new' keyword implies the use case. This is clear context without explicit exclusions.

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/kud/mcp-youtube'

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