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capcut_add_karaoke_captions

Add Hormozi-style karaoke captions to a CapCut draft by syncing word timestamps so the active spoken word lights up in gold or green.

Instructions

Add viral Hormozi-style karaoke captions where the active spoken word lights up in bright gold/yellow (#FFD700) or electric green (#00FF66). word_timestamps_json: JSON string of [{"word": "Stop", "start_ms": 0, "end_ms": 250}, ...]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draft_nameYes
highlight_colorNo#FFD700
words_per_chunkNo
word_timestamps_jsonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It conveys the visual effect and the highlight colors, but says nothing about whether it replaces existing captions, what permissions/draft state are required, or how it behaves with the existing timeline for what is clearly a mutating tool.

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?

Compact and front-loaded: one sentence on the effect followed by a single-line format example. No filler, though the schema-format line could be tighter.

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?

An output schema exists, so return values need not be explained, and the key timestamp format is given. However, the absence of annotations plus undocumented draft_name/words_per_chunk and no when-to-use routing leaves meaningful gaps for a mutating, multi-parameter tool.

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?

Schema coverage is 0%, so the description must compensate. It does document the critical word_timestamps_json with a concrete example and explains the two supported highlight colors, but leaves draft_name and words_per_chunk completely undocumented, so it only partially covers the four parameters.

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?

States a specific verb (Add) and resource (karaoke captions) and describes the distinguishing visual behavior: the active spoken word lights up in a highlight color. This implicitly separates it from the sibling capcut_add_captions, though it never names that sibling explicitly.

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?

There is no explicit when-to-use guidance and no comparison to the obvious alternative capcut_add_captions or the other overlay/badge tools. The usage is only inferable from the stylistic description ('viral Hormozi-style'), which leaves the agent guessing when this is preferred over plain captions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.