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shell-as-mcp

by meomeo-dev

ffmpeg__mix_audio_tracks

Combine voice and background music into a single audio file, with adjustable volume and duration settings.

Instructions

Mix two audio tracks (voice and background music) into a single output using the amix filter. @remarks Typical use: normalize voice first, then mix with BGM using a low bgm_volume (0.2–0.3). Returns JSON in stdout with output_path and applied volume parameters. @param voice_path Primary audio track path (for example voice or narration). @param bgm_path Background music track path. @param output_path Destination mixed audio path. @param voice_volume Volume multiplier for the primary track. Default 1.0. @param bgm_volume Volume multiplier for the background music track. Default 0.3. @param duration Output duration strategy: shortest (default), longest, or first. @param __mcp_response_mode Optional response mode: content (default) or structuredContent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bgm_pathYes
durationNo
bgm_volumeNo
voice_pathYes
output_pathYes
voice_volumeNo
__mcp_response_modeNocontent
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the output format ('Returns JSON in stdout with output_path and applied volume parameters') and default volume values, which is valuable. It does not mention potential failure modes or file overwrite behavior, but overall it provides meaningful behavioral insight.

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 primary action, followed by a useful 'remarks' note and then a structured parameter list. Each sentence adds value, though the @param list is lengthy; however, this is justified given the schema has no descriptions.

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?

Despite having no output schema or annotations, the description covers core behavior, parameter semantics, and return format. It lacks details on edge cases (e.g., file overwrite, invalid paths) but is sufficiently complete for an agent to use the tool correctly in typical scenarios.

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?

Schema description coverage is 0%, but the description compensates fully with @param annotations for all 7 parameters, including defaults and allowed values (e.g., duration strategy and __mcp_response_mode). This goes well beyond the schema and directly supports correct invocation.

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 a specific verb ('Mix'), the resource ('two audio tracks'), and mechanism ('amix filter'), distinguishing it from sibling tools like ffmpeg__normalize_audio and ffmpeg__concat_clips. It leaves no ambiguity about the tool's function.

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 a 'Typical use' workflow ('normalize voice first, then mix with BGM using a low bgm_volume'), which gives clear context for when to apply this tool. It does not explicitly name alternatives or state when not to use it, but the context is enough to guide an agent.

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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