Skip to main content
Glama

analyze-audio-waveform

Extract normalized amplitude data and peak times from audio files for waveform-driven animation in After Effects.

Instructions

Analyze an audio file to extract waveform amplitude data and detect peaks/transients. First call get-audio-info to retrieve the sourceFilePath, then pass it here. Returns normalized amplitude values (0-1) at evenly spaced time intervals plus an array of peak times where transients are detected. Uncompressed PCM WAV is read natively; any other format (mp3, m4a/aac, ogg, flac, a video file's audio track, ...) is transcoded on the fly via ffmpeg if it is installed and on PATH (override its location with the AE_FFMPEG_PATH env var).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesAbsolute path to the audio file (obtained from get-audio-info sourceFilePath). WAV works with no extra dependency; other formats need ffmpeg installed.
numPointsNoNumber of amplitude samples to return (default: 200). Higher = more detail.
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses that uncompressed PCM WAV is read natively, other formats are transcoded via ffmpeg if installed, and mentions the AE_FFMPEG_PATH env var override. Also describes return values: normalized amplitude values (0-1) and peak times.

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?

Three sentences with clear front-loading of purpose. The second sentence is instructional but not verbose. Could be slightly more structured, but overall concise with no wasted words.

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

Completeness5/5

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

Given no output schema and no annotations, the description comprehensively covers dependencies, format handling, env var, and output structure. Addresses all needed context for agent to invoke correctly.

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?

Schema coverage is 100%, so baseline is 3. The description adds context: filePath should come from get-audio-info, numPoints default is 200 and max 100000. It also explains return values beyond schema, but the schema already covers parameter details well.

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?

Clearly states the tool analyzes audio to extract waveform amplitude data and detect peaks/transients. The verb 'analyze' paired with resource 'audio-waveform' is specific and distinguishes it from sibling tools like set-audio-levels or add-any-effect.

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

Usage Guidelines5/5

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

Explicitly instructs to first call get-audio-info to obtain the sourceFilePath, then pass it here. Also details format handling (WAV native, others need ffmpeg) and env var override, providing clear when-to-use guidance.

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/a-y-ibrahim/after-effects-mcp'

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