audio-analysis

audio-analysis is a skill for Claude Code from danielrosehill/Claude-Video-Editor-Plugin. It costs 96 tokens per session (1,180 once invoked), scanned A, original, MIT.

An audio-measurement helper that checks how loud a video or audio file is. It reports LUFS, a standard measure of perceived loudness, along with peak levels and loudness variation.

In plain words
What is it for?
Use it to extract audio from video, measure loudness, and decide whether normalization is needed.
Why use it?
It shows whether audio matches common targets for YouTube, podcasts, broadcast, or Spotify before you adjust it.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the video-editing plugin — 40 skills shipped together

Good fit Use it to extract audio from video, measure loudness, and decide whether normalization is needed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/danielrosehill/claude-video-editor-plugin/audio-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add danielrosehill/Claude-Video-Editor-Plugin --skill audio-analysis
Clone the repo
git clone --depth 1 https://github.com/danielrosehill/Claude-Video-Editor-Plugin

Made for: Claude Code.

Or install video-editing, the plugin that ships this one along with the rest of its 40 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for audio-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/danielrosehill/claude-video-editor-plugin/audio-analysis.svg)](https://agentmods.dev/skills/danielrosehill/claude-video-editor-plugin/audio-analysis)
Your own site
<a href="https://agentmods.dev/skills/danielrosehill/claude-video-editor-plugin/audio-analysis"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-video-editor-plugin/audio-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,180 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.01180
Opus 5 $0.00048 $0.00590
Sonnet 5 $0.00019 $0.00236
Haiku 4.5 $0.00010 $0.00118

Measured 7d ago against content hash 62911f99232e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

audio-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/audio-analysis/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audio Analysis

Pull the audio out of a video (or take a standalone audio file) and run an EBU R128 loudness pass. Output is a short markdown report with LUFS / dBTP / LRA and a recommendation against a chosen target.

This skill does not normalize. Apply normalization separately (with transcode or a future normalize-audio skill) once you've decided on a target.

Procedure

1. Inputs

Field Default
Source required (video or audio)
Mode extract / analyze / both (default both)
Target youtube (-14 LUFS / -1 dBTP) / broadcast (-23 / -2) / podcast (-16 / -1) / streaming-spotify (-14 / -1)
Output dir sibling audio/ (or project's assets/ if inside an index project)

2. Extract

If the source is a video, pull the audio. Prefer stream-copy when the codec is sane (aac/opus/flac/mp3); otherwise re-encode to wav for analysis.

CODEC=$(ffprobe -v error -select_streams a:0 -show_entries stream=codec_name -of csv=p=0 "$SRC")
case "$CODEC" in
  aac|mp3|opus|flac) EXT="$CODEC"; ARGS="-vn -acodec copy" ;;
  *)                 EXT="wav";    ARGS="-vn -ac 2 -ar 48000 -c:a pcm_s24le" ;;
esac
mkdir -p "$OUT_DIR"
EXTRACTED="$OUT_DIR/$(basename "${SRC%.*}").$EXT"
ffmpeg -hide_banner -y -i "$SRC" $ARGS "$EXTRACTED"

3. Analyze (ebur128)

ffmpeg -hide_banner -nostats -i "$EXTRACTED" -af 'ebur128=peak=true:framelog=quiet' -f null - 2>&1 | tail -25

Parse the summary block at the end:

[Parsed_ebur128_0 @ ...] Summary:
  Integrated loudness:
    I:         -18.4 LUFS
    Threshold: -28.5 LUFS
  Loudness range:
    LRA:         8.1 LU
    Threshold: -38.5 LUFS
    LRA low:   -22.2 LUFS
    LRA high:  -14.1 LUFS
  True peak:
    Peak:       -1.3 dBFS

Pull I (integrated), LRA, and Peak with grep/awk.

Also probe stream metadata:

ffprobe -v error -select_streams a:0 -show_entries stream=codec_name,sample_rate,channels,bits_per_sample -of default=nw=1 "$SRC"

Read the full file on GitHub · 108 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 108 lines · 96 tokens per session scan A 62911f99232e

Subscribe to this mod's changes

audio-analysis is a skill published in the GitHub repository danielrosehill/Claude-Video-Editor-Plugin (5 stars, last pushed 4mo ago), licensed MIT. It adds 96 tokens to every session and 1,180 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

webgl-holographic-foil

A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.

nexu-io/open-design · 41 tokens

general-video

Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…

heygen-com/hyperframes · 92 tokens

html-ppt-hermes-cyber-terminal

OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.

nexu-io/open-design · 53 tokens

html-ppt-taste-brutalist

16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).

nexu-io/open-design · 78 tokens

diagnostic-stem-delivery

Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.

HKUDS/OpenSpace · 23 tokens

chengfeng-check-updates

An environment manager for a video-editing system. It checks whether its skills and runtime—the software needed to run them—are installed and compatible.

Agentchengfeng/chengfeng-videocut-skills · 120 tokens