Content & Media Creation · Leonxlnx/earshot
earshot
Listen with earshot whenever you must judge, choose, trim, verify or compare sound you cannot hear - picking a sound effect, music or ambience from candidates, finding the cleanest moment in a recording, checking whether audio reads as a real recording or as code-synthesized, reviewing a soundtrack or a video's audio (what happens when, sync to picture, loudness, mix), A/B-ing a mix change, making a sound in code and improving it by listening (earshot forge), or giving a code-made film its sound effects from the shipped bank (earshot sfx / kit). Use it before telling anyone how audio sounds.
L4 High-Privilege · Graded auth & full auditV1 Commit-PinnedExecute CommandWrite FileDual-pass Audit
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1How It Works & Mechanism
Measures and quantifies sound characteristics based on local CPU-powered audio acoustic and embedding models (CLAP + AST), rather than making unfounded guesses
skills/earshot/SKILL.mdearshot runs locally on CPU (audio
never leaves the machine, except with the optional `llm` command) and caches every embedding and result on disk.
Executes locally offline; audio features and embedding vectors are cached in-place
Provides a complete closed-loop workflow for audio asset selection: candidate ranking, clean point trimming, semantic acoustic descriptions, and synthetic vs. real recording discrimination
skills/earshot/SKILL.md1. `earshot rank "a soft felt mallet hit on a wooden block" downloads/sfx/ --top 5` - shortlist from a folder.
2. `earshot find winner.ogg "a single clean mallet hit" --top 3` - the best moments as sample trims (start / end in
seconds).
Quantified acoustic calibration and editing assistance
Video soundtrack review and alignment dashboard: extracts audio-visual sync timelines and generates composite sheet images with spectrograms and alignment scores
skills/earshot/SKILL.md2. `earshot sheet film.mp4 -o sheet.png --cues cues.json` (`--from 10 --to 25` zooms, `--detail low` is faster) -
an annotated PNG: frames, sections, labelled events, spectrogram, loudness, beats, cue markers coloured by sync
Outputs high-fidelity inspection sheets with storyboard frames and loudness alignment
2Core Capabilities
01Audio acoustic loudness measurement and real vs. synthetic discrimination
02Asset semantic retrieval and precise transient point trimming
03Audio-visual sync timeline extraction and alignment sheet rendering
4Recommended Governance & Evidence
Suggested Controls for Safe Operation
For Agent Runtime
Graded/per-use authorization, sandbox recommended
For Administrators
Approval workflow, rollback support, full audit
Evidence & Triggers (File Paths & Excerpts)
- scripts/: Executes local earshot CLI commands or Python API (earshot rank/find/describe/sheet)
- 本地文件系统: Reads media files and writes spectrogram analysis image sheet.png alongside embedding feature caches
Audit Notes: Local execution scripts and analysis tools: Relies on the locally installed earshot CLI tool for CPU-level audio feature extraction, reads local media, and writes visualization results to disk, with no unexpected external network requests or credential access.
5Second-Pass Verification
- [ok] 网络外发检测 — 默认命令音频数据绝不离开本机，除可选 llm 命令外无外部网络请求
- [ok] 模型与性能声明 — CLAP 与 AST 纯 CPU 运行，首跑加载约 20-40s，内嵌多线程并发保护
6Verdict & Scenarios
Completely eliminates the industry-wide flaw where LLMs 'cannot hear sound' and hallucinate audio performanceProvides professional-grade LUFS loudness measurement and audio-visual alignment spectrogram visual artifactsBest for: Agent developers and audio/video creators performing audio-visual sync verification for video editing, podcast scoring, and motion graphics
Not for: Pure voice interactive dialogue scenarios requiring cloud-based, real-time millisecond-level low-latency streaming
Install Agent-Ready
① Verified Mirror 2026-10-25
Option A · Direct DownloadDownload earshot.tar.gzsha256: 3f830b68f7ebc045…
Option B · Copy Guide for AgentAgents automatically download and verify mirrors from this JSON guide.