songsee

songsee is a skill for Claude Code, Codex from nativ3ai/hermes-agent-camel. It costs 20 tokens per session (637 once invoked), scanned A, a copy of songsee, MIT.

A command-line tool that turns audio files into visual charts, including frequency spectrograms, pitch patterns, loudness, tempo, and other sound features.

In plain words
What is it for?
It is for creating spectrogram images, multi-panel audio analyses, and visualizations of selected time ranges.
Why use it?
It makes properties of a recording visible, so you can inspect or compare audio without listening to the whole file repeatedly.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for creating spectrogram images, multi-panel audio analyses, and visualizations of selected time ranges.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nativ3ai/hermes-agent-camel/songsee
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 nativ3ai/hermes-agent-camel --skill songsee
Clone the repo
git clone --depth 1 https://github.com/nativ3ai/hermes-agent-camel

Made for: Claude Code, Codex.

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 songsee

README.md
[![agentmods](https://agentmods.dev/badge/skills/nativ3ai/hermes-agent-camel/songsee/github.svg)](https://agentmods.dev/skills/nativ3ai/hermes-agent-camel/songsee)
Your own site
<a href="https://agentmods.dev/skills/nativ3ai/hermes-agent-camel/songsee"><img src="https://agentmods.dev/badge/skills/nativ3ai/hermes-agent-camel/songsee/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for songsee

Your own site · 80×15
<a href="https://agentmods.dev/skills/nativ3ai/hermes-agent-camel/songsee"><img src="https://agentmods.dev/badge/skills/nativ3ai/hermes-agent-camel/songsee.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 637 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 95% copy Near-identical to another mod 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 $0.00020 $0.00637
Opus 5 $0.00010 $0.00318
Sonnet 5 $0.00004 $0.00127
Haiku 4.5 $0.00002 $0.00064

Measured 9d ago against content hash d5c0f9355154, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

songsee 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 9d 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.

Origin

This is a copy

95% identical to songsee — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/media/songsee/SKILL.md · 83 lines

What it actually says

songsee

Generate spectrograms and multi-panel audio feature visualizations from audio files.

Prerequisites

Requires Go:

go install github.com/steipete/songsee/cmd/songsee@latest

Optional: ffmpeg for formats beyond WAV/MP3.

Quick Start

# Basic spectrogram
songsee track.mp3

# Save to specific file
songsee track.mp3 -o spectrogram.png

# Multi-panel visualization grid
songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux

# Time slice (start at 12.5s, 8s duration)
songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg

# From stdin
cat track.mp3 | songsee - --format png -o out.png

Visualization Types

Use --viz with comma-separated values:

Type Description
spectrogram Standard frequency spectrogram
mel Mel-scaled spectrogram
chroma Pitch class distribution
hpss Harmonic/percussive separation
selfsim Self-similarity matrix
loudness Loudness over time
tempogram Tempo estimation
mfcc Mel-frequency cepstral coefficients
flux Spectral flux (onset detection)

Multiple --viz types render as a grid in a single image.

Common Flags

Flag Description
--viz Visualization types (comma-separated)
--style Color palette: classic, magma, inferno, viridis, gray
--width / --height Output image dimensions
--window / --hop FFT window and hop size
--min-freq / --max-freq Frequency range filter
--start / --duration Time slice of the audio
--format Output format: jpg or png
-o Output file path

Notes

  • WAV and MP3 are decoded natively; other formats require ffmpeg
  • Output images can be inspected with vision_analyze for automated audio analysis
  • Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines
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. 9d ago First seen · 83 lines · 20 tokens per session scan A d5c0f9355154

Subscribe to this mod's changes

songsee is a skill published in the GitHub repository nativ3ai/hermes-agent-camel (196 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 637 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to songsee, differing in 1 line, and is treated as a copy.

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