audio-jingle

audio-jingle is a skill for Claude Code, Codex from onfire7777/universal-ai-skills-library. It costs 78 tokens per session (1,159 once invoked), scanned A, a copy of audio-jingle, MIT.

An audio-production skill that creates jingles, background music, voiceovers, or sound effects. It saves the result as an MP3 or WAV file in the project folder.

In plain words
What is it for?
Use it to generate music with a genre and tempo, speech from a script with a chosen voice, or sound effects with a specified texture and duration.
Why use it?
It gives audio requests a defined path based on whether the job needs music, speech, or sound effects. The selected mode also guides the required creative details.

Skill for Claude CodeCodex

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

Good fit Use it to generate music with a genre and tempo, speech from a script with a chosen voice, or sound effects with a specified texture and duration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/onfire7777/universal-ai-skills-library/audio-jingle
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 onfire7777/universal-ai-skills-library --skill audio-jingle
Clone the repo
git clone --depth 1 https://github.com/onfire7777/universal-ai-skills-library

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 audio-jingle

README.md
[![agentmods](https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/audio-jingle/github.svg)](https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/audio-jingle)
Your own site
<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/audio-jingle"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/audio-jingle/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 audio-jingle

Your own site · 80×15
<a href="https://agentmods.dev/skills/onfire7777/universal-ai-skills-library/audio-jingle"><img src="https://agentmods.dev/badge/skills/onfire7777/universal-ai-skills-library/audio-jingle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,159 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 94% 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 $0.00078 $0.01159
Opus 5 $0.00039 $0.00580
Sonnet 5 $0.00016 $0.00232
Haiku 4.5 $0.00008 $0.00116

Measured 8d ago against content hash ed595b2b8039, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

audio-jingle 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 8d 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

94% identical to audio-jingle — 6 lines 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/audio-jingle/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audio Jingle Skill

Three sub-modes. The active project's audioKind decides which one runs:

audioKind Models we route to Plan focus
music Suno V5 (default), Udio, Lyria 2 genre + tempo + instrumentation
speech MiniMax TTS (default), Fish, ElevenLabs V3 script + voice + pacing
sfx ElevenLabs SFX (default), AudioCraft texture + impact + duration

Resource map

audio-jingle/
├── SKILL.md
└── example.html

Workflow

Step 0 — Read the project metadata

audioKind, audioModel, audioDuration (seconds), and (for speech) voice. Branch by audioKind and use the values verbatim — no clarifying form unless something is marked (unknown — ask).

Important: voice is provider-specific. For minimax-tts, --voice must be a valid MiniMax voice_id (for example male-qn-qingse), not a natural-language description. If you only have a prose voice brief ("warm female narrator", "neutral Mandarin"), keep that in your plan but omit --voice so the daemon's default voice id applies, or ask the user to choose a specific id.

Step 1 — Plan

Music

  • Genre + reference artists (1-2)
  • Tempo (BPM) + key
  • Instrumentation (3-5 instruments max)
  • Vocals: yes / no / hummed / choir
  • Mood arc (intro → chorus → outro)

Speech

  • Script (final, not draft — TTS runs verbatim)
  • Voice target + pacing For MiniMax this means a real voice_id, not prose in --voice
  • Pronunciation hints for proper nouns / acronyms

SFX

  • Texture (impact / whoosh / ambience / foley)
  • Duration + envelope (sharp attack vs. gentle swell)
  • Layering note (single hit vs. stacked)

State the plan in 2-3 sentences before dispatching.

Step 2 — Compose the prompt

Use the format the upstream model prefers. Bind audioDuration to the API parameter directly; never put "make it 30 seconds" in prose.

Step 3 — Dispatch via the media contract

Use the unified dispatcher — do not call provider APIs by hand:

"$OD_NODE_BIN" "$OD_BIN" media generate \
  --project "$OD_PROJECT_ID" \
  --surface audio \
  --audio-kind "<music|speech|sfx>" \
  --model "<audioModel from metadata>" \
  --duration <audioDuration seconds> \
  [--voice "<provider voice id (speech only)>"] \
  --output "<short-slug>-<duration>s.mp3" \
  --prompt "<assembled prompt from Step 2 — for speech, the literal script>"

Read the full file on GitHub · 133 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 133 lines · 78 tokens per session scan A ed595b2b8039

Subscribe to this mod's changes

audio-jingle is a skill published in the GitHub repository onfire7777/universal-ai-skills-library (16 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 1,159 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to audio-jingle, differing in 6 lines, and is treated as a copy.