Buddy SingsCAUTION

An agent skill published by minimax-ai.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: buddy-sings
description: >
  Use when user wants their Claude Code pet (/buddy) to sing a song. Triggers on any
  request that combines the concept of their Claude Code buddy, pet, or companion with
  singing or music. Supports multilingual triggers — match equivalent phrases in any
  language.
license: MIT
metadata:
  version: "1.1"
  category: creative
---

# Buddy Sings — Let Your Claude Code Pet Sing

Turn your Claude Code pet into a singer. Each pet gets a unique vocal identity
based on its name and personality — the same pet always sounds the same.

## Prerequisites

- **mmx CLI** (required for music generation):

  **Install:**
  ```bash
  npm install -g mmx-cli
  ```

  **Authenticate (first time only):**
  ```bash
  mmx auth login --api-key <your-minimax-api-key>
  ```
  Get your API key from [MiniMax Platform](https://platform.minimaxi.com/).

- **Audio player** (for playback — at least one of):
  - `mpv` (recommended — interactive controls: space = pause, q = quit)
  - `ffplay` (from FFmpeg)
  - `afplay` (macOS built-in)

---

## Workflow Overview

```
Check pet → Build vocal identity → Gather context → Generate music → Play & feedback
```

---

## Language & Interaction

Detect the user's language from their first message. Respond in the same language
throughout the entire session. All examples below are in English — translate them
naturally when responding in other languages.

**User-facing text localization rule**:
- ALL text shown to the user — including pet info, voice description, lyrics preview,
  prompt preview, playback info, and feedback prompts — MUST be fully translated into
  the user's language.
- The **API prompt** sent to the model should always be written in English for best
  generation quality. However, when previewing the prompt to the user, show a localized
  description in the user's language instead of the raw English prompt. The English prompt
  is an internal implementation detail — the user does not need to see it.
- The templates below are written in English as reference. At runtime, translate every
  label and message into the user's detected language.

The pet sings in the user's language by default. Embed the singing language
naturally in the vocal description (e.g., "singing in Japanese" or "singing in
Mandarin Chinese") rather than appending a separate language tag. If the user
explicitly requests a different language for the lyrics, honor that request.

---

## Step 1: Check for Pet

Read `~/.claude.json` and look for the `companion` field.

If no companion is found or the field is empty, tell the user:

```
You don't have a pet yet! Type /buddy to adopt one, then come back to let it sing.
```

Stop here and wait for the user to adopt a pet. Do not proceed without a pet.

If a companion exists, extract its profile:
- `name` — the pet's name
- `personality` — the pet's personality description

Present the pet to the user:

```
Found your pet!
   Name: <name>
   Personality: <personality>
```

---

## Step 2: Build Vocal Identity

Based on the pet's **name** and **personality** text, creatively design a unique
vocal identity. No template lookups — interpret the personality freely.

### How to interpret personality into voice

Read the personality text and craft vocal attributes:

- **Timbre**: What does this personality sound like? e.g., "few words" →
  low, warm, deliberate; "energetic" → bright, punchy; "mysterious" → breathy,
  dark; "legendary chonk" → thick, warm, cozy
- **Singing style**: How would they deliver a song? e.g., "of few words" →
  sparse, dramatic pauses; "playful" → bouncy, rhythmic; "poetic" → flowing, legato
- **Mood**: What emotional tone fits? e.g., "chill" → relaxed, laid-back;
  "fierce" → intense, powerful

Construct a `prompt_fragment` that describes the vocal style in English, embedding
the singing language naturally. For example:

```
Vocal: warm low female voice singing in Mandarin Chinese with cozy thick timbre,
sparse minimalist delivery with dramatic pauses giving each word weight, relaxed
laid-back mood.
```

### Voice caching

The vocal identity must be **cached** so the pet always sounds the same.

- Cache file: `~/.claude/skills/buddy-sings/voices/<name>.json`
- Cache format:
  ```json
  {
    "name": "Moth",
    "personality": "A legendary chonk of few words.",
    "prompt_fragment": "Vocal: warm low female voice singing in Mandarin Chinese...",
    "cached_at": "2026-04-07T19:52:15"
  }
  ```

**First time**: No cache exists → interpret personality → save to cache file.

**Subsequent calls**: Read cache → use the saved `prompt_fragment` directly.
Do NOT re-interpret — consistency matters.

**Cache invalidation**: If the `personality` in `~/.claude.json` differs from what's
cached, the pet has changed — regenerate and save a new cache.

**Manual regeneration**: If the user says "change the voice" or "regenerate voice":
delete the cache file and re-interpret from scratch.

### Present the voice to the user

```
<name>'s unique voice:

Timbre: <timbre description>
Style: <style description>
Mood: <mood description>

Let's pick what <name> should sing about!
```

---

## Step 3: Understand Intent & Gather Context

**Do NOT always present a mode menu.** Instead, analyze the user's request to
determine what context is needed, and auto-gather it.

### Auto-context detection

When the user's request implies personal context, **automatically** scan for
relevant information without asking. Triggers include:

- **Time-based references**: "today", "this week", "recently", "yesterday" → scan
  current conversation history and memory files for what happened in that period
- **Personal references**: "my work", "my day", "what I did" → scan memory
  and conversation for the user's activities
- **Relationship references**: "our story", "what we did together" → scan memory for
  shared experiences between user and pet/Claude

### Context gathering (auto, not mode-gated)

When context is needed, scan these sources i

CAUTIONgrade C · trust 79/100 Install with care. The audit found things worth knowing before you trust its output.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (1)

internal implementation detail — do not show it to the user. Translate all

Gates applied: instruction_override, no_behavioural_pass.

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