mcpbeat

Stepfun Tts

daymade/stepfun-tts

Generate Chinese / Japanese speech with StepFun's stepaudio-2.5-tts — Contextual TTS that replaces step-tts-2's `voice_label` with natural-language `instruction` (≤200 chars) plus inline `()` parentheses for句内 prosody. Use when the user wants emotional / prosody control over voice synthesis (whisper, pause, stress, mood pivot mid-sentence), batch-generates game / app voice lines, migrates from `step-tts-2` (the `voice_label → instruction` breaking change), or hits StepFun's stricter 2.5-era censorship (死/消失/political terms). Triggers on 阶跃 TTS, StepAudio 合成, 语音合成, 配音, 文本转语音, TTS 升级, 迁移 step-tts-2. For transcription with the sibling stepaudio-2.5-asr model, use the stepfun-asr skill instead.

9k tokens
context cost
the whole folder, loaded on every use
7
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1314
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/daymade/claude-code-skills --skill stepfun-tts

The instruction itself

9 sections, as written by the author

StepFun stepaudio-2.5-tts

Generate Chinese / Japanese speech with stepaudio-2.5-tts (released 2026-04, verified 2026-04-23). Contextual TTS — emotion and prosody go through natural-language description, not fixed labels.

> Companion: for transcription with stepaudio-2.5-asr (the sibling model), use the stepfun-asr skill — they share an API key but live on different endpoints with different body shapes.

Why this skill exists — StepAudio 2.5 has two non-obvious pitfalls that cost hours if you don't know them:

  • stepaudio-2.5-tts rejects voice_label (the step-tts-2 way). Emotion/prosody now goes through instruction (natural-language description, ≤200 chars) and inline () parentheses inside the text itself.
  • Censorship is stricter — anything containing 死 / 消失 / sensitive political terms returns censorship_block. Your rewrite options are in references/migration_from_v2.md.

Config and auth

API key lives in $STEPFUN_API_KEY (preferred) or ${CLAUDE_PLUGIN_DATA}/config.json (fallback for cross-session persistence). All bundled scripts try env first, then config.

First-time setup (one-liner):

mkdir -p "${CLAUDE_PLUGIN_DATA}" && cat > "${CLAUDE_PLUGIN_DATA}/config.json" <<EOF
{"api_key": "<paste key here>"}
EOF

If the user hasn't set a key, ask them to paste it (don't guess / don't use a placeholder). StepFun API keys are available at https://platform.stepfun.com/ → API Keys. Use a Normal key, not a Plan key (Plan keys are restricted to text models and silently fail on audio endpoints).

Common tasks — decision tree

| User wants... | Script | Key detail |

|---|---|---|

| Synthesize 1–500 char Chinese with emotion | scripts/tts_generate.py | Use instruction for mood, () for inline prosody |

| Synthesize long text (500–1000 char) | scripts/tts_generate.py | 1000 char is the hard cap; split at semantic boundaries above that |

| Batch-generate game/app voice lines | scripts/tts_generate.py --batch <jsonl> | Handle censorship_block fallback individually |

| A/B compare two TTS models | scripts/ab_compare.sh | Compares duration/size across two directories |

| Migrate from step-tts-2 | see references/migration_from_v2.md | voice_label.emotioninstruction rewrite + censorship list |

Starting points

  • Synthesize a single line: Run python3 scripts/tts_generate.py --text "你好" --out /tmp/hello.mp3 --instruction "温暖的希望感". For fine-grained control read the "Contextual TTS" section below.
  • A full migration from step-tts-2stepaudio-2.5-tts: read references/migration_from_v2.md end-to-end before touching code. It has the INSTRUCTION_MAP, the SKIP_CENSORED list pattern, and the output-directory-strategy for non-destructive A/B.

Contextual TTS — beyond emotion labels

The headline feature of stepaudio-2.5-tts is that you stop mapping emotions to fixed tags and start describing what you want in natural language. Two layers:

Global context (instruction parameter) — sets the overall tone for the entire utterance. ≤200 chars. Think of it like giving stage direction to a voice actor.

instruction: "克制的悲伤,语气低沉柔弱,像快要消失一样"

Inline context (() parentheses inside input) —句内 directives. Parenthesised content is consumed as directions and is NOT read aloud. Use for precise control of pauses, breath, emphasis, or mid-sentence emotion shifts.

input: "(试探着问)你好吗?(开心地)太好了!(突然沉下来)不过...我快要消失了。"

Examples that worked in practice (from 2026-04-23 verification):

  • instruction: "活泼俏皮,像是在撒娇,带点嘴硬" — visibly speeds up delivery vs neutral
  • instruction: "耳语声,气声很重,几乎听不清" — produces audible whisper/breath
  • input: "你好(停顿一下)我是蕾格(轻声)今天(加重)的天气真不错。" — inline directives all respected

What stepaudio-2.5-tts will NOT acceptvoice_label parameter. Error: voice_label is not supported for v2 models. This is the #1 migration gotcha from step-tts-2.

Common error patterns (real errors, real fixes)

| Error response | Actual cause | Fix |

|---|---|---|

| "voice_label is not supported for v2 models" | Sent voice_label to stepaudio-2.5-tts | Remove voice_label; put the same intent into instruction as natural language |

| "The content you provided or machine outputted is blocked." type: censorship_block | Sensitive word (死 / 消失 / etc.) | Rewrite the phrase OR fall back to step-tts-2 for that specific line (mixed-model is fine) |

| Silent audio truncation (input > 1000 chars) | Hard cap exceeded | Split at semantic boundaries; don't truncate mid-sentence |

More in references/known_issues.md.

When to read references

  • references/api_reference.md — exact request/response JSON for /v1/audio/speech, all fields, error responses. Read when writing raw HTTP calls instead of using the bundled scripts.
  • references/migration_from_v2.md — complete playbook for moving a step-tts-2 project to stepaudio-2.5-tts. Has the emotion→instruction rewrite table, the A/B directory strategy, decision checkpoints, and the 2026-04 speed/quality trade-off data (stepaudio-2.5-tts is ~20% slower than step-tts-2; audible prosody improvement). Read before any migration work.
  • references/known_issues.md — censorship patterns, TTS duration inflation, v2-family parameter naming gotcha, 1000-char hard cap. Read when debugging anomalous output or evaluating whether to adopt.

Design invariants (don't break these)

  • Non-destructive A/B output — when regenerating a corpus with a new model, write to a parallel directory (voice/zh_v25/), never overwrite the production corpus. The migration playbook shows why.
  • Per-line censorship handling — if 2/29 lines get censorship_block, don't fail the batch. Log the skipped IDs, continue. Mixed-model fallback (step-tts-2 for the skipped 2) is normal.
  • Don't duplicate voice_label logic in new code — any new TTS code targeting stepaudio-2.5-tts should only use instruction + inline (). Do not write a branch that conditionally emits voice_label.

Pricing (verified 2026-04-23, volatile)

  • stepaudio-2.5-tts contextual synthesis: ~5.8 元 / 万字符
  • Zero-shot voice cloning: ~9.9 元 / 音色

Re-verify at https://platform.stepfun.com/docs/zh/guides/pricing/details before quoting to stakeholders.

How to use it

Copy the folder

Take daymade/stepfun-tts from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.