stepfun-tts
Generates Chinese/Japanese speech with StepFun's Contextual TTS — default stepaudio-2.5-tts, stepaudio-3-tts for whisper/inline-() prosody. Replaces step-tts-2's voice_label with natural-language instruction. Use for emotional/prosody-controlled synthesis, batch voice lines, migrating from step-tts-2, or cloned voices (2.5/step-tts-2, not v3). Triggers on 阶跃 TTS, 语音合成, 配音. Not for transcription (use stepfun-asr).
How do I install this agent skill?
npx skills add https://github.com/daymade/claude-code-skills --skill stepfun-ttsIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill is safe. It provides tools and documentation for using StepFun's text-to-speech API, including scripts for batch synthesis and model comparison. No malicious patterns, exfiltration, or unauthorized code execution were detected.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
StepFun Contextual TTS (default stepaudio-2.5-tts)
Generate Chinese / Japanese speech with StepFun's Contextual TTS — emotion and prosody go through natural-language description, not fixed labels. Default model is stepaudio-2.5-tts (what the bundled script uses): in a 2026-09-16 blind A/B on our own cases, 2.5 won the neutral / jiao / lively-girl pairs 3:2. Pick stepaudio-3-tts when the line is whisper or heavy inline-() prosody — v3 won exactly those two pairs; v3 also raises the instruction cap to 500 chars (2.5 is 200). ⚠️ Never synthesize cloned voices with v3 — v3 speech 接受复刻音色 ID 不报错但静默回退默认女声——根因 = 阶跃复刻链路整体停在 2.5 家族(复刻创建 API 只收 2.5/step-tts-2/step-tts-mini,v3 不在列;v3 合成侧复刻未发布)。两代创建的克隆在 v3 上全丢:step-tts-2 克隆 SIM 0.272、2.5 创建的新克隆 SIM 0.195(锚 0.773),2.5 同 ID 0.743/0.678。
Companion: for transcription with
stepaudio-3-asr-max(the sibling model), use thestepfun-asrskill — they share an API key but live on different endpoints with different body shapes.
Why this skill exists — two non-obvious pitfalls that cost hours if you don't know them:
stepaudio-3-ttsrejectsvoice_label(the step-tts-2 way) — verified on v3 2026-09-16: HTTP 400voice_label is not supported for this model. Emotion/prosody goes throughinstruction(natural-language description, ≤500 chars on v3 — 200 was the 2.5 limit) and inline()parentheses inside the text itself.- Censorship behavior is model-version-specific — the 2.5-era trigger list (死 / 消失 / sensitive political terms →
censorship_block) did not fire on v3 in a 2026-09-16 single-sample probe; treat censorship as present but re-verify per trigger before building rewrite maps. The 2.5-era options are inreferences/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 / stepaudio-2.5-tts | see references/migration_from_v2.md | voice_label.emotion → instruction rewrite + 2.5-era 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. - From code: this script is the endpoint's wrapper in
llm-registry—llmreg.wrapper_for("stepfun-tts").tts_generate.synthesize(api_key=…, text=…, model=…, extra={…}).extrais merged into the request body as-is; with{"timestamp": True, "return_url": True}the server answers a JSON envelope ({"data": {"url", "subtitles"}}) that comes back underjsoninstead ofaudio_bytes(verified 2026-09-19). Parameters are not billed — send what you need. Direct/v1/audio/speechcalls elsewhere are blocked by thellm-entry-guardhook. - A full migration from
step-tts-2→ Contextual TTS: readreferences/migration_from_v2.mdend-to-end before touching code. It has theINSTRUCTION_MAP, the SKIP_CENSORED list pattern, and the output-directory-strategy for non-destructive A/B (written for 2.5; the migration mechanics are identical on v3).
Contextual TTS — beyond emotion labels
The headline feature of stepaudio-3-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. ≤500 chars on v3 (2.5 was 200; a 300-char instruction verified accepted on v3 2026-09-16). 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 (verified 2026-04-23 on 2.5; all five re-verified on v3 2026-09-16, including these instruction and inline-prosody cases):
instruction: "活泼俏皮,像是在撒娇,带点嘴硬"— visibly speeds up delivery vs neutralinstruction: "耳语声,气声很重,几乎听不清"— produces audible whisper/breathinput: "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-3-tts will NOT accept — voice_label parameter. Error on v3: voice_label is not supported for this model (2.5 said ...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 this model" (v3) / "...for v2 models" (2.5) | Sent voice_label to a Contextual TTS model | 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 (2.5-era: 死 / 消失 / etc.; v3 triggers unverified) | 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 Contextual TTS. Has the emotion→instruction rewrite table, the A/B directory strategy, decision checkpoints, and the 2026-04 speed/quality trade-off data (written against 2.5). Read before any migration work.references/known_issues.md— censorship patterns, TTS duration inflation, v2-family parameter naming gotcha, 1000-char hard cap. 2.5-era verification; re-verify on v3 before relying on a specific entry. 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_v3/), 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-3-tts should only use
instruction+ inline(). Do not write a branch that conditionally emitsvoice_label.
v3-specific facts (verified 2026-09-16)
- Official voices: 60+ via
GET /v1/audio/system_voices?model=stepaudio-3-tts— the 2.5 list is fully inherited, plus new voices (e.g. English-namedLisa/Alfie, 上海话shanghaifemale/shanghaimale). - Cloned (复刻) voices: do NOT use
stepaudio-3-tts— root cause nailed 2026-09-16: StepFun's whole cloning stack is still 2.5-family. The creation API (POST /v1/audio/voices) only acceptsstepaudio-2.5-tts/step-tts-2/step-tts-mini, and v3/v1/audio/speechsilently falls back to a default female voice for ANY cloned ID — SIM 0.272 (step-tts-2 clone) and 0.195 (fresh 2.5-created clone) vs the 0.773 anchor; the same IDs on 2.5 score 0.743/0.678. Synthesize clones withstepaudio-2.5-tts(best SIM) orstep-tts-2. - No WebSocket streaming for v3 (as of 2026-09-16):
wss://api.stepfun.com/v1/realtime/audio?model=stepaudio-3-ttsis rejected at handshake (404), while 2.5 still streams there. Need char-level subtitle timestamps on v3? Use RESTtimestamp:true + return_url:true(subtitles arrive in the response JSONdata.subtitles[], char-level ms, accumulated absolute axis) — barestream_format:"audio"cannot carry subtitles (server 400).
Pricing (verified 2026-09-16, volatile)
stepaudio-3-ttssynthesis: 2.5 元 / 万字符 (official model page, 2026-09-16 — cheaper than the 2.5-era ~5.8)- 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 can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
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