daymade/claude-code-skills

stepfun-tts

Generate Chinese / Japanese speech with StepFun's Contextual TTS — default stepaudio-2.5-tts (blind-judged better on neutral/emotive preset voices), stepaudio-3-tts for whisper & inline-prosody cases (where it won the same blind test).

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/daymade/claude-code-skills --skill stepfun-tts

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

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 the stepfun-asr skill — 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:

  1. stepaudio-3-tts rejects voice_label (the step-tts-2 way) — verified on v3 2026-09-16: HTTP 400 voice_label is not supported for this model. Emotion/prosody goes through instruction (natural-language description, ≤500 chars on v3 — 200 was the 2.5 limit) and inline () parentheses inside the text itself.
  2. 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 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):

bash
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...ScriptKey detail
Synthesize 1–500 char Chinese with emotionscripts/tts_generate.pyUse instruction for mood, () for inline prosody
Synthesize long text (500–1000 char)scripts/tts_generate.py1000 char is the hard cap; split at semantic boundaries above that
Batch-generate game/app voice linesscripts/tts_generate.py --batch <jsonl>Handle censorship_block fallback individually
A/B compare two TTS modelsscripts/ab_compare.shCompares duration/size across two directories
Migrate from step-tts-2 / stepaudio-2.5-ttssee references/migration_from_v2.mdvoice_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.
  • A full migration from step-tts-2 → Contextual 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 (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 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-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 responseActual causeFix
"voice_label is not supported for this model" (v3) / "...for v2 models" (2.5)Sent voice_label to a Contextual TTS modelRemove voice_label; put the same intent into instruction as natural language
"The content you provided or machine outputted is blocked." type: censorship_blockSensitive 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 exceededSplit 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)

  1. 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.
  2. 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.
  3. 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 emits voice_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-named Lisa/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 accepts stepaudio-2.5-tts / step-tts-2 / step-tts-mini, and v3 /v1/audio/speech silently 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 with stepaudio-2.5-tts (best SIM) or step-tts-2.
  • No WebSocket streaming for v3 (as of 2026-09-16): wss://api.stepfun.com/v1/realtime/audio?model=stepaudio-3-tts is rejected at handshake (404), while 2.5 still streams there. Need char-level subtitle timestamps on v3? Use REST timestamp:true + return_url:true (subtitles arrive in the response JSON data.subtitles[], char-level ms, accumulated absolute axis) — bare stream_format:"audio" cannot carry subtitles (server 400).

Pricing (verified 2026-09-16, volatile)

  • stepaudio-3-tts synthesis: 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.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
daymade
커뮤니티

github-ops

Operates GitHub via gh CLI and REST/GraphQL — PRs, issues, Actions, repos, collaborators, org permissions, 2FA — with explicit target, authorization, and independent readback. Use when a write reports success but state didn't change, or choosing gh/REST/GraphQL/UI-only. Not for local Git recovery (use git-safety-net), maintainer PR review (use github-review-pr), or upstream contribution (use github-contributor).

설치 수
2
GitHub Stars
1.5천
업데이트
10월 20일
daymade
커뮤니티

audio-router

Routes audio: StepFun ASR/语音识别, StepFun TTS/配音, transcript/妙记→会议纪要, merge/review minutes. Reads one bundled specialist; generic ASR and correction stay direct.

설치 수
2
GitHub Stars
1.5천
업데이트
10월 20일
daymade
커뮤니티

product-analysis

Multi-path parallel product analysis with cross-model test-time compute scaling. Spawns parallel agents (Claude Code agent teams + Codex CLI) to explore product from multiple perspectives, then synthesizes findings into actionable optimization plans. Can invoke competitors-analysis for competitive benchmarking. Use when "product audit", "self-review", "发布前审查", "产品分析", "analyze our product", "UX audit", or "信息架构审计".

설치 수
2
GitHub Stars
1.5천
업데이트
10월 15일
daymade
커뮤니티

fact-checker

Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.

설치 수
1
GitHub Stars
1.4천
업데이트
10월 4일