Skip to content
All Skills

Sag

ElevenLabs text-to-speech with mac-style say UX.

Data, AI & Research|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "sag-9fddf31b" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
# sag

Use `sag` for ElevenLabs TTS with local playback.

API key (required)

- `ELEVENLABS_API_KEY` (preferred)
- `SAG_API_KEY` also supported by the CLI

Quick start

- `sag "Hello there"`
- `sag speak -v "Roger" "Hello"`
- `sag voices`
- `sag prompting` (model-specific tips)

Model notes

- Default: `eleven_v3` (expressive)
- Stable: `eleven_multilingual_v2`
- Fast: `eleven_flash_v2_5`

Pronunciation + delivery rules

- First fix: respell (e.g. "key-note"), add hyphens, adjust casing.
- Numbers/units/URLs: `--normalize auto` (or `off` if it harms names).
- Language bias: `--lang en|de|fr|...` to guide normalization.
- v3: SSML `<break>` not supported; use `[pause]`, `[short pause]`, `[long pause]`.
- v2/v2.5: SSML `<break time="1.5s" />` supported; `<phoneme>` not exposed in `sag`.

v3 audio tags (put at the entrance of a line)

- `[whispers]`, `[shouts]`, `[sings]`
- `[laughs]`, `[starts laughing]`, `[sighs]`, `[exhales]`
- `[sarcastic]`, `[curious]`, `[excited]`, `[crying]`, `[mischievously]`
- Example: `sag "[whispers] keep this quiet. [short pause] ok?"`

Voice defaults

- `ELEVENLABS_VOICE_ID` or `SAG_VOICE_ID`

Confirm voice + speaker before long output.

## Chat voice responses

When the user asks for a "voice" reply (e.g., "crazy scientist voice", "explain in voice"), generate audio and send it:

```bash
# Generate audio file
sag -v Clawd -o /tmp/voice-reply.mp3 "Your message here"

# Then include in reply:
# MEDIA:/tmp/voice-reply.mp3
```

Voice character tips:

- Crazy scientist: Use `[excited]` tags, dramatic pauses `[short pause]`, vary intensity
- Calm: Use `[whispers]` or slower pacing
- Dramatic: Use `[sings]` or `[shouts]` sparingly

Default voice for Clawd: `lj2rcrvANS3gaWWnczSX` (or just `-v Clawd`)
#deep#researchelevenlabs-apisag

Related Skills

More skills in Data, AI & Research

Ablation Planner

Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.

#broad-capability#wanshuiyin-arisMIT

Ablation Planner

Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.

#broad-capability#wanshuiyin-arisMIT

About

Provides information about the bitwize-music plugin, its version, and its creator. Use when the user asks about the plugin, its purpose, version, or capabilities.

#github#broad-capabilityCC0-1.0

Ab Test Analysis

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.

#work-life#productivityMIT

Academic Search

Search and analyze academic literature. Find papers, understand research methodologies, and synthesize academic findings for research projects.

#work-life#officeMIT

Adaptyv

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

#broad-capability#scienceMIT