A command-line text-to-speech tool that uses ElevenLabs to turn written text into spoken audio and play it locally.

Use it to speak text, list available voices, choose a voice or model, guide pronunciation, and add expressive directions such as whispers, laughter, or singing.

It lets developers hear generated speech without building a separate audio workflow. It also provides controls for voices, languages, pronunciation, pauses, and delivery style.

sag — Skill for Claude Code and Codex by trpc-group

About the project

tRPC-Agent-Go is a Go framework for building AI agent applications with language models, graph-based workflows, tools, memory, retrieval, evaluation, and observability. Go developers use it to create deployable agent systems that can integrate with A2A, AG-UI, and MCP. The catalogue add-ons provide reusable workflows and agent integrations for the framework.

trpc-group/trpc-agent-go · 1,763 stars · on GitHub · trpc-group.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add trpc-group/trpc-agent-go --skill sag

Clone the repo

git clone --depth 1 https://github.com/trpc-group/trpc-agent-go

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/sag.svg)](https://agentmods.dev/skills/trpc-group/trpc-agent-go/sag)

Your own site

<a href="https://agentmods.dev/skills/trpc-group/trpc-agent-go/sag"><img src="https://agentmods.dev/badge/skills/trpc-group/trpc-agent-go/sag.svg" alt="Measured on agentmods" height="20"></a>

Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 707 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 98% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00016	$0.00707
Opus 5	$0.00008	$0.00353
Sonnet 5	$0.00003	$0.00141
Haiku 4.5	$0.00002	$0.00071

Measured 7d ago against content hash d86b98ff6586, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

sag scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

98% identical to sag — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

openclaw/skills/sag/SKILL.md · 88 lines

What it actually says

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

# 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)

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

7d ago First seen · 88 lines · 16 tokens per session scan A d86b98ff6586

Subscribe to this mod's changes

sag is a skill published in the GitHub repository trpc-group/trpc-agent-go (1,763 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 707 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to sag, differing in 4 lines, and is treated as a copy.

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