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.
npx skills add geezerrrr/motive --skill saggit clone --depth 1 https://github.com/geezerrrr/motiveWrote 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.
[](https://agentmods.dev/skills/geezerrrr/motive/sag)<a href="https://agentmods.dev/skills/geezerrrr/motive/sag"><img src="https://agentmods.dev/badge/skills/geezerrrr/motive/sag.svg" alt="Measured on agentmods" height="20"></a>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 |
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 8d 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.
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.
What it actually says
sag
Use sag for ElevenLabs TTS with local playback.
API key (required)
ELEVENLABS_API_KEY(preferred)SAG_API_KEYalso supported by the CLI
Quick start
sag "Hello there"sag speak -v "Roger" "Hello"sag voicessag 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(oroffif 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 insag.
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_IDorSAG_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)
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.
- 8d ago First seen · 88 lines · 16 tokens per session scan A d86b98ff6586
sag is a skill published in the GitHub repository geezerrrr/motive (117 stars, last pushed 6mo ago), licensed MIT. 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.
Other skills, from other repositories
capability-spotlight-video
Plan and submit a recurring series of diverse, premium Ace Data Cloud sales films. Each run discovers live capabilities, proves a real buyer outcome, assembles a rich provenance-bound material set, chooses a structurally distinct creative genome, and routes a freeform Pro production through Maestro general-video.
xiaohongshu
A tool for operating Xiaohongshu, also called RED, a Chinese platform for image, video, and article-based posts. It supports searching, inspecting content, publishing, scheduling, and managing interactions through a paired browser device.
bilibili
A tool for reading and publishing Bilibili 专栏 articles. Bilibili is a Chinese video and media platform, and 专栏 is its long-form article section.
kling-video
Generate AI videos with Kuaishou Kling via AceDataCloud API. Use when creating videos from text or images, extending existing videos, applying motion control, animating a talking photo from image+audio, or lip-syncing audio/text to video. Supports text-to-video, image-to-video, extend, motion generation…
maestro-video
Produce complete AI videos with Maestro via AceDataCloud API. Use when: Maestro, article-to-video, prompt-to-video, turn a brief or reference media into a finished captioned video, generate scripts/visuals/voiceover/music/editing in one workflow, create multilingual video variants, or remix/edit/extend a previous…
seedance-video
Generate and edit AI videos with Seedance via AceDataCloud API. Use for text/image video, Seedance 2.x multimodal image/audio/video reference, Seedance 2.5 pure-audio reference, edit, extend, and up to 30-second output. Supports multiple models, up to 4k, aspect ratio, and optional audio generation.