Moltis is a persistent personal agent server written in Rust that runs on hardware controlled by its user. It provides an AI agent with sandboxed command execution, model-provider connections, memory, voice, scheduling, messaging integrations, browser automation, and MCP tools. Its catalogue add-ons extend the agent’s workflows and available tools.
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 moltis-org/moltis --skill openai-whisper-apigit clone --depth 1 https://github.com/moltis-org/moltisWrote 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/moltis-org/moltis/openai-whisper-api)<a href="https://agentmods.dev/skills/moltis-org/moltis/openai-whisper-api"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/openai-whisper-api/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/moltis-org/moltis/openai-whisper-api"><img src="https://agentmods.dev/badge/skills/moltis-org/moltis/openai-whisper-api.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00020 | $0.00386 |
| Opus 5 | $0.00010 | $0.00193 |
| Sonnet 5 | $0.00004 | $0.00077 |
| Haiku 4.5 | $0.00002 | $0.00039 |
Grade A, and why
openai-whisper-api scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
# OpenAI Whisper API (curl) What it actually says
OpenAI Whisper API (curl)
Transcribe an audio file via OpenAI’s /v1/audio/transcriptions endpoint. Set OPENAI_BASE_URL to use an OpenAI-compatible proxy or local gateway.
Quick start
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a
Defaults:
- Model:
whisper-1 - Output:
<input>.txt
Useful flags
{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --model whisper-1 --out /tmp/transcript.txt
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language en
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --prompt "Speaker names: Peter, Daniel"
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json
API key
Set OPENAI_API_KEY, or configure it in the active Moltis config file ($OPENCLAW_CONFIG_PATH, default ~/.moltis/Moltis.json). Optionally set OPENAI_BASE_URL (for example http://127.0.0.1:51805/v1) to use an OpenAI-compatible proxy or local gateway:
{
skills: {
"openai-whisper-api": {
apiKey: "OPENAI_KEY_HERE",
},
},
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 48 lines · 20 tokens per session scan A b7df4fced433
openai-whisper-api is a skill published in the GitHub repository moltis-org/moltis (2,847 stars, last pushed 6d ago), licensed MIT. It adds 20 tokens to every session and 386 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
add-ollama-tool
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
llm-finetuning
LLM fine-tuning expert for LoRA, QLoRA, dataset preparation, and training optimization.
ml-engineer
Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps.
vector-db
Vector database expert for embeddings, similarity search, RAG patterns, and indexing strategies.
prompt-engineer
Prompt engineering expert for chain-of-thought, few-shot learning, evaluation, and LLM optimization.
opik-optimizer
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.