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 agentmods add skills/understudy-ai/understudy/openai-whisper-apinpx skills add understudy-ai/understudy --skill openai-whisper-apigit clone --depth 1 https://github.com/understudy-ai/understudyWrote 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/understudy-ai/understudy/openai-whisper-api)<a href="https://agentmods.dev/skills/understudy-ai/understudy/openai-whisper-api"><img src="https://agentmods.dev/badge/skills/understudy-ai/understudy/openai-whisper-api.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 | $0.00020 | $0.00335 |
| Opus 5 | $0.00010 | $0.00168 |
| Sonnet 5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00034 |
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 4d 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.
"requires": { "bins": ["curl"], "env": ["OPENAI_API_KEY"] }, This is a copy
95% identical to openai-whisper-api — 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
OpenAI Whisper API (curl)
Transcribe an audio file via OpenAI’s /v1/audio/transcriptions endpoint.
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 ~/.understudy/config.json5:
{
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.
- 4d ago First seen · 53 lines · 20 tokens per session scan A ed11f6778ee0
openai-whisper-api is a skill published in the GitHub repository understudy-ai/understudy (457 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 335 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to openai-whisper-api, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
openai-whisper-api
OpenAI Audio Transcriptions API via curl; gpt-4o-transcribe, mini, diarize, or whisper-1.
songsee
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
release-openclaw-maintainer
Prepare or verify OpenClaw stable, beta, and extended-stable releases, including backport discovery, changelogs, release notes, publish commands, and artifacts.
openclaw-testing
Choose, run, rerun, or debug OpenClaw tests, CI checks, Docker E2E lanes, release validation, and the cheapest safe verification path.
autoreview
Structured Codex, Claude, Amp, Pi, or Kimi code review when explicitly requested.
release-openclaw-ci
Run, watch, debug, and summarize OpenClaw full release CI, release checks, live provider gates, install/update proofs, and release-secret preflights.