Borrowing it
Nothing to install: this file belongs to fanfan-de/anybox. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fanfan-de/anybox/master/.agents/skills/transcribe/SKILL.mdgit clone --depth 1 https://github.com/fanfan-de/anyboxWrote 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/fanfan-de/anybox/transcribe)<a href="https://agentmods.dev/skills/fanfan-de/anybox/transcribe"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/transcribe/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/fanfan-de/anybox/transcribe"><img src="https://agentmods.dev/badge/skills/fanfan-de/anybox/transcribe.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00045 | $0.00715 |
| Opus 5 | $0.00023 | $0.00358 |
| Sonnet 5 | $0.00009 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
transcribe 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 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.
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
95% identical to transcribe — 6 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audio Transcribe
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
Workflow
- Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
- Verify
OPENAI_API_KEYis set. If missing, ask the user to set it locally (do not ask them to paste the key). - Run the bundled
transcribe_diarize.pyCLI with sensible defaults (fast text transcription). - Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
- Save outputs under
output/transcribe/when working in this repo.
Decision rules
- Default to
gpt-4o-mini-transcribewith--response-format textfor fast transcription. - If the user wants speaker labels or diarization, use
--model gpt-4o-transcribe-diarize --response-format diarized_json. - If audio is longer than ~30 seconds, keep
--chunking-strategy auto. - Prompting is not supported for
gpt-4o-transcribe-diarize.
Output conventions
- Use
output/transcribe/<job-id>/for evaluation runs. - Use
--out-dirfor multiple files to avoid overwriting.
Dependencies (install if missing)
Prefer uv for dependency management.
uv pip install openai
If uv is unavailable:
python3 -m pip install openai
Environment
OPENAI_API_KEYmust be set for live API calls.- If the key is missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.
- Never ask the user to paste the full key in chat.
Skill path (set once)
export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export TRANSCRIBE_CLI="$CODEX_HOME/skills/transcribe/scripts/transcribe_diarize.py"
User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills).
CLI quick start
Single file (fast text default):
python3 "$TRANSCRIBE_CLI" \
path/to/audio.wav \
--out transcript.txt
What ships with it
6 files 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 · 82 lines · 45 tokens per session scan A f530021da9f3
transcribe is a skill published in the GitHub repository fanfan-de/anybox (57 stars, last pushed 27d ago), licensed MIT. It adds 45 tokens to every session and 715 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to transcribe, differing in 6 lines, and is treated as a copy.
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