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 johnqtcg/awesome-skills --skill local-transcriptgit clone --depth 1 https://github.com/johnqtcg/awesome-skillsWrote 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/johnqtcg/awesome-skills/local-transcript)<a href="https://agentmods.dev/skills/johnqtcg/awesome-skills/local-transcript"><img src="https://agentmods.dev/badge/skills/johnqtcg/awesome-skills/local-transcript.svg" alt="Measured on agentmods" 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 | $0.00139 | $0.04161 |
| Opus 5 | $0.00069 | $0.02080 |
| Sonnet 5 | $0.00028 | $0.00832 |
| Haiku 4.5 | $0.00014 | $0.00416 |
Grade A, and why
local-transcript 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.
How it starts
The opening of the file, as written. The whole thing — 312 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local Transcript
Overview
Use this skill to turn a local media file into cleaned final transcript files in .txt, .pdf, or .docx format. Extract audio with ffmpeg, transcribe with mlx-whisper (Apple Silicon GPU) or faster-whisper (CPU fallback), then clean the transcript with deterministic replacements for known ASR bugs. LLM contextual proofreading is an opt-in second layer (--llm-backend local|claude) — see §LLM Proofreading Is Opt-In for why it is not the default.
Workflow
- Validate the input path.
- Confirm the requested output format.
- Check dependencies.
- Resolve the ASR mode:
fast,balanced, oraccurate. - Reuse cached audio/raw transcript/clean transcript layers when available.
- Extract or reuse 16 kHz mono WAV audio.
- Transcribe with the selected ASR backend (language auto-detected or user-specified via
--language). - Clean the transcript: simplified Chinese → deterministic replacements → (opt-in) LLM proofreading → post-LLM safety replacements.
- Paragraphize and write the requested final file(s).
Format Resolution Gate
- If the user explicitly requests
txt,pdf, orword/docx, use that format directly. - If the user requests multiple formats, generate all requested formats from the same cleaned transcript.
- If the user asks to transcribe a file but does not specify an output format, ask a short follow-up question before execution:
Which output format do you want: txt, pdf, or docx? - Do not guess the output format from context alone when the user did not say.
Dependency Gate
Before running, verify:
ffmpeg- local Python execution for
scripts/local_transcript.pyThis is an Apple-Silicon-first tool. Say so rather than presenting the fallbacks as an equivalent path — they are usable, not seamless.
| Platform | ASR | LLM proofreading | Chinese PDF |
|---|---|---|---|
| Apple Silicon | mlx-whisper (GPU/ANE), default |
mlx-lm + Qwen2.5, opt-in, no API key |
macOS system CJK fonts found automatically |
| Intel Mac / Linux / Windows | --backend faster-whisper (CPU, markedly slower) |
only --llm-backend claude (needs the claude CLI); local requires MLX |
must install a CJK font; the built-in candidates are macOS paths |
What ships with it
7 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.
- scripts/local_transcript.py 63 KB runs code
- scripts/make_reference_corpus.py 7.2 KB runs code
- scripts/run_quality_eval.py 18 KB runs code
- scripts/run_regression.sh 255 B runs code
- scripts/tests/stub_transcriber.py 1.4 KB runs code
- scripts/tests/test_local_transcript.py 50 KB runs code
- scripts/zh_replacements.json 605 B
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 · 312 lines · 139 tokens per session scan A afe15596e24c
local-transcript is a skill published in the GitHub repository johnqtcg/awesome-skills (30 stars, last pushed yesterday), licensed MIT. It adds 139 tokens to every session and 4,161 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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