wjs-transcribing-audio

wjs-transcribing-audio is a skill for Claude Code, Codex from jianshuo/claude-skills. It costs 128 tokens per session (4,814 once invoked), scanned B, original, MIT.

An audio and video transcription workflow that creates a timestamped SRT subtitle file in the language spoken. SRT is a subtitle format containing text plus the times when each line appears.

In plain words
What is it for?
Use it to make source-language subtitles or transcripts from audio and video, including Chinese, English, Spanish, Portuguese, French, Italian, Japanese, and Korean recordings.
Why use it?
It removes the need to type speech and timing by hand. It chooses a speech-recognition service based on the source language and includes word-level timing for assembling subtitles.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to make source-language subtitles or transcripts from audio and video, including Chinese, English, Spanish, Portuguese, French, Italian, Japanese, and Korean recordings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jianshuo/claude-skills/wjs-transcribing-audio
Install

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.

Any agent
npx skills add jianshuo/claude-skills --skill wjs-transcribing-audio
Clone the repo
git clone --depth 1 https://github.com/jianshuo/claude-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin wjs-transcribing-audio/plugin install wjs-transcribing-audio after adding the marketplace above.

Wrote 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.

agentmods badge for wjs-transcribing-audio

README.md
[![agentmods](https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-transcribing-audio/github.svg)](https://agentmods.dev/skills/jianshuo/claude-skills/wjs-transcribing-audio)
Your own site
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-transcribing-audio"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-transcribing-audio/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.

agentmods 80×15 button for wjs-transcribing-audio

Your own site · 80×15
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-transcribing-audio"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-transcribing-audio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 128 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,814 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 181
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium Data Exfiltration · line 67
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 68
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium MCP Rug Pull · line 134
    uvx/uv tool run commands without ==version create a rug-pull risk.
    Fix: Pin the version: uvx package-name==1.2.3
  • medium MCP Rug Pull · line 190
    uvx/uv tool run commands without ==version create a rug-pull risk.
    Fix: Pin the version: uvx package-name==1.2.3
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00128 $0.04814
Opus 5 $0.00064 $0.02407
Sonnet 5 $0.00026 $0.00963
Haiku 4.5 $0.00013 $0.00481

Measured 12d ago against content hash 8a790d975419, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade B, and why

wjs-transcribing-audio scanned grade B 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 12d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/build_srt_from_asr.py, scripts/volc_asr_stream.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

r = httpx.post( "https://api.openai.com/v1/audio/transcriptions",
wjs-transcribing-audio/SKILL.md · 247 lines

How it starts

The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.

wjs-transcribing-audio

Spoken audio in → timestamped SRT in the same language out. This skill stops at the source-language SRT. Translation to another language is the next skill (/wjs-translating-subtitles).

When to use

  • User provides a video or audio file and wants a transcript / SRT in the source language.
  • User already has a translated SRT and the source SRT is missing.
  • User asks "做 SRT" / "make subtitles" / "出逐字稿" with no translation step requested yet.

When NOT to use

  • Source-language SRT already exists → skip straight to /wjs-translating-subtitles.
  • User wants the transcript in a different language than spoken → run this skill first, then /wjs-translating-subtitles.
  • User wants only the dub or burn-in → if SRT exists, skip; otherwise run this first.

Routing: which engine

Source language Default engine Why
Chinese (zh-CN, zh-HK, zh-TW) Volcano (豆包) ASR Materially better accuracy than Whisper for Chinese — user's standing preference
Any other (es, en, pt, fr, it, ja, ko, …) OpenAI Whisper API with word-level granularity Whisper's multilingual is strong; word timestamps let us assemble cues ourselves
Offline / no API access Local openai-whisper (medium) Quality floor; same loop/blob failure modes apply

For Chinese, do not default to Whisper unless the user explicitly asks for it or Volcano is unavailable. This is a deliberate routing decision — see user's memory on Chinese ASR priority.

OpenAI Whisper API path (non-Chinese, and Chinese fallback)

The key principle: do not request response_format=srt. Whisper cue-segmentation fails on long monologues (30-second blob cues) and quiet stretches (loop hallucinations). Request word-level timestamps and assemble cues yourself — the post-processing is deterministic and free.

Why not response_format=srt

Two failure modes that wreck whisper-1 SRT output on long content:

  1. 30-second blob cues. In long monologues, whisper-1 with response_format=srt emits one cue covering the full 30s condition_on_previous_text window. Transcript is fine; timing is unusable for on-screen reading.
  2. Loop hallucination on quiet tails. Greedy temperature=0 on low-energy audio produces "你如果不把拥抱浪费写在这上面,你很难的" repeated 50 times.

Read the full file on GitHub · 247 lines

Files

What ships with it

2 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.

Changes

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.

  1. 12d ago First seen · 247 lines · 128 tokens per session scan B 8a790d975419

Subscribe to this mod's changes

wjs-transcribing-audio is a skill published in the GitHub repository jianshuo/claude-skills (129 stars, last pushed 23d ago), licensed MIT. It adds 128 tokens to every session and 4,814 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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