trx

name	trx
description	Transcribe audio/video using trx CLI and post-process results with agent corrections. Use when: (1) user wants to transcribe a video or audio file, (2) user shares a YouTube/Twitter/Instagram URL for transcription, (3) user says "transcribe", "subtitles", "srt", "transcript", (4) user wants to fix/clean up a whisper transcription, (5) user asks to extract text from a video.
metadata	{"author":"Railly Hugo","version":"0.4.0"}

trx -- Agent-First Transcription CLI

Install: npx skills add crafter-station/trx -g

Prerequisites

Check setup: trx doctor --output json. If dependencies missing, run trx init.

Install: bun add -g @crafter/trx

Workflow

1. Dry-run first (always)

trx transcribe <input> --dry-run --output json

Validates input, checks dependencies, shows execution plan without running.

2. Transcribe

For URLs (YouTube, Twitter, Instagram, etc.):

trx transcribe "https://youtube.com/watch?v=..." --output json

For local files:

trx transcribe ./recording.mp4 --output json

Agent-optimized (text only, saves tokens):

trx transcribe <input> --fields text --output json

Backends (v0.4.0+)

trx supports two backends: local Whisper (default) and OpenAI API.

# Local Whisper (default, offline, free)
trx transcribe <input> --backend local

# OpenAI API (faster, SOTA accuracy, requires OPENAI_API_KEY)
trx transcribe <input> --backend openai

OpenAI models:

• gpt-4o-transcribe — SOTA accuracy (default for openai backend)
• gpt-4o-mini-transcribe — cheapest
• whisper-1 — legacy, supports per-segment SRT timestamps

Local models: tiny, base, small, medium, large-v3-turbo, large.

Set backend persistently via trx init --backend openai or in config.

3. Post-process (fix whisper mistakes)

After transcription, read the .txt output and apply corrections. Read whisper-fixes.md for common patterns.

Correction checklist:

1. Punctuation: Whisper drops periods at paragraph boundaries and misplaces commas. Fix sentence boundaries.
2. Accents (Spanish): Whisper often drops diacritics. Restore: como -> como/cmo, esta -> esta/est, mas -> mas/ms.
3. Technical terms: Whisper misspells domain-specific words. Ask user for a glossary or infer from context.
4. Repeated phrases: Whisper sometimes stutters on word boundaries. Remove exact consecutive duplicates.
5. Speaker attribution: If user provides speaker names, insert [Speaker Name]: markers.
6. Filler words: Remove "um", "uh", "este", "o sea" if user wants clean output.
7. Timestamp alignment: If editing .srt, preserve the timestamp structure. Only modify text between timestamps.

4. Schema introspection

trx schema transcribe
trx schema init

Commands

Command	Example
init	trx init --model small
transcribe	trx transcribe <url-or-file> --output json
doctor	trx doctor --output json
schema	trx schema transcribe

Shorthand

trx <input> is equivalent to trx transcribe <input>.

Output format

• --output json: Machine-readable (default when piped)
• --output table: Human-readable with progress (default when TTY)
• --fields text: Only return transcript text (saves tokens)
• --fields metadata: Only return metadata (language, model)
• --dry-run: Validate without executing

Flags reference

Flag	Description	Default
--backend <name>	local or openai	from config
--language <code>	ISO 639-1 language code	auto (from config)
--model <size>	Override model: tiny, base, small, medium, large-v3-turbo, large, gpt-4o-transcribe, gpt-4o-mini-transcribe, whisper-1	from config
--output-dir <dir>	Output directory	. (cwd)
--no-download	Skip yt-dlp (local files only)	false
--no-clean	Skip ffmpeg audio cleaning	false
--json <payload>	Raw JSON input	-

Edge cases

• yt-dlp extension mismatch: yt-dlp sometimes outputs .mp4.webm instead of .mp4. The CLI handles this by scanning for the downloaded file by prefix.
• Large files (>1hr): Whisper processes in segments. Works but is slow on CPU. Consider --model tiny for speed.
• No GPU: whisper-cli uses CPU by default. Acceptable for tiny/base/small models.
• Auto-detect language: When --language auto, Whisper detects the language from the first 30 seconds. For multilingual content, specify the primary language.