videocut-clip-oral

Original：🇨🇳 Chinese

Translated

Spoken video transcription and slip-of-the-tongue recognition. Generate review drafts and deletion task checklists. Trigger phrases: edit spoken video, process video, recognize slip-of-the-tongue

1installs

Sourcezrt-ai-lab/opencode-skills

Added on2026-02-14

NPX Install

npx skill4agent add zrt-ai-lab/opencode-skills videocut-clip-oral

SKILL.md Content (Chinese)

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Edit Spoken Video

Transcription + Slip-of-the-tongue/Silence Recognition → Generate Review Draft

Quick Usage

User: Help me edit this spoken video
User: Process this video

Workflow

1. FunASR 30s segmented transcription (character-level timestamps)
    ↓
2. Recognize slip-of-the-tongue (sentence-by-sentence check)
    ↓
3. Recognize micro slip-of-the-tongue (VAD detects short segments)
    ↓
4. Recognize filler words (um/ah/eh, etc.)
    ↓
5. Recognize silence (≥1s)
    ↓
6. Generate review draft (timestamp-driven)
    ↓
7. Output deletion task TodoList
    ↓
[Await User Confirmation] → After user confirmation, execute /videocut:edit

⚠️ Why use 30s segmentation

FunASR has timestamp drift for long videos, 30s segmentation avoids this issue.

Progress TodoList

Created on startup:

- [ ] Read "Transcription Best Practices" → Transcribe video
- [ ] Read "Slip-of-the-Tongue Recognition Methodology" → Recognize slip-of-the-tongue
- [ ] VAD detection for micro slip-of-the-tongue (short segments < 0.5s)
- [ ] Scan filler words (um/ah/eh, etc.)
- [ ] Recognize silence (≥1s)
- [ ] Generate review draft
- [ ] Output deletion task checklist

⚠️ Must read methodology before execution

Stage	Read First	Then Execute
Transcription	`tips/Transcription Best Practices.md`	Call ASR
Slip-of-the-tongue Recognition	`tips/Slip-of-the-Tongue Recognition Methodology.md`	Sentence-by-sentence analysis

Core: Timestamp-driven

Deletion Task Format

Each item must be marked with precise timestamps

(start-end)

:

Slip-of-the-tongue (N instances):
- [ ] 1. `(start-end)` Delete "incorrect text" → Keep "correct text"

Filler words (N instances):
- [ ] 1. `(end of previous word - start of next word)` Delete "um" Context: XX【um】YY

Silence (N instances):
- [ ] 1. `(start-end)` Silence Xs

Slip-of-the-tongue Types

Type	Example	Deletion Strategy
Repetition	`Pull full new pull full`	Delete only the difference ("new")
Replacement	`AI is AI will`	Delete the first complete version ("AI is")
Stutter	`Listen will will`	Delete the first repeated character

⚠️ Key Rules

Timestamp-driven: Review draft directly marks timestamps, no need to search text during editing
Token-by-token analysis: For slip-of-the-tongue where "delete front, keep back", must check timestamps token by token
Check time span: If the time span of slip-of-the-tongue > 2 seconds, there must be silence, need to split

Output Files

01-xxx-v1_transcript.json  # Transcription result (with timestamps)
01-xxx-v1_Review Draft.md        # Slip-of-the-tongue review draft

Display Requirements

After generating the review draft, must show it to the user:

Write to file
```
01-xxx-v1_Review Draft.md
```
Read and display the content
Wait for user confirmation on which items to delete

Methodology

See

tips/Slip-of-the-Tongue Recognition Methodology.md

:

Slip-of-the-tongue recognition methods (sentence-by-sentence check)
Precise processing of "delete front, keep back"
FunASR timestamp alignment rules