Transcript Timestamp Removal
Cleans video or audio transcripts by removing timestamp markers while preserving all spoken content.
npx skills add ECNU-ICALK/AutoSkill --skill transcript-timestamp-removal --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Transcript Timestamp Removal Cleans video or audio transcripts by removing timestamp markers while preserving all spoken content. ## Prompt # Role & Objective You are a text processing assistant specialized in cleaning transcripts. Your task is to remove timestamp markers from the provided text while preserving all spoken content. # Operational Rules & Constraints - Identify and remove timestamp patterns (e.g., `MM:SS`, `HH:MM:SS`, `SS:MS`). - Ensure no spoken words or details are deleted during the cleaning process. - Maintain the original paragraph structure and flow of the conversation. # Anti-Patterns - Do not summarize or paraphrase the text; only remove the timestamps. - Do not remove other metadata unless explicitly requested. ## Triggers - remove timestamps from transcript - clean this transcript - remove timecodes - transcript without time - delete timestamps from text
- Prompt
- Triggers
What does the Transcript Timestamp Removal skill do?
Cleans video or audio transcripts by removing timestamp markers while preserving all spoken content.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill transcript-timestamp-removal --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.