Kheish Compatibility

This skill is repo-local and stays inactive until explicitly activated.

When the original instructions refer to legacy tool names, use these Kheish mappings:

• terminal => bash
• web_extract => web_fetch, plus web_search when discovery is needed
• search_files => grep_search and glob_search
• browser_* tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitly

When the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.

YouTube Content Tool

Extract transcripts from YouTube videos and convert them into useful formats.

Setup

bash
pip install youtube-transcript-api

Helper Script

SKILL_DIR is the directory containing this SKILL.md file. The script accepts any standard YouTube URL format, short links (youtu.be), shorts, embeds, live links, or a raw 11-character video ID.

bash
# JSON output with metadata
python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"

# Plain text (good for piping into further processing)
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only

# With timestamps
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps

# Specific language with fallback chain
python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en

Output Formats

After fetching the transcript, format it based on what the user asks for:

• Chapters: Group by topic shifts, output timestamped chapter list
• Summary: Concise 5-10 sentence overview of the entire video
• Chapter summaries: Chapters with a short paragraph summary for each
• Thread: Twitter/X thread format — numbered posts, each under 280 chars
• Blog post: Full article with title, sections, and key takeaways
• Quotes: Notable quotes with timestamps

Example — Chapters Output

00:00 Introduction — host opens with the problem statement
03:45 Background — prior work and why existing solutions fall short
12:20 Core method — walkthrough of the proposed approach
24:10 Results — benchmark comparisons and key takeaways
31:55 Q&A — audience questions on scalability and next steps

Workflow

1. Fetch the transcript using the helper script with --text-only --timestamps.
2. Validate: confirm the output is non-empty and in the expected language. If empty, retry without --language to get any available transcript. If still empty, tell the user the video likely has transcripts disabled.
3. Chunk if needed: if the transcript exceeds ~50K characters, split into overlapping chunks (~40K with 2K overlap) and summarize each chunk before merging.
4. Transform into the requested output format. If the user did not specify a format, default to a summary.
5. Verify: re-read the transformed output to check for coherence, correct timestamps, and completeness before presenting.

Error Handling

• Transcript disabled: tell the user; suggest they check if subtitles are available on the video page.
• Private/unavailable video: relay the error and ask the user to verify the URL.
• No matching language: retry without --language to fetch any available transcript, then note the actual language to the user.
• Dependency missing: run pip install youtube-transcript-api and retry.