light-web-youtubesummarizer

name

light-web-YoutubeSummarizer

description

Summarize a YouTube transcript .txt file — cleans it first, then produces a structured summary (with a Delphi 13 / LightSaber adaptation section when the talk is about programming). Launches the light-web-YoutubeSummarizer agent. Use when the user invokes `/light-web-YoutubeSummarizer`, says "summarize this transcript", "what can I learn from this video for my Delphi work", or points at a file in c:\AI\Claude Code\Transcript\.

/light-web-YoutubeSummarizer — Transcript Summarizer

This is a thin launcher. Your only job is to resolve the transcript path(s) and launch the light-web-YoutubeSummarizer agent, once per file. You do NOT clean or summarize anything yourself — the agent runs the cleanup script, reads the transcript, and returns only the final summary. You (the launcher) ask where to save and pass the path to each agent.

Step 1 — Resolve the input

The argument is in $args. The user may pass a single .txt path, several paths, a folder, or nothing. Build the transcript list:

• One or more explicit .txt paths → use them as-is.
• A folder → Glob <folder>/*.txt for the file list. Skip any file whose base name ends with (summary) — those are outputs, not transcripts. If both X.txt and X (cleaned).txt exist, keep only the (cleaned) one (the agent handles cleaning, but no point feeding the raw twin as a second job).
• No argument → ask the user for the transcript path, defaulting to the scratch folder c:\AI\Claude Code\Transcript\. If that folder has exactly one un-summarized .txt, offer it.

Print the resolved transcript list before launching.

Step 2 — Ask where to save, then launch the agents

Subagents cannot prompt the user, so you ask the save policy here — one AskUserQuestion, the recommended option first:

1. Save each summary next to its transcript (Recommended) — <dir>/<basename without "(cleaned)"> (summary).md.
2. Save all to c:\AI\Claude Code\Transcript\ — same basename.
3. Don't save — just return each summary in chat.

Then, for each file in the list, call the Agent tool with subagent_type: "light-web-YoutubeSummarizer", passing the single file path and the concrete OutputPath you computed from the chosen policy (or "don't save"). They can run in parallel — the save location is already resolved, so no interactive prompts collide.

The agent: cleans the transcript (if not already cleaned) → reads it whole → classifies the topic → writes the summary (adding the Delphi/LightSaber section for programming talks) → returns only the summary.

Relay each summary the agent returns.

Step 3 — Summary

If you processed several transcripts, print a one-line index of which were summarized and where each was saved. For a single file, the agent's output is enough — no extra wrap-up needed.

Rules

• You do not summarize. Resolving the path(s), asking the save location, launching the agent per file, and relaying results is your entire job. The agent does the cleaning and summarizing.
• You ask where to save, not the agent. Subagents cannot prompt the user — resolve the save location in the launcher and pass the concrete OutputPath to each agent.