You are helping me build the following AI agent workflow.

## Goal
YouTube Video Transcription And Summary To Telegram: Send any YouTube link via Telegram to instantly receive a structured summary with key insights, tips, and quotes.

## Specification
- What it does: Send a YouTube link via Telegram to instantly receive a structured summary featuring key insights, tips, and quotes. You get this result after the system fetches the full transcript, processes it with an AI model, and returns the formatted content directly to your chat.
- Trigger: Triggered by an event (Manual · on new link sent to Telegram)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Telegram: Trigger and delivery of summaries
  - Supadata API: Fetching video transcripts
  - OpenAI Chat Model: Summarizing content via GPT-4o

## Known pitfalls, handle each one explicitly in your implementation
1. Supadata API calls may fail on private or restricted videos, so add error handling that notifies the user of access issues.
2. Long transcripts can exceed token limits, so implement a chunking strategy or use a model with a larger context window.
3. Telegram message length is capped at 4096 characters, so truncate long summaries and append a link to the full transcript if needed.

## Reference implementation
https://n8n.io/workflows/4964 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/youtube-video-transcription-and-summary-to-telegram/ via usecasesforagents.com