yt-intel

name	yt-intel
description	YouTube Content Intelligence Pipeline (UNATTENDED MODE). Extracts metadata + transcript from a YouTube video, applies the Fabric extract_wisdom analysis pattern, scores relevance to Delivery Factory, and (if relevant) generates a branded DOCX report, uploads to Google Drive, and posts a summary to Discord

YouTube Content Intelligence Pipeline — UNATTENDED MODE

This is an automated invocation. There is no interactive user. All decisions must be made autonomously based on the thresholds below.

You are executing the /yt-intel pipeline. This is a 6-step process that extracts intelligence from a YouTube video, gates it for relevance to Agentic Delivery / Delivery Factory, and (if relevant) produces a branded report with Drive archival and Discord notification.

Input: A YouTube URL (e.g., https://www.youtube.com/watch?v=VIDEO_ID)

---

Step 1: EXTRACT — Video Metadata + Transcript

1a. Metadata extraction

Run via Bash:

yt-dlp --dump-json "<URL>" > /tmp/yt-intel/metadata.json

Parse from the JSON:

Field	JSON key
Title	title
Channel	channel (or uploader)
Published date	upload_date (format: YYYYMMDD -> reformat to YYYY-MM-DD)
Duration	duration (seconds -> format as MM:SS or HH:MM:SS)
Views	view_count
Likes	like_count
Tags	tags (array -> comma-separated)
Chapters	chapters (array of {title, start_time, end_time})
Description	description (first 500 chars)

1b. Transcript extraction

# Download auto-generated subtitles
yt-dlp --write-auto-subs --sub-lang en --skip-download -o "/tmp/yt-intel/transcript" "<URL>"

This produces a .vtt file. Clean it:

# Parse VTT -> clean text (deduplicate, remove timestamps)
python3 -c "
import re, sys

with open('/tmp/yt-intel/transcript.en.vtt', 'r') as f:
    content = f.read()

# Remove VTT header and metadata
lines = content.split('\n')
text_lines = []
seen = set()
for line in lines:
    line = line.strip()
    # Skip timestamps, empty lines, VTT headers, and style tags
    if not line or '-->' in line or line.startswith('WEBVTT') or line.startswith('Kind:') or line.startswith('Language:') or line[0:1].isdigit() and len(line) < 10:
        continue
    # Remove HTML tags
    clean = re.sub(r'<[^>]+>', '', line)
    if clean and clean not in seen:
        seen.add(clean)
        text_lines.append(clean)

with open('/tmp/yt-intel/transcript_clean.txt', 'w') as f:
    f.write(' '.join(text_lines))
print(f'Transcript: {len(text_lines)} unique lines, {len(\" \".join(text_lines))} chars')
"

Read the clean transcript for analysis. If transcript extraction fails (no captions available), continue with metadata-only analysis.

---

Step 2: ANALYZE — Extract Wisdom

Apply the Fabric extract_wisdom structured analysis to the transcript. Produce these sections:

Output Structure

# YouTube Content Intelligence Report

> **Generated:** YYYY-MM-DD | **Pipeline:** /yt-intel (extract_wisdom)
> **Source:** [Title](URL)

---

## Video Metadata

| Field | Value |
|-------|-------|
| **Title** | ... |
| **Channel** | ... |
| **Published** | ... |
| **Duration** | ... |
| **Views** | ... |
| **Likes** | ... |
| **Tags** | ... |

---

## Summary
[3-5 sentence overview of the video's core argument and conclusions]

---

## Ideas
[10-15 numbered key concepts/ideas, each 1-2 sentences with **bold lead**]

---

## Insights
[5-8 numbered deeper analyses — non-obvious takeaways, each 2-3 sentences with **bold lead**]

---

## Quotes
[8-12 notable verbatim quotes from the speaker, attributed]

---

## Facts
[10-15 numbered factual claims with specific numbers, studies, or data points]

---

## Habits & Practices
[5-10 numbered actionable habits or practices mentioned]

---

## References
[Table: Type | Name | Context — for all tools, people, companies, studies, products mentioned]

---

## Recommendations
[8-12 numbered recommendations from the speaker]

---

## One-Sentence Takeaway
> **[Single most important point in bold]**

Quality bar: Each section must have substantive content. If the video doesn't support a section (e.g., no specific quotes), write "None identified" rather than fabricating content. Facts must be verifiable claims from the video, not your own additions.

---

Step 3: RELEVANCE GATE

Score the video's relevance to Agentic Delivery / Delivery Factory on a weighted 1-10 scale.

Scoring Criteria

Criterion	Weight	What counts as relevant
Dark factory / autonomous delivery	3x	Software factories, lights-out development, autonomous agents building software, zero-human-code workflows
AI coding tools & practices	2x	Claude Code, Codex, Cursor, Copilot, agentic coding, vibe coding, spec-driven development, AI-assisted dev workflows
DevOps / infrastructure automation	2x	CI/CD, containers, monitoring, deployment automation, GitOps, infrastructure-as-code
Enterprise software delivery	1x	Engineering management, team structures, developer productivity, delivery metrics, technical leadership
Business model / pricing / GTM	1x	SaaS pricing, product-led growth, AI-native business models, developer tools market
Irrelevant content	-5x	Gaming, lifestyle, politics, entertainment, cooking, sports, or other unrelated topics

Calculation

1. Rate each criterion 0-10
2. Multiply by weight
3. Sum weighted scores, divide by total weight (10)
4. Clamp to 1-10 range

Decision Thresholds (UNATTENDED MODE)

Score	Action
>= 6	PROCEED — Continue to Steps 4-6 (DOCX, Drive, Discord)
3 - 5	PROCEED WITH REDUCED PRIORITY — Continue to Steps 4-6 but prefix Discord title with [MARGINAL]. The pre-filter already scored this above threshold, so complete the analysis.
< 3	SKIP — Output the summary and score to stdout. Print: "Low relevance to Delivery Factory (score: X/10). Skipping Drive upload and Discord notification." Stop here.

Relevance Section (added to report if proceeding)

After the One-Sentence Takeaway, add:

---

## Relevance to Agentic Delivery

**Score: X/10**

[Brief justification of the score — 2-3 sentences]

| Video Concept | Agentic Delivery Equivalent |
|--------------|---------------------------|
| [concept from video] | [how it maps to our product/positioning] |
| ... | ... |

### Sales Talking Points Extracted

1. [talking point derived from video insights]
2. ...

---

Step 4: GENERATE DOCX (only if relevance gate passes)

4a. Write Markdown report

Save the complete report (Steps 2 + 3 output) to:

/tmp/yt-intel/YYYY-MM-DD_<video-title-slug>_<channel-slug>_extract-wisdom.md

Slug rules: lowercase, hyphens for spaces, strip special chars, max 50 chars per slug.

4b. Convert to branded DOCX

Use the Pandoc MCP with the Agentic Delivery reference template:

mcp__pandoc__convert-contents
  input_file: "/tmp/yt-intel/YYYY-MM-DD_<slug>.md"
  output_format: "docx"
  reference_doc: "/home/burhan/github/dev-delivery-factory-deployment/.claude/templates/AgenticDelivery_Document-Template_v2.docx"
  output_file: "/tmp/yt-intel/YYYY-MM-DD_<video-title-slug>_<channel-slug>_extract-wisdom.docx"

Verify the DOCX was created:

ls -la /tmp/yt-intel/*.docx

---

Step 5: UPLOAD TO DRIVE (only if relevance gate passes)

5a. Copy files to accessible path

The Google Workspace MCP restricts file:// URLs to ALLOWED_FILE_DIRS ($HOME and /tmp). Files in /tmp/yt-intel/ are already accessible.

5b. Upload DOCX report

mcp__google-workspace__create_drive_file
  file_name: "YYYY-MM-DD_<video-title-slug>_<channel-slug>_extract-wisdom.docx"
  fileUrl: "file:///tmp/yt-intel/<filename>.docx"
  folder_id: "1ISaW-3u8Kcrl_sfnGUR8pYfivlmazFzD"
  user_google_email: "[e-mail]"

Folder: 05-YouTube-Intelligence/Summaries/ (ID: 1ISaW-3u8Kcrl_sfnGUR8pYfivlmazFzD)

IMPORTANT: If create_drive_file uploads with wrong MIME type (e.g. text/plain), the DOCX will render as garbage on Drive. Verify the upload is application/vnd.openxmlformats-officedocument.wordprocessingml.document. If it fails, copy the DOCX to $HOME first and retry from there.

5c. Upload clean transcript

mcp__google-workspace__create_drive_file
  file_name: "YYYY-MM-DD_<video-title-slug>_transcript.txt"
  fileUrl: "file:///tmp/yt-intel/transcript_clean.txt"
  folder_id: "1IZBTofol-NwDEPWRzpc_HOy8PVr2JsXy"
  user_google_email: "[e-mail]"

Folder: 05-YouTube-Intelligence/Transcripts/ (ID: 1IZBTofol-NwDEPWRzpc_HOy8PVr2JsXy)

5d. Get shareable link

mcp__google-workspace__get_drive_shareable_link
  file_id: <uploaded DOCX file ID>
  user_google_email: "[e-mail]"

Save this link for the Discord message.

---

Step 6: POST TO DISCORD (only if relevance gate passes)

Channel

#ad-intel — Channel ID: 1475173738646470826

Message Format

**INTEL REPORT** — <Clickbait Title>

<2-3 sentence hook with the most provocative or surprising finding from the video. Make it compelling enough that someone scrolling Discord stops to read.>

**Key stats:**
- <stat 1 — most striking number/claim>
- <stat 2>
- <stat 3>
- <stat 4 (optional)>

**Relevance (X/10):** <One sentence on why this matters for Delivery Factory>

Full analysis: <Drive shareable link>
Source: <YouTube URL>

Constraints

• Max 2000 characters (Discord message limit)
• The clickbait title should be your own reframing, not just the video title
• The hook should make someone want to read the full report
• Stats should be specific numbers, not vague claims
• Do NOT use >>> block quotes (renders poorly in Discord)

Send via Discord MCP

Use discord_discover to find the send message action, then discord_execute to post. The channel ID is 1475173738646470826.

---

Error Handling

Error	Recovery
yt-dlp not found	Pipeline error — yt-dlp must be pre-installed
No subtitles available	Continue with metadata-only analysis
Pandoc conversion fails	Check pandoc is installed. Fall back to uploading the .md file
Drive upload fails	Check Google auth. Retry once.
Discord post fails	Log error and continue — report is still on Drive
Video is age-restricted/private	Log error and skip

---

Working Directory

All intermediate files go to /tmp/yt-intel/. Create it if it doesn't exist:

mkdir -p /tmp/yt-intel

Clean up previous run files at the start of each invocation, but do not delete files from other videos (check filenames).