SkillHub

reddit-quote-topaz

v1.0.0

Create an Instagram carousel from a popular-picks list with Reddit quotes + Topaz 2x upscaling. Cover = "clean" style ("Top CATEGORY in Destination"), attraction slides = "quote" style with Reddit quotes + subreddit attribution. All photos Topaz-enhanced before overlay. Trigger phrase "reddit-quote-...

Sourced from ClawHub, Authored by psyduckler

Installation

Please help me install the skill `reddit-quote-topaz` from SkillHub official store. npx skills add psyduckler/reddit-quote-topaz

Reddit Quote Carousel (Topaz Enhanced)

Same as reddit-quote-carousel but adds Topaz Labs 2x AI upscale after photo finding, before text overlays.

Trigger

Bernard says "reddit-quote-topaz" → use this skill. Bernard says "reddit-quote" → use reddit-quote-carousel (no Topaz).

Parameters

  • destination (required): City/region (e.g. "Barcelona")
  • category (required): What the picks are (e.g. "Cheap Eats", "Hidden Gems", "Date Night Spots")
  • popular_picks_url (required): tabiji.ai popular-picks page URL to pull attractions + Reddit quotes from
  • reddit_post_count (optional): Number of Reddit posts analyzed (for subtitle). Pull from the page if available.

Pipeline (3 chained sub-agents)

Working directory: /tmp/ig-reddit-quote/

Sub-agent 1: Scrape Picks + Find Photos + Topaz Enhance

  1. Fetch the popular-picks page via web_fetch to get:
  2. List of attractions (names)
  3. A compelling Reddit quote for each attraction (vivid, specific, personal — not generic praise)
  4. The subreddit each quote came from (e.g. "r/london", "r/AskLondon")
  5. Total Reddit post count if shown on the page

  6. Find photos using instagram-photo-find workflow:

  7. 1 hero photo for the destination (for cover slide)
  8. 1 photo per attraction (for quote slides)
  9. For each: web_search → download candidates → vision-score → keep best

  10. Topaz 2x Enhance each best photo:

TOPAZ_API_KEY=$(security find-generic-password -s "topaz-api-key" -w)

curl --request POST 
  --url https://api.topazlabs.com/image/v1/enhance 
  --header "X-API-Key: ${TOPAZ_API_KEY}" 
  --header 'accept: image/jpeg' 
  --header 'content-type: multipart/form-data' 
  --form 'model=Low Resolution V2' 
  --form 'output_scale_factor=2' 
  --form 'output_format=jpeg' 
  --form "image=@/tmp/ig-reddit-quote/${slug}-best.jpg" 
  --output "/tmp/ig-reddit-quote/${slug}-enhanced.jpg"

If sync returns JSON with process_id instead of image bytes, use async flow:

# Submit async
RESPONSE=$(curl -s --request POST 
  --url https://api.topazlabs.com/image/v1/enhance/async 
  --header "X-API-Key: ${TOPAZ_API_KEY}" 
  --header 'content-type: multipart/form-data' 
  --form 'model=Low Resolution V2' 
  --form 'output_scale_factor=2' 
  --form 'output_format=jpeg' 
  --form "image=@/tmp/ig-reddit-quote/${slug}-best.jpg")

PROCESS_ID=$(echo "$RESPONSE" | jq -r '.process_id')

# Poll until Completed
while true; do
  STATUS=$(curl -s --header "X-API-Key: ${TOPAZ_API_KEY}" 
    "https://api.topazlabs.com/image/v1/status/${PROCESS_ID}" | jq -r '.status')
  [ "$STATUS" = "Completed" ] && break
  sleep 3
done

# Download
curl -s --header "X-API-Key: ${TOPAZ_API_KEY}" 
  "https://api.topazlabs.com/image/v1/download/${PROCESS_ID}" 
  --output "/tmp/ig-reddit-quote/${slug}-enhanced.jpg"
  1. Write manifest to /tmp/ig-reddit-quote/manifest.json:
{
  "destination": "Barcelona",
  "category": "Cheap Eats",
  "reddit_post_count": 150,
  "cover_photo": "/tmp/ig-reddit-quote/cover-enhanced.jpg",
  "slides": [
    {
      "name": "Bar Cañete",
      "quote": "Went here on a random Tuesday and had the best patatas bravas of my life.",
      "subreddit": "r/barcelona",
      "photo": "/tmp/ig-reddit-quote/bar-canete-enhanced.jpg",
      "original": "/tmp/ig-reddit-quote/bar-canete-best.jpg",
      "source_url": "instagram.com/p/XXX/",
      "topaz_enhanced": true
    }
  ]
}

Sub-agent 2: Text Overlays

Read manifest. Create overlays using instagram-photo-text-overlay skill on enhanced images.

Slide 1 (Cover)clean style:

python3 /Users/psy/.openclaw/workspace/skills/instagram-photo-text-overlay/scripts/overlay.py 
  --input /tmp/ig-reddit-quote/cover-enhanced.jpg 
  --output /tmp/ig-reddit-quote/slide-1.jpg 
  --title "Top {COUNT} {CATEGORY} in {DESTINATION}" 
  --subtitle "Insider Takes from Reddit ({N}+ posts)" 
  --style clean --watermark "tabiji.ai"

Slides 2+quote style, one per attraction:

python3 /Users/psy/.openclaw/workspace/skills/instagram-photo-text-overlay/scripts/overlay.py 
  --input /tmp/ig-reddit-quote/{slug}-enhanced.jpg 
  --output /tmp/ig-reddit-quote/slide-{N}.jpg 
  --title "{ATTRACTION_NAME}" 
  --quote "{REDDIT_QUOTE}" 
  --author "{SUBREDDIT}" 
  --style quote --watermark "tabiji.ai"

Output: slides at /tmp/ig-reddit-quote/slide-{1-N}.jpg

Sub-agent 3: Publish to Instagram

  1. Host images in tabiji repo (img/instagram/), git push, use raw GitHub URLs
  2. Create carousel item containers
  3. Create carousel container with caption
  4. Publish
  5. Get permalink
  6. Cleanup hosted images + local temp files

Instagram API Auth

Keys from macOS Keychain: - instagram-access-token — Graph API token - instagram-account-id — IG user ID (17841449394591017)

Topaz API Auth

  • topaz-api-key — Topaz Labs API key (macOS Keychain)

Caption Template

{flag_emoji} Top {COUNT} {CATEGORY} in {DESTINATION}

Real recommendations from {N}+ Reddit posts 🧵

📍 Swipe for the spots + what Redditors actually said:
1. {Attraction 1}
2. {Attraction 2}
...

Full list with maps, prices & more Reddit recs 👉 {POPULAR_PICKS_URL}

💬 {PROVOCATIVE_QUESTION — e.g. "What's the most overrated restaurant you've been to abroad?" or "Would you trust a stranger's Reddit rec over a Michelin star?"}

#{destination} #{category_tag} #redditfinds #traveltips #foodietravel #localfavorites #tabiji

Tips

  • Pick quotes that are specific and personal — "best patatas bravas of my life" beats "this place is great"
  • Keep quotes under ~120 chars so they render well on the slide
  • If a quote is too long, trim it but keep the vivid part
  • The cover title should feel like a listicle: "Top 7 Cheap Eats in Barcelona"
  • Topaz model: Low Resolution V2 — designed for web-sourced images (our exact use case)
  • Topaz rate limits: If HTTP 429, use exponential backoff. Sequential processing of 6-8 images should be fine.
  • Keep originals in manifest so you can fall back if Topaz fails on a specific image