--- name: clawdbites description: Extract recipes from Instagram reels. Use when a user sends an Instagram reel link and wants to get the recipe from the caption. Parses ingredients, instructions, and macros into a clean format. homepage: https://github.com/kylelol/ClawdBites metadata: {"clawdbot":{"emoji":"🦞","os":["darwin","linux"],"requires":{"bins":["yt-dlp","ffmpeg","whisper"]},"install":[{"id":"yt-dlp","kind":"brew","formula":"yt-dlp","bins":["yt-dlp"],"label":"Install yt-dlp via Homebrew"},{"id":"ffmpeg","kind":"brew","formula":"ffmpeg","bins":["ffmpeg"],"label":"Install ffmpeg via Homebrew"},{"id":"whisper","kind":"shell","command":"pip3 install --user openai-whisper","label":"Install Whisper (local, no API key)"}]}} ---

Instagram Recipe Extractor

Extract recipes from Instagram reels using a multi-layered approach:

1. Caption parsing — Instant, check description first
2. Audio transcription — Whisper (local, no API key)
3. Frame analysis — Vision model for on-screen text

No Instagram login required. Works on public reels.

When to Use

• User sends an Instagram reel link
• User mentions "recipe from Instagram" or "save this reel"
• User wants to extract recipe details from a video post

How It Works (MANDATORY FLOW)

ALWAYS follow this complete flow — do not stop after caption if instructions are missing:

1. User sends Instagram reel URL
2. Extract metadata using yt-dlp (--dump-json)
3. Parse the caption for recipe details
4. Check completeness: Does caption have BOTH ingredients AND instructions?

- ✅ YES: Present the recipe - ❌ NO (missing instructions or incomplete): Automatically proceed to audio transcription — do NOT stop or ask the user

1. If audio transcription needed:

- Download video: yt-dlp -o "/tmp/reel.mp4" "URL" - Extract audio: ffmpeg -y -i /tmp/reel.mp4 -vn -acodec pcm_s16le -ar 16000 -ac 1 /tmp/reel.wav - Transcribe: whisper /tmp/reel.wav --model base --output_format txt --output_dir /tmp - Merge caption ingredients with audio instructions

1. Present clean, formatted recipe (combining caption + audio as needed)
2. User decides what to do (save to notes, add to wishlist, etc.)

Completeness check heuristics:

• Has ingredients = contains 3+ quantity+item patterns (e.g., "1 cup flour", "2 lbs chicken")
• Has instructions = contains action verbs (blend, cook, bake, mix, pour, add) + sequence OR numbered steps

Extraction Command

yt-dlp --dump-json "https://www.instagram.com/reel/SHORTCODE/" 2>/dev/null

Key fields from JSON output:

• description — The caption containing the recipe
• uploader — Creator's name
• channel — Creator's handle
• webpage_url — Original URL
• like_count — Popularity indicator

Recipe Parsing

Look for these patterns in the caption:

Macros:

• "X Calories | Xg P | Xg C | Xg F"
• "Macros per serving"
• "Cal/Protein/Carbs/Fat"

Ingredients:

• Lines starting with quantities (1 cup, 2 tbsp, 24oz)
• Lines with measurement units
• Emoji bullet points (🥩 🌽 🧀 etc.)

Sections:

• "For the [component]:"
• "Ingredients:"
• "Instructions:"
• "Directions:"

Output Format

Present extracted recipe cleanly:

## [Recipe Name]
*From @[handle]*

**Macros (per serving):** X cal | Xg P | Xg C | Xg F

### Ingredients
- [ingredient 1]
- [ingredient 2]
...

### Instructions
1. [step 1]
2. [step 2]
...

---
Source: [original URL]

User Actions After Extraction

Let the user decide what to do:

• "Save to my recipes" → Save to Apple Notes (if meal-planner skill available)
• "Add to wishlist" → Save to memory/recipe-wishlist.json
• "Just show me" → Display only, no save
• "Plan this for next week" → Hand off to meal-planner skill

Wishlist Storage

Optional storage for recipes user wants to try later:

memory/recipe-wishlist.json:

{
  "recipes": [
    {
      "name": "Recipe Name",
      "source": "instagram",
      "sourceUrl": "https://instagram.com/reel/...",
      "handle": "@creator",
      "addedDate": "2026-01-26",
      "tried": false,
      "macros": {
        "calories": 585,
        "protein": 56,
        "carbs": 25,
        "fat": 28,
        "servings": 3
      },
      "ingredients": [...],
      "instructions": [...]
    }
  ]
}

Error Handling

If yt-dlp fails:

• Check if URL is valid Instagram reel format
• May be a private account — inform user
• Suggest user paste caption text manually as fallback

If no recipe found in caption (IMPORTANT):

After extracting, scan the caption for recipe indicators:

• Ingredient quantities (numbers + units like oz, cups, tbsp, lbs)
• Recipe sections ("For the...", "Ingredients:", "Instructions:")
• Cooking verbs (bake, cook, sauté, mix, combine)
• Macro information (calories, protein, carbs, fat)

If none found, tell the user clearly:

> "I pulled the caption but it doesn't look like the recipe is there — it might just be a teaser or the recipe is only shown in the video itself. Here's what the caption says: > > [show caption] > > A few options: > 1. Check the comments — sometimes creators post recipes there > 2. Check their bio link — might lead to the full recipe > 3. Describe what you saw in the video and I can help find a similar recipe"

Recipe detection heuristics:

HAS_RECIPE if caption contains:
- 3+ ingredient-like patterns (quantity + food item)
- OR "recipe" + ingredient list
- OR macro breakdown + ingredients
- OR numbered/bulleted instructions

NO_RECIPE if caption is:
- Mostly hashtags
- Just a description/teaser
- Under 100 characters
- No quantities or measurements

Integration with meal-planner

The meal-planner skill can reference this skill:

• When planning meals, check wishlist for untried recipes
• Suggest wishlist recipes that match pantry items
• Mark recipes as "tried" after they're used in a meal plan

Audio Transcription (V2) — MANDATORY FALLBACK

When caption is missing instructions, ALWAYS transcribe the audio automatically. Do not stop and ask the user — just do it. This is the most common case since creators often put ingredients in captions but speak the instructions.

Step 1: Download video

yt-dlp -o "/tmp/reel.mp4" "https://instagram.com/reel/XXX"

Step 2: Extract audio

ffmpeg -i /tmp/reel.mp4 -vn -acodec pcm_s16le -ar 16000 -ac 1 /tmp/reel.wav

Step 3: Transcribe with Whisper

/Users/kylekirkland/Library/Python/3.14/bin/whisper /tmp/reel.wav --model base --output_format txt --output_dir /tmp

Step 4: Parse transcript for recipe Look for cooking instructions, ingredients mentioned verbally.

Inference for Missing Measurements

ALWAYS infer quantities when not provided. Never present a recipe without amounts — estimate based on context and standard package sizes.

Vague Language → Specific Amounts

| What they say | Infer | |--------------|-------| | "some chicken" | ~1 lb | | "a bit of garlic" | 2-3 cloves | | "handful of spinach" | ~2 cups | | "drizzle of oil" | 1-2 tbsp | | "season to taste" | ½ tsp salt, ¼ tsp pepper | | "splash of soy sauce" | 1-2 tbsp | | "a few tablespoons" | 2-3 tbsp | | "some rice" | 1 cup dry | | "cheese on top" | ½ - 1 cup shredded | | "diced onion" | 1 medium onion | | "bell peppers" | 2 peppers |

Standard Package Sizes (when item mentioned without amount)

| Ingredient | Standard Package | Infer | |------------|------------------|-------| | Puff pastry | 17oz sheet | 1 sheet | | Ground beef/turkey | 1 lb pack | 1 lb | | Chicken breast | ~1.5 lb pack | 1.5 lbs | | Sausage links | 14oz / 4-5 links | 1 package | | Bacon | 12oz / 12 slices | ½ package (6 slices) | | Shredded cheese | 8oz bag | 1-2 cups | | Tortillas | 8-10 count | 1 package | | Canned beans | 15oz can | 1 can | | Broth/stock | 32oz carton | 1-2 cups | | Pasta | 16oz box | 8oz (half box) | | Rice | 2 lb bag | 1-2 cups dry |

Context-Aware Scaling

...