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IMDb Awards Access Skill

Extract comprehensive awards and nominations data from IMDb for both people (actors, directors, etc.) and titles (movies, TV shows).

Overview

This skill bypasses IMDb's AWS WAF anti-bot protection to reliably extract structured awards data that would otherwise be blocked or return 402/403 errors. It provides detailed information about:

• Award events (Academy Awards, Golden Globes, etc.)
• Individual nominations and wins
• Categories and years
• Associated works and people
• Win/nomination status

Features

• Anti-Bot Bypass: Uses Playwright with stealth settings to overcome AWS WAF challenges
• Structured Data: Returns parsed, easy-to-use JSON instead of raw HTML
• Dual Support: Works for both names (nm...) and titles (tt...)
• Rich Details: Includes images, captions, event links, and more
• Summary Stats: Provides aggregate counts of wins and nominations

Functions

get_name_awards

Get awards for an IMDb name (person).

result = await execute({
    "function": "get_name_awards",
    "name_id": "nm0000149"  # Jodie Foster
})

Parameters:

• name_id (required): IMDb name ID (e.g., 'nm0000149')

get_title_awards

Get awards for an IMDb title (movie/TV show).

result = await execute({
    "function": "get_title_awards",
    "title_id": "tt0944835"  # Salt (2010)
})

Parameters:

• title_id (required): IMDb title ID (e.g., 'tt0944835')

get_awards

Auto-detect entity type and get awards.

result = await execute({
    "function": "get_awards",
    "imdb_id": "nm0000149"  # Auto-detects name vs title
})

Parameters:

• imdb_id (required): IMDb ID (nm... or tt...)

Response Structure

Successful Response

{
  "success": true,
  "entity_id": "nm0000149",
  "entity_type": "name",
  "entity_name": "Jodie Foster",
  "primary_image": "https://m.media-amazon.com/images/...",
  "summary": {
    "category_count": 88,
    "total_wins": 62,
    "total_nominations": 156
  },
  "categories": [
    {
      "event_id": "ev0000003",
      "event_name": "Academy Awards, USA",
      "event_href": "/event/ev0000003/?ref_=nmawd",
      "total_awards": 5,
      "awards": [
        {
          "id": "an0049441",
          "year": 1992,
          "status": "Winner",
          "award_name": "Oscar",
          "category": "Best Actress in a Leading Role",
          "title": "The Silence of the Lambs",
          "title_id": "tt0102926",
          "names": [],
          "image_url": "https://m.media-amazon.com/images/...",
          "image_caption": "Jodie Foster in The Silence of the Lambs (1991)"
        }
      ]
    }
  ]
}

Error Response

{
  "success": false,
  "error": "Timeout waiting for page to load",
  "error_code": "TIMEOUT",
  "url": "https://www.imdb.com/name/nm0000149/awards/"
}

Error Codes

Examples

Example 1: Get awards for an actor

# Jodie Foster - Academy Award winner
result = await execute({
    "function": "get_name_awards",
    "name_id": "nm0000149"
})

print(f"{result['entity_name']}: {result['summary']['total_wins']} wins, {result['summary']['total_nominations']} nominations")

# Find Oscar wins
for category in result['categories']:
    if category['event_name'] == 'Academy Awards, USA':
        for award in category['awards']:
            if award['status'] == 'Winner':
                print(f"  {award['year']}: {award['category']} - {award['title']}")

Output:

Jodie Foster: 62 wins, 156 nominations
  1992: Best Actress in a Leading Role - The Silence of the Lambs
  1989: Best Actress in a Leading Role - The Accused

Example 2: Get awards for a movie

# The Silence of the Lambs
result = await execute({
    "function": "get_title_awards",
    "title_id": "tt0102926"
})

print(f"{result['entity_title']} ({result['release_year']}): {result['summary']['total_wins']} wins")

# Print all awards by event
for category in result['categories']:
    print(f"\n{category['event_name']}: {category['total_awards']} nominations")
    for award in category['awards'][:3]:  # First 3
        print(f"  {award['year']} {award['status']}: {award['category']}")

Example 3: Filter by award status

result = await execute({"function": "get_awards", "imdb_id": "nm0000149"})

# Get only wins
wins = []
for category in result['categories']:
    for award in category['awards']:
        if award['status'] == 'Winner':
            wins.append({
                'event': category['event_name'],
                'year': award['year'],
                'category': award['category'],
                'work': award.get('title', 'N/A')
            })

print(f"Total wins: {len(wins)}")
for win in sorted(wins, key=lambda x: x['year'], reverse=True)[:5]:
    print(f"  {win['year']}: {win['event']} - {win['category']}")

Example 4: Count nominations by event

from collections import Counter

result = await execute({"function": "get_name_awards", "name_id": "nm0000149"})

event_counts = Counter()
for category in result['categories']:
    event_counts[category['event_name']] = category['total_awards']

print("Nominations by event:")
for event, count in event_counts.most_common(5):
    print(f"  {event}: {count}")

Technical Details

Anti-Bot Bypass

IMDb uses AWS WAF (Web Application Firewall) with JavaScript challenges. Direct HTTP requests return HTTP 202 with a JavaScript challenge page. This skill uses:

• Playwright: Headless browser automation
• Stealth Mode: Disables automation detection
• Realistic Headers: Mimics real browser behavior
• JavaScript Rendering: Executes JS to solve WAF challenges

Data Source

Data is extracted from the __NEXT_DATA__ script tag, which contains Next.js server-side props in JSON format. This is more reliable and structured than HTML scraping.

Rate Limiting

IMDb may rate-limit excessive requests. Recommendations:

• Add 2-3 second delays between requests
• Cache results (awards data changes infrequently)
• Limit concurrent requests
• Respect requests_per_minute: 20 guideline

Use Cases

1. Award History Research: Track an actor's or film's award history
2. Competitive Analysis: Compare award wins between films/actors
3. Content Enrichment: Add award data to movie databases
4. Statistical Analysis: Analyze award patterns and trends
5. Biographical Research: Build comprehensive actor profiles

Limitations

• Requires JavaScript execution (uses Playwright, not simple HTTP)
• Slower than pure HTTP APIs due to browser overhead
• May encounter rate limits with excessive requests
• Award data is limited to what IMDb displays on awards pages
• Some older or obscure awards may not be fully detailed

Testing

# Test the executor
import asyncio
from executor import execute

async def test():
    # Test name awards
    result1 = await execute({"function": "get_name_awards", "name_id": "nm0000149"})
    assert result1['success']
    assert result1['entity_type'] == 'name'
    assert len(result1['categories']) > 0
    print(f"✓ Name awards: {result1['entity_name']}")
    
    # Test title awards
    result2 = await execute({"function": "get_title_awards", "title_id": "tt0944835"})
    assert result2['success']
    assert result2['entity_type'] == 'title'
    print(f"✓ Title awards: {result2['entity_title']}")
    
    # Test auto-detect
    result3 = await execute({"function": "get_awards", "imdb_id": "nm0000149"})
    assert result3['success']
    print("✓ Auto-detect works")
    
    print("\nAll tests passed!")

asyncio.run(test())

Changelog

v1.0.0 (Initial Release)

• First release with name and title award extraction
• AWS WAF bypass using Playwright
• Structured JSON output with categories and awards
• Error handling and validation