Update to Achriom

{
  "name": "recommendations",
  "description": "Cross-media recommendation methodology. Use when suggesting what to read, watch, or listen to next. Considers mood, themes, and patterns across all media types. Triggers on \"what should I...\" or \"recommend\" questions.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 205
    }
  ],
  "skill_md_contents": "---\nname: \"recommendations\"\ndescription: \"Cross-media recommendation methodology. Use when suggesting what to read, watch, or listen to next. Considers mood, themes, and patterns across all media types. Triggers on \\\"what should I...\\\" or \\\"recommend\\\" questions.\"\n---\n\n# Recommendations\n\n## When to Activate\n\n- User asks what to read/watch/listen to next\n- Looking for something similar to an item they loved\n- Seeking a specific mood or vibe\n- Want to explore a theme across media types\n- \"I'm in the mood for...\"\n\n## Recommendation Philosophy\n\n**Mine their collection first.** They already own things they haven't explored. Surface those before suggesting new acquisitions.\n\n**Cross-media connections.** If they loved a book's themes, find the film or album that shares that spirit.\n\n**Respect their taste.** Their ratings and notes tell you what resonates. Use that signal.\n\n## Recommendation Process\n\n### 1. Understand the Request\nWhat are they really asking for? Mood? Theme? Similar to something specific?\n\n### 2. Check Their Collection\n```\nget_stats()  # Overall shape\nget_by_rating(media_type, min_rating=4)  # What they love\nsearch(media_type, query=\"relevant theme\")\nget_timeline(media_type)  # Recent engagement\n```\n\n### 3. Find Unread/Unwatched Gems\nSearch for items with matching themes that are still `unread`, `unwatched`, or `unheard`:\n```\nsearch(media_type=\"book\", query=\"theme\", filter=\"unread\")\n```\n\n### 4. Cross-Media Bridge\nIf they loved a book, search films:\n```\nsearch(media_type=\"movie\", query=\"theme from book\")\n```\nMake explicit connections: \"The melancholy in [book] shows up visually in [film]...\"\n\n### 5. Research New Suggestions\nIf nothing in collection fits, research:\n```\ntavily-search(query=\"books similar to [title] theme\")\n```\n\n## Recommendation Patterns\n\n**The unread shelf:** \"You have [book] sitting unread - given how much you loved [similar book], this might be the moment.\"\n\n**The mood match:** \"You rated [dark album] highly. [Other album] has that same weight.\"\n\n**The thematic thread:** \"This theme of isolation runs through your highest-rated items. Here's where else it appears...\"\n\n**The cross-pollination:** \"The director of [film] was influenced by [author] - you have both in your library.\"\n\n## Always Include\n\n- **Why** this recommendation fits (don't just list titles)\n- **Something to sample** - a track preview, a YouTube clip, a book passage\n- **The connection** to what they already love\n"
}