Begin the reading goal interview.

Returns the interview prompt to guide the conversation. Use this when the user says "interview me" or "set up my profile".

Save the user's reading profile after the interview.

Args: name: User's name

domains: List of reading domains with goals. Each domain should have:
    - id: Short identifier (e.g., "classic_lit", "neuroscience")
    - name: Display name (e.g., "Classic Literature")
    - purpose: Why they want to read in this area
    - target_books: Number of books they aim to read

preferences: Reading preferences dictionary:
    - pacing: "slow_deep" | "steady" | "fast_volume"
    - challenge_tolerance: "low" | "medium" | "high"
    - parallel_books: Number of books they read at once

context: Current context dictionary:
    - mood: Current reading mood
    - avoidances: List of things to avoid

Returns: Confirmation with status and message

Retrieve the current user profile.

Analyze the profile to extract latent features.

Returns the context builder prompt along with the current profile. After analysis, call update_latent_features with the results.

Update the profile with extracted latent features.

Args: features: Dictionary of latent features extracted from analysis.

Build a curated reading stack for a specific domain.

Args: domain: The domain ID to build a stack for (e.g., "classic_lit").

Returns the syllabus builder prompt with user context. After generating recommendations, call save_bookstack to persist them.

Save a curated book stack for a domain.

Args: domain: The domain ID this stack belongs to books: List of book recommendations description: Optional description of what this stack will achieve

Get all book stacks, or a specific domain's stack.

Get the next recommended book to read.

Manually add a book to an existing stack.

Log a completed book (quick mode).

Args: title: Book title author: Author name domain: Which domain this book belongs to rating: Optional 1-5 rating quick_note: Optional brief note

Start a deep reflection session for a book.

Save a deep reflection for a book.

Args: title: Book title key_takeaway: One sentence distillation craft_lessons: What you learned about writing/craft personal_insights: How this connects to your life favorite_quotes: Memorable passages next_appetite: "more_like_this" | "ready_for_challenge" | "palette_cleanser"

Get reading log entries.

Get reading progress summary across all domains.

Analyze your reading history to identify patterns.

Examines your completed books to find:

• Themes you gravitate toward

• Difficulty levels that work best

• Reading pace insights

• Author preferences

Results are saved and used for smarter recommendations.

Get or create a profile for an author.

Args: author: Author name (e.g., "Leo Tolstoy")

Returns author data including books read, ratings, and notes.

Update notes about an author's style and your impressions.

Args: author: Author name style_notes: Dictionary with keys like: - prose: Description of writing style - themes: List of common themes - strengths: What they do well - comparable_to: Similar authors your_notes: Your personal notes about this author

Get your favorite authors ranked by affinity.

Args: limit: Maximum number of authors to return (default 10)

Add a connection between two books for future recommendations.

Args: from_book: Title of the first book to_book: Title of the second book relationship: Type of connection: - "similar_theme": Similar themes or topics - "complements": Different angles on same topic - "next_step": Natural progression from first to second - "contrast": Interesting contrast/counterpoint reason: Why these books are connected strength: "strong" | "moderate" | "weak"

Find books connected to one you've read.

Args: title: Title of a book you've read

Returns books that are connected to this one.