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dilolabsdilolabs/nosia/.claude/skills/caching-patterns/SKILL.md

caching-patterns

Skill211 starsChanged 5 months agoMITView on GitHub

Implements HTTP caching with ETags, fragment caching, Russian doll caching, and Solid Cache configuration. Use when optimizing performance, adding caching layers, or when user mentions ETags, fresh_when, stale?, cache keys, or Russian doll caching. WHEN NOT: For Turbo Stream real-time updates (use turbo-patterns), for background job cache warming logic (use job-patterns).

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We split this skill into the rules it gives an agent

7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use counter caches to avoid N+1 in cache keys:

    line 132
  2. Very specific:

    Use fresh_when for index and show actions

    line 275
  3. Very specific:

    Use touch: true on associations for automatic invalidation

    line 276
  4. Distinctive:

    Use Solid Cache in production (database-backed, no Redis)

    line 277
  5. Distinctive:

    Use counter caches for counts

    line 280
  6. Distinctive:

    Use Redis for caching (use Solid Cache)

    line 289
  7. Distinctive:

    Use generic cache keys without version/timestamp

    line 293

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Caching Patterns

Philosophy: Cache Aggressively, Invalidate Precisely

  • HTTP caching with ETags and fresh_when for free 304 Not Modified responses
  • Russian doll caching with touch: true for automatic cache invalidation
  • Fragment caching in views with cache keys based on updated_at timestamps
  • Solid Cache (database-backed, no Redis) for production caching
  • Collection caching with cache_collection for lists
  • Low-level caching with Rails.cache.fetch for expensive computations

Project Knowledge

Stack: Solid Cache (database-backed), Turbo for page refreshes, ETags with conditional GET, fragment caching in ERB views, collection caching for lists.

Multi-tenancy: Cache keys scoped to account. URL-based: app.myapp.com/123/projects/456.

Commands:

rails solid_cache:install        # Install Solid Cache
rails db:migrate                 # Run cache migrations
rails cache:clear                # Clear cache

Caching Strategy Hierarchy

Apply caching in this order (highest impact first):

  1. HTTP caching -- fresh_when / stale? in controllers (free 304s)
  2. Fragment caching -- cache blocks in views (Russian doll)
  3. Collection caching -- cache_collection for lists of partials
  4. Low-level caching -- Rails.cache.fetch for expensive computations

Pattern 1: HTTP Caching with ETags

See @references/http-caching.md for full details.

# Single resource -- returns 304 if ETag matches
class BoardsController < ApplicationController
  def show
    @board = Current.account.boards.find(params[:id])
    fresh_when @board
  end

  def index
    @boards = Current.account.boards.includes(:creator)
    fresh_when @boards
  end
end

# Composite ETag from multiple objects
def show
  fresh_when [@board, @card, Current.user]
end

# API with stale? for conditional rendering
def show
  @board = Current.account.boards.find(params[:id])
  if stale?(@board)
    render json: @board
  end
end

# Custom ETag with parameters
fresh_when etag: [@activities, @report_date, Current.user.timezone]

Pattern 2: Russian Doll Caching

See @references/fragment-caching.md for full details.

Set up touch cascades in models:

class Card < ApplicationRecord
  belongs_to :board, touch: true
end

class Comment < ApplicationRecord
  belongs_to :card, touch: true
  # Updating comment touches card -> touches board -> invalidates all caches
end

Nest cache blocks in views:

<% cache @board do %>
  <h1><%= @board.name %></h1>
  <% @board.columns.each do |column| %>
    <% cache column do %>
      <% column.cards.each do |card| %>
        <% cache card do %>
          <%= render card %>
        <% end %>
      <% end %>
    <% end %>
  <% end %>
<% end %>

Pattern 3: Collection Caching

<%# Cache each item individually with multi-fetch optimization %>
<% cache_collection @boards, partial: "boards/board" %>

<%# Manual alternative %>
<% @boards.each do |board| %>
  <% cache board do %>
    <%= render "boards/board", board: board %>
  <% end %>
<% end %>

Use counter caches to avoid N+1 in cache keys:

class Card < ApplicationRecord
  belongs_to :board, counter_cache: true, touch: true
end

class Board < ApplicationRecord
  def cache_key_with_version
    "#{cache_key}/cards-#{cards_count}-#{updated_at.to_i}"
  end
end

Pattern 4: Fragment Caching with Custom Keys

<%# Multiple dependencies %>
<% cache ["board_header", @board, Current.user] do %>
  <h1><%= @board.name %></h1>
  <% if Current.user.can_edit?(@board) %>
    <%= link_to "Edit", edit_board_path(@board) %>
  <% end %>
<% end %>

<%# With expiration %>
<% cache ["board_stats", @board], expires_in: 15.minutes do %>
  <div class="stats"><%= @board.cards.count %> cards</div>
<% end %>

<%# Conditional caching %>
<% cache_if @enable_caching, board do %>
  <%= board.name %>
<% end %>

<%# Multi-key with locale %>
<% cache ["dashboard", Current.account, Current.user,
          @boards.maximum(:updated_at), I18n.locale] do %>
  <%= render "boards_summary", boards: @boards %>
<% end %>

Pattern 5: Low-Level Caching

class Board < ApplicationRecord
  def statistics
    Rails.cache.fetch([self, "statistics"], expires_in: 1.hour) do
      {
        total_cards: cards.count,
        completed_cards: cards.joins(:closure).count,
        total_comments: cards.joins(:comments).count
      }
    end
  end

  # Race condition protection for expensive operations
  def expensive_calculation
    Rails.cache.fetch(
      [self, "expensive_calculation"],
      expires_in: 1.hour,
      race_condition_ttl: 10.seconds
    ) { calculate_complex_metrics }
  end

  # Version-based cache busting
  STATS_VERSION = 2
  def versioned_statistics
    Rails.cache.fetch([self, "statistics", "v#{STATS_VERSION}"],
                      expires_in: 1.hour) { calculate_statistics }
  end
end

Pattern 6: Cache Invalidation

See @references/cache-invalidation.md for full details.

# Prefer touch: true cascades (automatic)
belongs_to :board, touch: true

# Manual invalidation for low-level caches
class Card < ApplicationRecord
  after_create_commit :clear_board_caches
  after_destroy_commit :clear_board_caches

  private

  def clear_board_caches
    Rails.cache.delete([board, "statistics"])
    Rails.cache.delete([board, "card_distribution"])
  end
end

# Sweeper pattern for batch invalidation
class CacheSweeper
  def self.clear_board_caches(board)
    Rails.cache.delete([board, "statistics"])
    Rails.cache.delete([board, "card_distribution"])
    Rails.cache.delete([board, "activity_summary", Date.current])
  end
end

Pattern 7: Solid Cache Configuration

# config/environments/production.rb
config.cache_store = :solid_cache_store

# config/environments/development.rb
config.cache_store = :memory_store, { size: 64.megabytes }

# config/environments/test.rb
config.cache_store = :null_store

Pattern 8: Cache Warming

class CacheWarmerJob < ApplicationJob
  queue_as :low_priority

  def perform(account)
    account.boards.find_each do |board|
      board.statistics
      board.card_distribution
    end
  end
end

# config/recurring.yml
cache:
  daily_refresh:
    class: DailyCacheRefreshJob
    schedule: every day at 3am
    queue: low_priority

Boundaries

Always

  • Use fresh_when for index and show actions
  • Use touch: true on associations for automatic invalidation
  • Use Solid Cache in production (database-backed, no Redis)
  • Include expires_in for time-based data
  • Scope cache keys to account in multi-tenant apps
  • Use counter caches for counts
  • Eager load associations to prevent N+1 queries

Ask First

  • Whether to cache user-specific content
  • Cache expiration times (freshness vs performance)
  • Whether to warm caches in background jobs

Never

  • Use Redis for caching (use Solid Cache)
  • Cache without considering invalidation strategy
  • Forget touch: true with Russian doll caching
  • Cache CSRF tokens or sensitive user data
  • Use generic cache keys without version/timestamp
  • Cache in test environment (use :null_store)
  • Cache across account boundaries in multi-tenant apps

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