refactor(cli)!: rename all skills and agents to consistent ce- prefix (#503)

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

plugins/compound-engineering/skills/ce-dspy-ruby/assets/signature-template.rb

@@ -0,0 +1,221 @@
+# frozen_string_literal: true
+
+# =============================================================================
+# DSPy.rb Signature Template — v0.34.3 API
+#
+# Signatures define the interface between your application and LLMs.
+# They specify inputs, outputs, and task descriptions using Sorbet types.
+#
+# Key patterns:
+#   - Use T::Enum classes for controlled outputs (not inline T.enum([...]))
+#   - Use description: kwarg on fields to guide the LLM
+#   - Use default values for optional fields
+#   - Use Date/DateTime/Time for temporal data (auto-converted)
+#   - Access results with result.field (not result[:field])
+#   - Invoke with predictor.call() (not predictor.forward())
+# =============================================================================
+
+# --- Basic Signature ---
+
+class SentimentAnalysis < DSPy::Signature
+  description "Analyze sentiment of text"
+
+  class Sentiment < T::Enum
+    enums do
+      Positive = new('positive')
+      Negative = new('negative')
+      Neutral = new('neutral')
+    end
+  end
+
+  input do
+    const :text, String
+  end
+
+  output do
+    const :sentiment, Sentiment
+    const :score, Float, description: "Confidence score from 0.0 to 1.0"
+  end
+end
+
+# Usage:
+#   predictor = DSPy::Predict.new(SentimentAnalysis)
+#   result = predictor.call(text: "This product is amazing!")
+#   result.sentiment  # => Sentiment::Positive
+#   result.score      # => 0.92
+
+# --- Signature with Date/Time Types ---
+
+class EventScheduler < DSPy::Signature
+  description "Schedule events based on requirements"
+
+  input do
+    const :event_name, String
+    const :start_date, Date                     # ISO 8601: YYYY-MM-DD
+    const :end_date, T.nilable(Date)            # Optional date
+    const :preferred_time, DateTime             # ISO 8601 with timezone
+    const :deadline, Time                       # Stored as UTC
+  end
+
+  output do
+    const :scheduled_date, Date                 # LLM returns ISO string, auto-converted
+    const :event_datetime, DateTime             # Preserves timezone
+    const :created_at, Time                     # Converted to UTC
+  end
+end
+
+# Date/Time format handling:
+#   Date     → ISO 8601 (YYYY-MM-DD)
+#   DateTime → ISO 8601 with timezone (YYYY-MM-DDTHH:MM:SS+00:00)
+#   Time     → ISO 8601, automatically converted to UTC
+
+# --- Signature with Default Values ---
+
+class SmartSearch < DSPy::Signature
+  description "Search with intelligent defaults"
+
+  input do
+    const :query, String
+    const :max_results, Integer, default: 10
+    const :language, String, default: "English"
+    const :include_metadata, T::Boolean, default: false
+  end
+
+  output do
+    const :results, T::Array[String]
+    const :total_found, Integer
+    const :search_time_ms, Float, default: 0.0       # Fallback if LLM omits
+    const :cached, T::Boolean, default: false
+  end
+end
+
+# Input defaults reduce boilerplate:
+#   search = DSPy::Predict.new(SmartSearch)
+#   result = search.call(query: "Ruby programming")
+#   # max_results=10, language="English", include_metadata=false are applied
+
+# --- Signature with Nested Structs and Field Descriptions ---
+
+class EntityExtraction < DSPy::Signature
+  description "Extract named entities from text"
+
+  class EntityType < T::Enum
+    enums do
+      Person = new('person')
+      Organization = new('organization')
+      Location = new('location')
+      DateEntity = new('date')
+    end
+  end
+
+  class Entity < T::Struct
+    const :name, String, description: "The entity text as it appears in the source"
+    const :type, EntityType
+    const :confidence, Float, description: "Extraction confidence from 0.0 to 1.0"
+    const :start_offset, Integer, default: 0
+  end
+
+  input do
+    const :text, String
+    const :entity_types, T::Array[EntityType], default: [],
+          description: "Filter to these entity types; empty means all types"
+  end
+
+  output do
+    const :entities, T::Array[Entity]
+    const :total_found, Integer
+  end
+end
+
+# --- Signature with Union Types ---
+
+class FlexibleClassification < DSPy::Signature
+  description "Classify input with flexible result type"
+
+  class Category < T::Enum
+    enums do
+      Technical = new('technical')
+      Business = new('business')
+      Personal = new('personal')
+    end
+  end
+
+  input do
+    const :text, String
+  end
+
+  output do
+    const :category, Category
+    const :result, T.any(Float, String),
+          description: "Numeric score or text explanation depending on classification"
+    const :confidence, Float
+  end
+end
+
+# --- Signature with Recursive Types ---
+
+class DocumentParser < DSPy::Signature
+  description "Parse document into tree structure"
+
+  class NodeType < T::Enum
+    enums do
+      Heading = new('heading')
+      Paragraph = new('paragraph')
+      List = new('list')
+      CodeBlock = new('code_block')
+    end
+  end
+
+  class TreeNode < T::Struct
+    const :node_type, NodeType, description: "The type of document element"
+    const :text, String, default: "", description: "Text content of the node"
+    const :level, Integer, default: 0
+    const :children, T::Array[TreeNode], default: []  # Self-reference → $defs in JSON Schema
+  end
+
+  input do
+    const :html, String, description: "Raw HTML to parse"
+  end
+
+  output do
+    const :root, TreeNode
+    const :word_count, Integer
+  end
+end
+
+# The schema generator creates #/$defs/TreeNode references for recursive types,
+# compatible with OpenAI and Gemini structured outputs.
+# Use `default: []` instead of `T.nilable(T::Array[...])` for OpenAI compatibility.
+
+# --- Vision Signature ---
+
+class ImageAnalysis < DSPy::Signature
+  description "Analyze an image and answer questions about its content"
+
+  input do
+    const :image, DSPy::Image, description: "The image to analyze"
+    const :question, String, description: "Question about the image content"
+  end
+
+  output do
+    const :answer, String
+    const :confidence, Float, description: "Confidence in the answer (0.0-1.0)"
+  end
+end
+
+# Vision usage:
+#   predictor = DSPy::Predict.new(ImageAnalysis)
+#   result = predictor.call(
+#     image: DSPy::Image.from_file("path/to/image.jpg"),
+#     question: "What objects are visible?"
+#   )
+#   result.answer  # => "The image shows..."
+
+# --- Accessing Schemas Programmatically ---
+#
+#   SentimentAnalysis.input_json_schema   # => { type: "object", properties: { ... } }
+#   SentimentAnalysis.output_json_schema  # => { type: "object", properties: { ... } }
+#
+#   # Field descriptions propagate to JSON Schema
+#   Entity.field_descriptions[:name]       # => "The entity text as it appears in the source"
+#   Entity.field_descriptions[:confidence] # => "Extraction confidence from 0.0 to 1.0"