few-shot-example-gen ยท diff
git:20260507.44b06c0 to git:20260601.da7723a
65 added, 65 removed. Audit A to A.
- ---
- name: few-shot-example-gen
- description: Few-shot example generation and optimization for improved LLM performance
- allowed-tools:
- - Read
- - Write
- - Edit
- - Bash
- - Glob
- - Grep
- graph:
- domains: [domain:software-engineering]
- specializations: [specialization:ai-agents-conversational]
- skillAreas: [skill-area:prompt-engineering, skill-area:prompt-instruction-tuning-agents]
- roles: [role:ml-engineer, role:backend-engineer]
- workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
-
- ---
-
- # Few-Shot Example Generation Skill
-
- ## Capabilities
-
- - Generate diverse few-shot examples
- - Implement example selection strategies
- - Optimize example ordering for performance
- - Create dynamic example retrieval
- - Design example formats for specific tasks
- - Implement example quality validation
-
- ## Target Processes
-
- - prompt-engineering-workflow
- - intent-classification-system
-
- ## Implementation Details
-
- ### Example Selection Strategies
-
- 1. **Semantic Similarity**: Select similar examples
- 2. **MMR Selection**: Diverse example selection
- 3. **N-Gram Overlap**: Lexical similarity
- 4. **Random Sampling**: Baseline selection
- 5. **Length-Based**: Control example sizes
-
- ### Configuration Options
-
- - Number of examples
- - Selection algorithm
- - Example format (input/output structure)
- - Max token limits
- - Example store backend
-
- ### Best Practices
-
- - Cover edge cases in examples
- - Balance example diversity
- - Optimize example ordering
- - Test with varied inputs
- - Monitor token usage
-
- ### Dependencies
-
- - langchain
- - sentence-transformers (for semantic selection)
+ ---
+ name: few-shot-example-gen
+ description: Few-shot example generation and optimization for improved LLM performance
+ allowed-tools:
+ - Read
+ - Write
+ - Edit
+ - Bash
+ - Glob
+ - Grep
+ graph:
+ domains: [domain:software-engineering]
+ specializations: [specialization:ai-agents-conversational]
+ skillAreas: [skill-area:prompt-engineering, skill-area:prompt-instruction-tuning-agents]
+ roles: [role:ml-engineer, role:backend-engineer]
+ workflows: [workflow:ml-model-lifecycle, workflow:feature-development]
+
+ ---
+
+ # Few-Shot Example Generation Skill
+
+ ## Capabilities
+
+ - Generate diverse few-shot examples
+ - Implement example selection strategies
+ - Optimize example ordering for performance
+ - Create dynamic example retrieval
+ - Design example formats for specific tasks
+ - Implement example quality validation
+
+ ## Target Processes
+
+ - prompt-engineering-workflow
+ - intent-classification-system
+
+ ## Implementation Details
+
+ ### Example Selection Strategies
+
+ 1. **Semantic Similarity**: Select similar examples
+ 2. **MMR Selection**: Diverse example selection
+ 3. **N-Gram Overlap**: Lexical similarity
+ 4. **Random Sampling**: Baseline selection
+ 5. **Length-Based**: Control example sizes
+
+ ### Configuration Options
+
+ - Number of examples
+ - Selection algorithm
+ - Example format (input/output structure)
+ - Max token limits
+ - Example store backend
+
+ ### Best Practices
+
+ - Cover edge cases in examples
+ - Balance example diversity
+ - Optimize example ordering
+ - Test with varied inputs
+ - Monitor token usage
+
+ ### Dependencies
+
+ - langchain
+ - sentence-transformers (for semantic selection)