llm-classifier ยท diff
git:20260325.a6b3a88 to git:20260507.313363d
61 added, 58 removed. Audit A to A.
- ---
- name: llm-classifier
- description: LLM-based zero-shot and few-shot classification for flexible intent detection
- allowed-tools:
- - Read
- - Write
- - Edit
- - Bash
- - Glob
- - Grep
- ---
-
- # LLM Classifier Skill
-
- ## Capabilities
-
- - Implement zero-shot classification with LLMs
- - Design few-shot classification prompts
- - Configure structured output for labels
- - Implement confidence scoring
- - Design classification taxonomies
- - Handle multi-label classification
-
- ## Target Processes
-
- - intent-classification-system
- - dialogue-flow-design
-
- ## Implementation Details
-
- ### Classification Patterns
-
- 1. **Zero-Shot**: No examples, description-based
- 2. **Few-Shot**: Example-based classification
- 3. **Structured Output**: JSON schema for labels
- 4. **Chain-of-Thought**: Reasoning before classification
- 5. **Ensemble**: Multiple prompts/models
-
- ### Configuration Options
-
- - LLM model selection
- - Label descriptions
- - Example selection strategy
- - Output format specification
- - Confidence calibration
-
- ### Best Practices
-
- - Clear label descriptions
- - Representative examples
- - Consistent output format
- - Calibrate confidence scores
- - Test with edge cases
-
- ### Dependencies
-
- - langchain-core
- - LLM provider
+ ---
+ name: llm-classifier
+ description: LLM-based zero-shot and few-shot classification for flexible intent detection
+ allowed-tools:
+ - Read
+ - Write
+ - Edit
+ - Bash
+ - Glob
+ - Grep
+ graph:
+ domains: [domain:software-engineering]
+
+ ---
+
+ # LLM Classifier Skill
+
+ ## Capabilities
+
+ - Implement zero-shot classification with LLMs
+ - Design few-shot classification prompts
+ - Configure structured output for labels
+ - Implement confidence scoring
+ - Design classification taxonomies
+ - Handle multi-label classification
+
+ ## Target Processes
+
+ - intent-classification-system
+ - dialogue-flow-design
+
+ ## Implementation Details
+
+ ### Classification Patterns
+
+ 1. **Zero-Shot**: No examples, description-based
+ 2. **Few-Shot**: Example-based classification
+ 3. **Structured Output**: JSON schema for labels
+ 4. **Chain-of-Thought**: Reasoning before classification
+ 5. **Ensemble**: Multiple prompts/models
+
+ ### Configuration Options
+
+ - LLM model selection
+ - Label descriptions
+ - Example selection strategy
+ - Output format specification
+ - Confidence calibration
+
+ ### Best Practices
+
+ - Clear label descriptions
+ - Representative examples
+ - Consistent output format
+ - Calibrate confidence scores
+ - Test with edge cases
+
+ ### Dependencies
+
+ - langchain-core
+ - LLM provider