LLM Classifier Skill

SkillAI & models

LLM-based zero-shot and few-shot classification for flexible intent detection

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the LLM Classifier Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/llm-classifier/SKILL.md and read by ahel’s review.

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

Zero-Shot: No examples, description-based
Few-Shot: Example-based classification
Structured Output: JSON schema for labels
Chain-of-Thought: Reasoning before classification
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

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: llm-classifier
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter