Agentic Patterns Skill

Triggers

• agentic
• reflection
• react pattern
• planning
• memory
• tool use

Purpose

To build sophisticated AI agents that can think, plan, and correct themselves using 2025-era cognitive architectures.

Supported Patterns

1. Reflection / Self-Correction

The Problem: Models make mistakes. The Solution: Ask the model to review its own output before finalizing it.

• Flow: Generate -> Critique -> Refine.
• Usage: Critical code generation, complex math, reasoning tasks.

2. ReAct (Reason + Act)

The Problem: Models need external information. The Solution: Interleave reasoning traces with tool execution.

• Flow: Thought -> Action -> Observation -> Thought...
• Usage: Web browsing, database querying, API interaction.

3. Planning (Chain of Thought)

The Problem: Complex tasks need decomposition. The Solution: Break goal into a sequence of steps.

• Flow: Goal -> Plan -> Execute Step 1 -> Update Plan.
• Usage: Multi-step workflows, project implementation.

4. Memory Augmented

The Problem: Context window limits. The Solution: External storage (Vector DB, Knowledge Graph).

• Types:
• Episodic: Past interactions ("What did we do yesterday?").
• Semantic: Facts and knowledge ("How does this repo work?").
• Procedural: How to do things (stored skills/tools).

5. Tool Use / Function Calling

The Problem: Models can't "do" things. The Solution: Structured output mapped to executable functions.

• Best Practice: Define strict JSON schemas for tools constraints.

Instructions

1. Identify Need: "The user wants a research report."
2. Select Pattern: "This requires Planning (to outline the report) and ReAct (to search the web)."
3. Implement:

• Define the loop (e.g., while not done:).
• Define the prompt structure (e.g., "You are a researcher...").
• Implement the tool execution layer.