TenerifeProp/.kilo/rules/agent-patterns.md

Agent Patterns Rules

Based on research from Anthropic, OpenAI, and Lilian Weng.

Core Patterns (Anthropic)

1. Prompt Chaining

Sequential steps with validation gates.

when: Task can be cleanly decomposed
example: Generate copy, then translate
gate: Validate each step before next

2. Routing

Classify input, route to specialized agent.

when: Distinct categories, clear classification
example: Customer service routing (refunds, technical, general)

3. Parallelization

Run independent tasks simultaneously.

when: Subtasks are independent
types:
  - Sectioning: Break into parallel parts
  - Voting: Multiple attempts, aggregate results

4. Orchestrator-Workers

Central controller delegates to workers.

when: Subtasks dynamic, not pre-defined
example: Coding agent editing multiple files

5. Evaluator-Optimizer

Loop: generate, evaluate, improve.

when: Clear criteria, iterative improves
example: Code review loop

Memory Architecture (Lilian Weng)

Components

• Planning: Task decomposition, self-reflection
• Memory: Short-term, long-term, episodic
• Tool Use: External APIs, code execution

Memory Types

1. Sensory: Embeddings (milliseconds)
2. Short-term: Context window (~4000 tokens)
3. Long-term: Vector store (infinite)
4. Episodic: Experience log

Tool Use Best Practices (Anthropic)

1. Give model "think" space before output
2. Keep formats close to internet patterns
3. Minimize formatting overhead
4. Invest in ACI like HCI

ReAct Pattern

Interleave reasoning and action:

Thought: [reasoning]
Action: [tool call]
Observation: [result]
(Repeat until done)

Reflexion Pattern

Learn from mistakes:

1. Take action
2. Check heuristic
3. Generate reflection
4. Update memory
5. Retry with lesson