LoongFlow — PEES Iterative Problem Solving

Use this skill when the user wants to iteratively improve a solution — optimization, evolution, structured retries with learning, or any task that benefits from multiple rounds of refinement rather than a one-shot attempt.

Step 1: Analyze and Advise

Before starting, analyze the task and advise the user on which mode to use. Present both options clearly:

Native PEES (recommended for simple tasks):

• Best for: single-file fixes, small features, bug fixes, focused improvements
• How it works: You run Plan-Execute-Evaluate-Summary iterations yourself within this conversation
• Pros: Fast, no setup, no external dependencies, transparent workspace with full history
• Cons: Limited to ~5 iterations, single-threaded, no population-based evolution

LoongFlow Engine (recommended for complex tasks):

• Best for: optimization problems, multi-file projects, tasks needing many iterations (50+), population-based evolution with diversity preservation
• How it works: Downloads the LoongFlow framework, creates a general_agent task, runs evolutionary optimization in the background, monitors via cron
• Pros: Powerful evolutionary engine with multi-island model, Boltzmann selection, MAP-Elites diversity, checkpointing, cost tracking
• Cons: Requires ANTHROPIC_API_KEY and ANTHROPIC_BASE_URL, setup time, runs as background process
• Source: https://github.com/baidu-baige/LoongFlow

Ask the user which mode they prefer before proceeding.

Step 2: Follow the Mode Guide

Once the user chooses, read the corresponding reference file for detailed instructions:

• Native PEES → Read references/native-pees.md and follow it
• LoongFlow Engine → Read references/engine-mode.md and follow it

Architecture Reference

LoongFlow supports three tiers for agent projects:

Complexity Assessment

Task Analysis
├── Only needs conversation + simple tools? → SIMPLE
├── Needs file operations or code generation?
│   ├── Has numerical evaluation metric? → ADVANCED
│   └── No numerical metric? → STANDARD
└── Needs iterative optimization?
    ├── Has clear scoring function? → ADVANCED
    └── Qualitative improvement? → STANDARD