360 Secure SkillHub
360 安全技能中心

LLMBooster

LLMBooster 通过 Plan → Draft → Self-Critique → Refine 四步流程强制结构化推理,改善低端模型跳步、漏细节、缺少自查的问题;提供 1-4 级思考深度、步骤进度可视化与使用统计,并通过 /booster 命令启用、停用或查询状态。框架由宿主 LLM 自行执行,无需额外 LLM 端点。

danlct27
danlct27
热度 58.88
最近更新 2026-05-11 17:34:55
分类:效率依赖:读写文件 / 代码执行 / 内部调用大模型应用场景:工作流 / 报告撰写 / 校对润色 / 摘要总结 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add llmbooster
Metadata
name
llmbooster
description
A 4-step thinking framework to boost LLM output quality. Enforces structured reasoning (Plan → Draft → Self-Critique → Refine) to improve low-end LLM responses. No LLM endpoint needed - LLM follows the framework itself. Triggered by "detailed analysis", "in-depth analysis", "use booster", or /booster command.
metadata
{"openclaw":{"emoji":"🚀","requires":{"bins":[]}}}

LLMBooster Skill

A Thinking Framework, Not an Automation Tool

LLMBooster is a 4-step thinking framework that improves LLM output quality through structured reasoning. No LLM endpoint needed - the LLM follows the framework itself.

Core Philosophy

Problem with low-end LLMs: Jump to conclusions, miss details, lack self-review.

Booster solution: Enforce structured thinking process.

Plan → Draft → Self-Critique → Refine

Trigger Conditions

  • User says "use booster", "booster", or "/booster"
  • User requests: "detailed analysis", "in-depth analysis", "help me analyze"
  • User requests: "improve quality", "detailed analysis"
  • User asks for evaluation, comparison, or decision support
  • User requests code review or technical documentation
  • User asks complex questions (lengthy tasks, multi-step problems)

How It Works

LLM executes the framework itself, no Python calls needed:

  1. LLM reads prompts/plan.md → Create structured plan
  2. LLM reads prompts/draft.md → Write complete draft
  3. LLM reads prompts/self_critique.md → Review issues
  4. LLM reads prompts/refine.md → Polish final output

Command Handling

When user enters /booster command, execute:

cd ~/.openclaw/workspace/skills/llmbooster && python3 -c "
from config_loader import ConfigLoader
from state_manager import SkillStateManager
from cli_handler import CLICommandHandler

loader = ConfigLoader()
config = loader.load('config.schema.json')
state_mgr = SkillStateManager(config)
cli = CLICommandHandler(state_mgr)
result = cli.handle('/booster status')
print(result.message)
"

CLI Commands

Command Description
/booster enable Enable LLMBooster
/booster disable Disable LLMBooster
/booster status Show current status
/booster stats Show usage statistics
/booster depth <1-4> Set thinking depth
/booster help Show help

Thinking Depth

Depth Steps Quality Speed Use Case
1 Plan ★★☆☆ Fastest Quick analysis, brainstorm
2 Plan → Draft ★★★☆ Fast General tasks, simple Q&A
3 + Self-Critique ★★★★ Medium Code review, technical docs
4 Full pipeline ★★★★★ Slowest Important docs, complex analysis

Visual Feedback

When executing, Booster displays:

🚀 **Booster Pipeline Started**: Analyzing task...
────────────────────────────────────────
🚀 Booster [█░░░░] Step 1/4: **Plan**
✅ Plan completed (2.3s)

🚀 Booster [██░░░] Step 2/4: **Draft**
✅ Draft completed (5.1s)

🚀 Booster [███░░] Step 3/4: **Self-Critique**
✅ Self-Critique completed (1.8s)

🚀 Booster [████] Step 4/4: **Refine**
✅ Refine completed (3.2s)
────────────────────────────────────────
✅ **Booster Complete** - 4 steps, 12.4s total

Prompt Templates

All templates are in prompts/ directory:

  • plan.md - Step 1: Create structured plan
  • draft.md - Step 2: Write complete draft
  • self_critique.md - Step 3: Review and list improvements
  • refine.md - Step 4: Apply improvements

Why It Works

Low-End LLM Problem Booster Solution
Jumps to conclusions Plan step forces structured thinking
Misses details Draft step requires complete coverage
No self-review Self-Critique step finds issues
Rough output Refine step polishes final result

Usage Statistics

/booster stats
# 📊 **Booster Statistics**
# ───────────────────────
# Status: enabled
# Thinking Depth: 4
# Tasks Processed: 5
# Last Used: 2026-03-22T09:30:00

Files

File Purpose
SKILL.md Skill definition + trigger conditions
README.md Documentation
booster.py Core module + helpers
cli_handler.py CLI command processing
state_manager.py State + statistics
stream_handler.py Visual feedback
config_loader.py Config loading
prompts/*.md Step prompt templates