AI Skill Hub 推荐使用:智能代理框架 是一款优质的Agent工作流。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
智能代理框架 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
智能代理框架 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install sdd-riper
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install sdd-riper
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/huisezhiyin/sdd-riper
cd sdd-riper
pip install -e .
# 验证安装
python -c "import sdd_riper; print('安装成功')"
# 命令行使用
sdd-riper --help
# 基本用法
sdd-riper input_file -o output_file
# Python 代码中调用
import sdd_riper
# 示例
result = sdd_riper.process("input")
print(result)
# sdd-riper 配置文件示例(config.yml) app: name: "sdd-riper" debug: false log_level: "INFO" # 运行时指定配置文件 sdd-riper --config config.yml # 或通过环境变量配置 export SDD_RIPER_API_KEY="your-key" export SDD_RIPER_OUTPUT_DIR="./output"
Let the model move the work forward. Let the human own goals, boundaries, permissions, checkpoints, evidence, and acceptance.
SDD-RIPER is an AI coding harness for working with strong coding agents. It is not a magic prompt and it is not heavyweight spec-driven development. It is a small set of controls that make model-driven work observable, recoverable, reviewable, and safe to resume.
The default entry is sdd-riper-one-light. Use the heavier sdd-riper-one when the task needs stricter gates.
For Codex, Claude Code, and other agentic coding environments, the smallest useful repo layout is:
<repo>/
AGENTS.md
skills/
codemap/
new-chat-ready/
sdd-riper-one-light/
sdd-riper-one/
Recommended defaults:
AGENTS.md.AGENTS.md; use examples/global-agents.md as the template.sdd-riper-one-light by default.codemap before planning changes in unfamiliar or large code.new-chat-ready before long pauses, context resets, or handoffs.sdd-riper-one for high-risk or audit-heavy work.Use this prompt for ordinary coding or documentation work:
Use sdd-riper-one-light for this task.
Do not change files yet.
First give me:
- your understanding of the task
- the core goal for this loop
- a minimal spec / summary
- Done Contract: what counts as done, and what proves it
- next actions
- risks
- validation method
Wait for my approval before execution.
For unfamiliar code, first ask for a CodeMap:
Use codemap.
Create a feature-level or project-level code terrain index before planning changes.
Focus on entry points, call chains, risk points, validation entry points, and the smallest code slice to read next.
For a fresh-chat handoff:
Use new-chat-ready.
Create a resume pack and a paste-ready next-chat prompt.
Also scan for reusable project knowledge, but do not commit memory/spec/handoff files unless I explicitly approve.
read context -> restate goal and risk -> checkpoint -> execute -> validate -> reverse sync
The harness keeps a few hard rules:
高质量的AI工作流框架,值得关注
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AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
总体来看,智能代理框架 是一款质量良好的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | sdd-riper |
| 原始描述 | 开源AI工作流:Lightweight AI Agent Harness for agentic coding: let strong models explore while。⭐233 · Python |
| Topics | ai-agentagentic-codingpython |
| GitHub | https://github.com/huisezhiyin/sdd-riper |
| 语言 | Python |
收录时间:2026-05-26 · 更新时间:2026-05-26 · License:未公布 · AI Skill Hub 不对第三方内容的准确性作法律背书。
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