harness工程 Prompt-first起始包 是 AI Skill Hub 本期精选Prompt模板之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。
harness工程 Prompt-first起始包 是经过精心设计和反复验证的专业 Prompt 模板集合。这些 Prompt 框架能够有效激活 Claude、ChatGPT 等大型语言模型的深层能力,让 AI 生成更准确、更有价值的输出结果。无需任何安装,直接复制模板内容到 AI 对话框即可使用。
harness工程 Prompt-first起始包 是经过精心设计和反复验证的专业 Prompt 模板集合。这些 Prompt 框架能够有效激活 Claude、ChatGPT 等大型语言模型的深层能力,让 AI 生成更准确、更有价值的输出结果。无需任何安装,直接复制模板内容到 AI 对话框即可使用。
# Prompt 无需安装,直接复制使用 # 支持:Claude / ChatGPT / Gemini / 通义千问 等主流模型 # 使用步骤 # 1. 复制 Prompt 模板内容 # 2. 粘贴到 AI 对话框 # 3. 替换 [占位符] 为实际内容 # 4. 发送后获取结构化输出 # 获取原始文件 git clone https://github.com/harnessworks/harness-starter-kit
# 粘贴到 Claude/ChatGPT 使用 # 示例 Prompt 结构: 你是一位 [角色],擅长 [领域]。 请根据以下要求完成任务: 任务背景:[描述背景] 具体要求:[详细说明] 输出格式:[期望格式] # 将 [] 内内容替换为实际需求
# harness-starter-kit 配置文件示例(config.yml) app: name: "harness-starter-kit" debug: false log_level: "INFO" # 运行时指定配置文件 harness-starter-kit --config config.yml # 或通过环境变量配置 export HARNESS_STARTER_KIT_API_KEY="your-key" export HARNESS_STARTER_KIT_OUTPUT_DIR="./output"
<img width="2172" height="724" alt="Harness Starter Kit logo banner" src="https://github.com/user-attachments/assets/c303dffe-402d-44f4-8d11-3c28936f3a3e" />
<img width="1536" height="1024" alt="Harness engineering workflow diagram" src="https://github.com/user-attachments/assets/13dbc277-ec47-4c0b-87ca-d31a88e83f4f" />
</p>
<p align="center"> <img alt="Generic profile" src="https://img.shields.io/badge/profile-generic-6b7280?style=flat-square" /> <img alt="Python" src="https://img.shields.io/badge/Python-3776AB?style=flat-square&logo=python&logoColor=white" /> <img alt="TypeScript" src="https://img.shields.io/badge/TypeScript-3178C6?style=flat-square&logo=typescript&logoColor=white" /> <img alt="Node.js" src="https://img.shields.io/badge/Node.js-5FA04E?style=flat-square&logo=nodedotjs&logoColor=white" /> <img alt="Next.js" src="https://img.shields.io/badge/Next.js-000000?style=flat-square&logo=nextdotjs&logoColor=white" /> <img alt="React" src="https://img.shields.io/badge/React-087EA4?style=flat-square&logo=react&logoColor=white" /> <img alt="Vue" src="https://img.shields.io/badge/Vue-4FC08D?style=flat-square&logo=vuedotjs&logoColor=white" /> <img alt="Django" src="https://img.shields.io/badge/Django-092E20?style=flat-square&logo=django&logoColor=white" /> <img alt="Flask" src="https://img.shields.io/badge/Flask-000000?style=flat-square&logo=flask&logoColor=white" /> <img alt="FastAPI" src="https://img.shields.io/badge/FastAPI-009688?style=flat-square&logo=fastapi&logoColor=white" /> <img alt="Spring Boot" src="https://img.shields.io/badge/Spring_Boot-6DB33F?style=flat-square&logo=springboot&logoColor=white" /> <img alt="Android" src="https://img.shields.io/badge/Android-3DDC84?style=flat-square&logo=android&logoColor=white" /> <img alt="Go" src="https://img.shields.io/badge/Go-00ADD8?style=flat-square&logo=go&logoColor=white" /> <img alt="Rust" src="https://img.shields.io/badge/Rust-000000?style=flat-square&logo=rust&logoColor=white" /> <img alt="Contributors" src="https://img.shields.io/github/contributors/harnessworks/harness-starter-kit?style=flat-square" /> </p>
English | 한국어 | 日本語 | 简体中文 | 繁體中文
<p align="center"> <a href="https://harnessworks.github.io/harness-starter-kit/"> <img alt="Launch site" src="https://img.shields.io/badge/Launch-Agent_Session_Demo-0077ff?style=for-the-badge" /> </a> <a href="https://dev.to/baskduf/i-stopped-prompt-engineering-my-ai-coding-agent-i-started-engineering-the-repo-instead-1i3e"> <img alt="Read the launch essay" src="https://img.shields.io/badge/Read-Launch_Essay-0A0A0A?style=for-the-badge&logo=devdotto&logoColor=white" /> </a> <a href="https://github.com/harnessworks/harness-agent-benchmark-runner"> <img alt="View benchmark runner" src="https://img.shields.io/badge/Benchmark-Harness_Runner-2F855A?style=for-the-badge&logo=github&logoColor=white" /> </a> </p>
Open the target repository with your coding agent and give it this prompt.
<details> <summary>Show full adoption prompt</summary>
Use this kit to apply harness engineering to this repository:
https://github.com/harnessworks/harness-starter-kit
Clone the kit into ./harness-starter-kit if it is not already present, read it,
then apply its prompt-first harness engineering workflow to this repository.
Requirements:
- Treat the current working directory as the target repository.
- Treat ./harness-starter-kit as read-only reference material after cloning.
- Inspect this repository before editing.
- Preserve existing architecture, tools, package manager, commands, docs, and
conventions.
- Do not blindly copy templates.
- Add only the minimum useful harness pieces.
- Prefer updating existing docs/configs over duplicating them.
- Do not overwrite or delete existing files without explaining why.
- If I ask for /harness doctor, use
./harness-starter-kit/commands/harness-doctor.md.
- If I ask for /harness update after adoption, use
./harness-starter-kit/commands/harness-update.md to refresh the kit reference,
record .harness/source.json, and selectively update target harness files
without blindly overwriting existing files.
- If I ask for /harness refresh after adoption, use
./harness-starter-kit/commands/harness-refresh.md to review existing harness
docs, rules, knowledge records, and checks for stale or duplicated guidance.
Do not delete, archive, move, or rename files without my explicit approval for
the specific files.
- If I ask for /harness review sub-agent, use
./harness-starter-kit/commands/harness-review.md and treat the request as
explicit permission to use a read-only reviewer subagent when available and
permitted by the active runtime and tool instructions. If unavailable,
blocked, not permitted, or failed, report the fallback reason.
- If I ask for /harness review, use
./harness-starter-kit/commands/harness-review.md to review the current change
set from an opposing harness-engineering perspective. Report findings,
missing checks, overreach, durable memory gaps, and follow-up recommendations
without modifying files unless I explicitly ask you to apply fixes after the
review.
Expected result:
- project-specific AGENTS.md or updated existing agent instructions
- knowledge store if no equivalent exists
- lightweight drift checks based on this repo's real rules
- local verification commands using existing tools
- adoption report with files changed, checks to run, assumptions, remaining
manual steps, failure memory, effectiveness measurement plan,
normal/focused/manual gate placement, and whether
./harness-starter-kit should be removed, ignored, or kept before commit
</details>
For the full prompt and workflow details, see docs/prompts/apply-to-target-repo.md and docs/adoption-workflow.md.
<p align="center"> <img width="360" alt="GitHub star support illustration for Harness Starter Kit" src="https://github.com/user-attachments/assets/a09c060c-3ac1-4ca4-bbce-8220478da130" /> </p>
<p align="center"> <em>💫 If this kit helps you, a GitHub star would be appreciated. 💫</em> </p>
<details> <summary>Show adoption details</summary>
This is not primarily an automatic installer. The agent should inspect the target repository first, then adapt the smallest useful set of harness artifacts: instructions, enforceable constraints, feedback loops, durable memory, drift checks, and an adoption report. Follow docs/adoption-workflow.md and the prompt in docs/prompts/apply-to-target-repo.md.
Use the optional installer only when you want a skeleton before agent-driven adaptation. It copies profile snippets into docs/harness/profiles/<profile> for review; prompt-first adoption reads profiles from the cloned kit at harness-starter-kit/templates/profiles/<profile>.
python harness-starter-kit/scripts/apply_harness.py --target . --profile generic --dry-run
Profiles shown in the badges above are conservative reference snippets, not automatic migrations. See docs/profiles.md and docs/checklists/profile-absorption.md.
For the detailed documentation index, see docs/component-map.md. Common adoption references: docs/checklists/external-api-work.md, docs/checklists/decision-failure-memory.md, and docs/checklists/verification-scripts.md.
Validation coverage and local checks live in docs/validation.md. Lifecycle pilot details live in docs/examples/lifecycle-pilot-results.md. They do not prove that harness adoption reduces repeated agent mistakes. Use docs/evaluation.md, docs/templates/effectiveness-report.md, and docs/templates/task-outcome.yaml to measure comparable tasks, wrong-file edits, first-pass verification, and human rework.
Dogfood reports include TodayBus for a Next.js public-data target and Harness ERP for a Spring/Maven backend and vanilla frontend target. Both are harnessed-only benchmarks, not proof of effectiveness improvement.
</details>
该项目提供了一个开源Prompt模板,用于提高仓库安全性,适用于A的开发者,但需要进一步完善和测试
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。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
经综合评估,harness工程 Prompt-first起始包 在Prompt模板赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | harness-starter-kit |
| 原始描述 | 开源Prompt模板:harness engineering Prompt-first starter kit for making repositories safer for A。⭐71 · Python |
| Topics | promptai-agentscoding-agentsdeveloper-toolsdocumentationharness-engineeringpython |
| GitHub | https://github.com/harnessworks/harness-starter-kit |
| License | MIT |
| 语言 | Python |
收录时间:2026-06-11 · 更新时间:2026-06-11 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端