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opentanglopentangl 开发

Agent Skill

opentangl 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

17,082

周安装

691

GitHub Stars

2

下载量

5,362
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:opentangl(opentangl 开发)
来源仓库:https://github.com/8co/opentangl
安装命令:
openclaw skills install opentangl
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install opentangl

简介

全栈开发团队协作工具,由用户描述愿景自动生成完整代码实现。

  • 支持跨仓库构建、PR 提交与合并审查全流程自动化。
  • 适用于快速原型开发与 MVP 搭建场景。opentangl 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 生成代码需经人工审核后方可上线,防范潜在漏洞风险。
  • 安装命令:openclaw skills install opentangl

SKILL.md

name
opentangl
description
Not a code generator — an entire dev team. You write the vision, it ships the code. Autonomous builds, PRs, reviews, and merges across multiple repos. Point it at any JS/TS project and a product vision. It plans features, writes code, verifies builds, creates PRs, reviews diffs, and merges — autonomously. Manages multiple repos as one product. Use when you want to ship code without writing it. AI code generation, autonomous development, workflow automation, multi-repo orchestration, TypeScript, JavaScript, GitHub, OpenAI, Anthropic, Claude, GPT, LLM, devtools, CI/CD, pull requests, code review.
homepage
https://github.com/8co/opentangl
category
development
tags
["ai-agents", "code-generation", "autonomous-development", "multi-repo", "typescript", "javascript", "github", "pull-requests", "openai", "anthropic", "claude", "gpt", "llm", "devtools", "workflow-automation", "ci-cd", "code-review", "codegen"]
metadata
{"clawdbot":{"emoji":"🤖","requires":{"bins":["node","git","gh"]}}}

OpenTangl

Configure a self-driving development loop for any JavaScript/TypeScript project. This skill detects your project setup, generates configuration files, and prepares OpenTangl to run autonomously.

Follow these steps in order. Complete each step fully before moving to the next. Wait for user confirmation at every gate before proceeding. Do not skip steps or combine them — the user needs to complete actions on their end between steps.

Prerequisites

The user must have OpenTangl cloned and installed before using this skill. If they haven't, provide these commands for them to run:

git clone https://github.com/8co/opentangl.git
cd opentangl
npm install

Do not run these commands on the user's behalf. Wait for confirmation that OpenTangl is installed.

Once confirmed, verify the required tools are present. Run each check and report the results:

  • Node.js ≥ 18 — run node --version and show the output
  • git — run git --version and show the output
  • GitHub CLI — run gh auth status and show the output (needed for PR creation and merging)

Report all results to the user. If anything is missing, tell them exactly how to install it and stop until resolved.

Step 1 — Determine the Target Project

Ask the user:

Are you improving (a) an existing project, or (b) starting from scratch?

Path A: Existing Project

  1. Ask: "Where is your project?" Accept a path. If they say "this directory," use cwd.
  2. Tell the user you'll read config files in their project directory to detect the setup. Only inspect files in the directory the user provided — do not scan outside it. Check:

- Type: tsconfig.json → TypeScript, vite.config.ts → Vite, next.config.* → Next.js, serverless.yml → Serverless - Package manager: package-lock.json → npm, yarn.lock → yarn, pnpm-lock.yaml → pnpm - Build/test commands: Read package.json scripts for build, test, lint, typecheck - Source dirs: Default to src/ if it exists - Target branch: Check git symbolic-ref refs/remotes/origin/HEAD or look for main vs master

  1. Show everything you detected and confirm with the user before proceeding.
  2. Ask: "Are there other repos that are part of this same product?" If yes, repeat detection for each.

Path B: New Project

Tell the user to scaffold and initialize their project before continuing. Suggest the appropriate tool based on what they want to build:

  • React + Vite: npm create vite@latest {name} -- --template react-ts
  • Next.js: npx create-next-app@latest {name} --typescript
  • Express: create package.json + src/index.ts manually

They should also initialize git and create a GitHub repo:

cd {name}
git init && git add . && git commit -m "Initial scaffold"
gh repo create {name} --public --source . --push

Do not run these commands on the user's behalf. Once they confirm the project exists with a GitHub remote, continue.

Step 2 — Generate projects.yaml

Create projects.yaml in the OpenTangl root directory. Each project entry needs:

projects:
  - id: my-app                          # Short kebab-case ID (used in CLI flags)
    name: my-app                        # Human-readable name
    path: ../my-app                     # Relative path from OpenTangl root to the project
    type: react-vite                    # Project type (see below)
    description: React dashboard app    # One-line description
    scan_dirs:
      - src                             # Directories containing source code
    skip_patterns:
      - node_modules
      - dist
      - "*.test.*"
    verify:                             # Commands that must pass before committing
      - command: npm
        args: [run, build]
    package_manager: npm                # npm | yarn | pnpm
    merge:
      target_branch: main               # Branch PRs merge into

Supported types: typescript-node, serverless-js, serverless-ts, react-vite, react-next, express (or any descriptive string).

For multi-project setups, add an environment field to group related projects under a shared vision:

  - id: my-api
    environment: my-product
    # ...
  - id: my-frontend
    environment: my-product
    # ...

Step 3 — Create the Vision Doc

Create docs/environments/{environment}/product-vision.md (use the project id as environment name for single projects, or the environment field for multi-project).

The vision doc has two sections:

Origin & Direction (human-authored, never modified by OpenTangl)

Ask the user to describe:

  • What This Is — 2-3 sentences about the project
  • Where It's Going — long-term direction, 6-12 months out
  • What Matters Most — 3-5 principles guiding decisions

Current Priorities (maintained by OpenTangl after each run)

Ask: "What are the first 3-5 things you want built or improved?"

Write them as Active Initiatives:

### Active Initiatives

1. **{Priority}** — {What and why}
   - Status: not started

If the user isn't sure, offer to read the codebase and suggest priorities.

Step 4 — Configure the LLM

The user needs to create a .env file in the OpenTangl root with their API key. Do not accept or handle API keys directly — provide the template and let the user create the file themselves.

First, verify that .env appears in the project's .gitignore by reading the file. If it does not, add it and tell the user.

Then provide the appropriate template for the user to fill in:

For OpenAI:

OPENAI_API_KEY=sk-...
OPENAI_MODEL=gpt-4o
DEFAULT_AGENT=openai

For Anthropic (Claude):

ANTHROPIC_API_KEY=sk-ant-...
ANTHROPIC_MODEL=claude-sonnet-4-20250514
DEFAULT_AGENT=anthropic

Tell the user: "Create a .env file in the OpenTangl root and paste one of the templates above with your key. This file is gitignored and will never be committed."

Wait for confirmation before continuing.

Step 5 — Prepare the First Run

Initialize an empty task queue:

mkdir -p tasks
echo "tasks: []" > tasks/queue.yaml

Then provide the user with the command to start the autopilot. Do not run this command on the user's behalf — show it and let them execute it:

For a single project:

npx tsx src/cli.ts autopilot --projects {project-id} --cycles 1 --feature-ratio 0.8

For multi-project:

npx tsx src/cli.ts autopilot --projects {api-id},{ui-id} --cycles 1 --feature-ratio 0.8

What happens during a cycle:

  1. OpenTangl reads the vision doc and scans the codebase
  2. It proposes tasks aligned with the vision
  3. It executes each task — writes code, runs verification
  4. It creates PRs, reviews them with the LLM, merges if clean
  5. It updates the vision doc with progress

Tell the user to review the results after the first run — check the generated PRs and the updated vision doc.

Troubleshooting

  • "No pending tasks" — The queue is empty. Run autopilot to have the LLM propose tasks, or add more specific priorities to the vision doc.
  • Build failures — OpenTangl retries up to 3 times with error feedback. If all attempts fail, the task is marked failed and skipped.
  • Escalated PRs — The LLM reviewer flagged critical concerns. Check the GitHub issue it created for details.
  • "OPENAI_API_KEY is required" — Create .env and add your key (see Step 4).
  • Merge conflicts — OpenTangl has a built-in conflict resolver. If it can't resolve automatically, the PR is escalated for human review.

适合场景

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用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.76%
按下载量换算4,116

安全审计

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通过

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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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