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ashish797

FounderClaw

作者 ashish797 · GitHub ↗ · v2.1.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install founderclaw
功能描述
FounderClaw — Multi-agent engineering team for OpenClaw. 29 skills, 6 agents (CEO + 5 departments), structured workspace, auto mode, vision sub-agent routing...
使用说明 (SKILL.md)

FounderClaw

Multi-agent engineering team for OpenClaw. 29 skills. 6 agents. One install.

IMPORTANT: Post-Install Setup Required

After installing this package (via ClawHub or git clone), you MUST run the installer to:

  1. Symlink individual skills to ~/.agents/skills/
  2. Create the workspace at ~/.openclaw/founderclaw/
  3. Apply multi-agent config (6 agents)
  4. Build the headless browser

Run from this directory:

bash install.sh

This is REQUIRED. Without it, only the package directory exists — skills won't be discovered by OpenClaw.

What FounderClaw Adds

Agents:

Agent Role
CEO (🎯) Orchestrates everything
Strategy (📐) Product thinking & design
Shipper (🚀) Code review & deploy
Tester (🔍) QA & browser testing
Safety (🛡️) Security & guardrails
Observer (📊) Debug & retrospectives

Skills (29): Strategy: office-hours, plan-ceo-review, plan-eng-review, plan-design-review, design-consultation, design-review, design-shotgun, autoplan Shipping: review, ship, land-and-deploy, canary, benchmark, document-release Testing: qa, qa-only, browse, setup-browser-cookies, connect-chrome Safety: cso, careful, freeze, guard, unfreeze Debugging: investigate, retro, codex Setup: gstack-upgrade, setup-deploy, install-founderclaw, founderclaw-status

Links

License

MIT

安全使用建议
Before installing or running anything from this package: 1) Inspect install.sh and uninstall.sh (don't run curl | bash without reviewing). 2) Review the install steps that will symlink into ~/.agents/skills/, create ~/.openclaw/founderclaw/, and modify OpenClaw config — back up current config first. 3) Audit the Chrome extension files and browse daemon code if you care about browser privacy: the tool reads Chromium cookie DBs and uses Keychain/secret stores to decrypt cookies (you will see OS prompts). 4) If you don't want proactive/autonomous behavior, avoid enabling 'proactive' features and consider disabling autonomous model invocation for this skill or only using user-invoked flows. 5) Only provide any LLM API keys (Anthropic, etc.) if you understand which tests or features require them. 6) If you are unsure, run the package in an isolated environment (VM or throwaway account) first and verify what install.sh does. These patterns can be legitimate for a browser-driven QA/agent system, but they carry sensitive side effects and merit manual review.
功能分析
Type: OpenClaw Skill Name: founderclaw Version: 2.1.0 FounderClaw is a comprehensive multi-agent engineering system for OpenClaw that provides a persistent browser daemon, automated QA, security auditing, and design tools. The bundle includes a Playwright-based browser manager (browse/src/browser-manager.ts), a cookie import utility for authenticated testing (browse/src/cookie-import-browser.ts), and an installer (install.sh) that configures a multi-agent workspace. While the system possesses high-privilege capabilities such as reading local browser cookies and modifying OpenClaw configurations, these are documented features aligned with its purpose. The code implements security best practices, including bearer token authentication for the local daemon and redaction of sensitive data in activity logs (browse/src/activity.ts). No evidence of malicious intent, unauthorized data exfiltration, or hidden backdoors was found.
能力评估
Purpose & Capability
The name/description (FounderClaw: multi-agent engineering team with a headless browser) lines up with the files and instructions: a browse daemon, 29 skills, install scripts, a Chrome extension, and many SKILL.md workflow docs. Access to local browser cookies, a local HTTP daemon, and symlinking skills into ~/.agents/skills/ are coherent with the described functionality.
Instruction Scope
Runtime instructions require running install.sh (symlinks skills, creates ~/.openclaw/founderclaw, builds the browser binary) and the README suggests a curl|bash install option. The SKILL.md and docs explicitly describe reading Chromium cookie DBs and invoking Keychain prompts for decryption — which is consistent with a browser-testing tool but is sensitive. The package also includes a proactive suggestion system (auto-suggesting skills) and language indicating injection of ETHOS into skill preambles; these behaviors broaden what the agent will do and merit review. No instructions (in metadata) declare external endpoints beyond localhost, but the repo contains code for a Chrome extension and tests that may call LLM APIs if configured.
Install Mechanism
There is no formal install spec in registry metadata, but the package includes install.sh, build scripts, and compiled-binary build instructions. README suggests a remote curl|bash install from GitHub which is high risk unless you trust the source and inspect the script. The repo contains many executables and a browser daemon; installing without reviewing install.sh/uninstall.sh and the extension source could write files, modify config, and register services.
Credentials
Registry metadata declares no required env vars or credentials. However, docs reference optional development/test flows that need ANTHROPIC_API_KEY and other model config; tests and LLM-eval tooling will require API keys if you run them. The code legitimately needs access to local browser cookie DBs and Keychain (decryption) for the browse skill — this is proportionate to the browse capability but sensitive. No unrelated cloud credentials are requested in metadata.
Persistence & Privilege
always:false (no forced presence). The installer intends to symlink skills into ~/.agents/skills/ and create ~/.openclaw/founderclaw/ workspace — this is expected for a multi-skill system but does grant persistent local footprint and will modify your OpenClaw configuration per README. The skill can run autonomously (model invocation not disabled) which is platform default; combine this with the proactive suggestion behavior if you want to limit autonomous actions.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install founderclaw
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /founderclaw 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v2.1.0
Improved install: interactive model selection, platform detection, channel setup, natural agent personalities.
v2.0.1
fix: SKILL.md instructs agent to run install.sh after package install
v2.0.0
v2.0: Clean publish, no fork. Multi-agent engineering team for OpenClaw.
v1.1.0
Security cleanup: removed test files, build scripts. Reduced from 301 to 215 files. Remaining patterns are all legitimate (headless browser, design tool API calls).
v1.0.2
Restored design tool with clean auth.ts. Full capability restored.
v1.0.1
Security cleanup: removed telemetry, API key refs, prompt injection patterns. Reduced suspicious patterns from 69 to 8 (all legitimate).
v1.0.0
Initial release: 29 skills, 6 agents, multi-agent engineering team for OpenClaw.
元数据
Slug founderclaw
版本 2.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 7
常见问题

FounderClaw 是什么?

FounderClaw — Multi-agent engineering team for OpenClaw. 29 skills, 6 agents (CEO + 5 departments), structured workspace, auto mode, vision sub-agent routing... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 155 次。

如何安装 FounderClaw?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install founderclaw」即可一键安装,无需额外配置。

FounderClaw 是免费的吗?

是的,FounderClaw 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

FounderClaw 支持哪些平台?

FounderClaw 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 FounderClaw?

由 ashish797(@ashish797)开发并维护,当前版本 v2.1.0。

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