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Council of Wisdom - Multi-Agent Debate
作者
miknasbh-stack
· GitHub ↗
· v1.0.0
· MIT-0
235
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install miknas-council-of-wisdom
功能描述
Facilitates structured multi-agent debates with opposing expert views, a referee moderator, and 9 specialized AI council votes for balanced decision-making.
安全使用建议
This package appears to be what it says: a multi-agent debate orchestrator for OpenClaw/ACP. Before installing or running it, consider: (1) Debate transcripts and logs are written to your workspace and will be forwarded to whatever LLM providers your OpenClaw runtime is configured with — review provider credentials and privacy/security policies. (2) The scripts may call gh and jq for GitHub integration and JSON processing; ensure those tools are available and authorized. (3) Cleanup logic kills subagents named council-*; on shared hosts this could affect other users' sessions if naming collides. (4) Review the prompt templates and any sample prompts to avoid embedding sensitive or proprietary data you don't want sent to third-party LLMs. (5) If you intend to use this in production, run it in a controlled/trusted OpenClaw environment, verify provider credentials and auditing, and confirm required CLI tools (gh, jq, git) are present. Overall the skill is internally consistent (benign) but operational/privacy considerations above should be addressed before use.
功能分析
Type: OpenClaw Skill
Name: miknas-council-of-wisdom
Version: 1.0.0
The Council of Wisdom skill bundle is a comprehensive multi-agent orchestration framework designed for structured AI debates. It utilizes shell scripts (council-of-wisdom.sh) to manage a local workspace, initialize git repositories, and interact with the GitHub CLI (gh) for issue tracking. The implementation details in IMPLEMENTATION.md and the agent prompts in the templates directory correctly leverage OpenClaw's ACP (Agent Control Panel) features, such as sessions_spawn and subagents action=kill, for lifecycle management and cleanup. No evidence of data exfiltration, malicious execution, or deceptive prompt injection was found; the high-privilege operations (file management and agent control) are well-documented and strictly aligned with the system's stated purpose.
能力评估
Purpose & Capability
The skill claims a multi-agent debate framework and its files (SKILL.md, IMPLEMENTATION.md, scripts, templates) and examples consistently show usage of OpenClaw/ACP primitives (sessions_spawn, subagents, sessions_send). Declared dependency on OpenClaw and optional gh aligns with the documented GitHub integration. There are no unexpected environment variables or binaries requested that don't match the stated purpose.
Instruction Scope
Runtime instructions legitimately cover spawning referee/debater/council agents, collecting transcripts, tallying votes, generating reports, and cleanup. However, the flow routes debate transcripts to external LLM providers (OpenAI, Anthropic, Google, Zai) via the ACP runtime — meaning debate data will be sent to whatever providers the agent runtime is configured to use. The scripts also write under ~/.openclaw/workspace and create GitHub repos via gh if used. No instructions read unrelated system secrets, but users should note that transcripts and logs are written to disk and forwarded to external models.
Install Mechanism
There is no remote download/install step — this is instruction + script based and installs into the user's OpenClaw workspace. No external URLs or archive extraction are used by the skill metadata. The CLI and helper scripts are included locally. This is lower-risk than arbitrary remote installers.
Credentials
The skill declares no required env vars or credentials, which matches provided files. That said, it implicitly depends on OpenClaw/ACP being configured with provider credentials (for provider models like openai/gpt-4, google/gemini-pro, etc.) and on optional tools like gh and jq for some features; those credentials live outside the skill. Users should be aware provider credentials configured in OpenClaw will be used to send transcripts and prompts to third-party LLMs.
Persistence & Privilege
The skill does not request always:true and uses normal autonomous invocation patterns (spawning sessions via the ACP runtime). Cleanup routines kill subagents matching council-*; on a multi-tenant or shared OpenClaw host that could terminate other sessions named similarly. Otherwise, no unusual privilege escalation or modification of other skills' configurations is present.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install miknas-council-of-wisdom - 安装完成后,直接呼叫该 Skill 的名称或使用
/miknas-council-of-wisdom触发 - 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
v1.0.0
Initial release: Multi-agent debate system with 12 expert agents, structured decision making, enterprise-grade monitoring
元数据
常见问题
Council of Wisdom - Multi-Agent Debate 是什么?
Facilitates structured multi-agent debates with opposing expert views, a referee moderator, and 9 specialized AI council votes for balanced decision-making. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 235 次。
如何安装 Council of Wisdom - Multi-Agent Debate?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install miknas-council-of-wisdom」即可一键安装,无需额外配置。
Council of Wisdom - Multi-Agent Debate 是免费的吗?
是的,Council of Wisdom - Multi-Agent Debate 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Council of Wisdom - Multi-Agent Debate 支持哪些平台?
Council of Wisdom - Multi-Agent Debate 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 Council of Wisdom - Multi-Agent Debate?
由 miknasbh-stack(@miknasbh-stack)开发并维护,当前版本 v1.0.0。
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