← 返回
未分类 中文

OpenClaw Consensus

Run a fixed 2-round cross-model deliberation through the repo-local OpenClaw Consensus runtime.
通过仓库本地的OpenClaw Consensus运行时运行固定的2轮跨模型协商。
pstepien-labs pstepien-labs 来源
未分类 clawhub v0.1.2 1 版本 99703.3 Key: 无需
★ 0
Stars
📥 336
下载
💾 0
安装
1
版本
#latest

概述

OpenClaw Consensus

Use this skill when the user explicitly wants a bounded cross-model deliberation on one brief.

What this skill does

  • runs the same brief through 2-4 explicitly selected API-backed models from the active OpenClaw-configured pool
  • preserves round-1 and round-2 artifacts on disk
  • asks the current session model to write the final synthesis

Do not use this skill when

  • the user wants casual chat or a single quick answer
  • the user did not agree to explicit model selection yet
  • the request is framed as replacing a lawyer, accountant, doctor, engineer, or other expert

Required inputs

Before running, confirm all of these:

  1. one final brief
  2. an explicit model shortlist of at least 2 models
  3. an optional run label if the user wants one

Model rules

  • In this MVP, the model shortlist is required.
  • Only use models that appear in node {baseDir}/src/cli.mjs models.
  • Do not silently substitute a missing or failing model.
  • Do not use ollama/* models in this repo's MVP.

Invocation flow

  1. If needed, inspect the configured model pool:

```bash

node {baseDir}/src/cli.mjs models

```

  1. Run the consensus flow with the brief, explicit model list, and the current session model as orchestrator:

```bash

node {baseDir}/src/cli.mjs run --brief "" --models "openai-codex/gpt-5.4,openai-codex/gpt-5.5" --orchestrator-model "" --label "optional-label"

```

  1. Read back the generated final.md and run.json before summarizing for the user.

Output expectations

Read the final synthesis carefully and present it truthfully:

  • consensus
  • disagreements
  • unresolved uncertainty
  • escalation points
  • best overall synthesis

Safety rules

  • Preserve disagreement; do not flatten it in your summary.
  • Consensus is not proof of correctness.
  • Keep expert-escalation language narrow and honest.
  • If the CLI reports a fallback or unavailable selected model, stop and surface the failure clearly instead of improvising around it.

版本历史

共 1 个版本

  • v0.1.2 当前
    2026-05-07 17:58 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

ai-agent

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,381 📥 320,685
dev-programming

Github

steipete
使用 `gh` CLI 与 GitHub 交互,通过 `gh issue`、`gh pr`、`gh run` 和 `gh api` 管理议题、PR、CI 运行及高级查询。
★ 676 📥 325,626
ai-agent

self-improving agent

pskoett
捕获经验教训、错误及修正内容,以实现持续改进。适用于以下场景:(1)命令或操作意外失败;(2)用户纠正Claude(如“不,那不对……”“实际上……”);(3)用户请求的功能不存在;(4)外部API或工具出现故障;(5)Claude发现自身
★ 4,082 📥 812,424