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omni-agent-builder全向 Agent 构建器

Agent Skill

omni-agent-builder 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

8,641

周安装

353

GitHub Stars

公开资料未说明

下载量

2,768
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:omni-agent-builder(全向 Agent 构建器)
来源仓库:https://github.com/ollieb89/omni-agent-builder
安装命令:
openclaw skills install omni-agent-builder
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 omni-agent-builder

简介

生成 OpenClaw 工作区所需的核心配置文件与多代理架构模板。

  • 自动生成 SOUL.md、IDENTITY.md 与 AGENTS.md 等规范文档。
  • 支持高性能与安全性配置选项以适应不同团队需求。
  • 使用前需明确代理角色定义与协作流程设计。omni-agent-builder 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 建议定期更新 IDENTITY 文件以保持行为一致性。

SKILL.md

name
omni-agent-builder
description
Build high-performing, secure OpenClaw agents and multi-agent teams end-to-end. Generates required OpenClaw workspace files (SOUL.md, IDENTITY.md, AGENTS.md, USER.md, TOOLS.md, HEARTBEAT.md, BOOTSTRAP.md, optional MEMORY.md + memory/YYYY-MM-DD.md). Incorporates best practices for team orchestration, Personal Intelligence (Pi) memory management, continuous evaluation, and CLI-driven setup/deployment.

Omni-Agent Builder (OpenClaw)

Design and generate a complete OpenClaw agent workspace with robust defaults:

  • secure-by-default operating rules
  • optional multi-agent orchestration (Planner / Executor / Critic)
  • Personal Intelligence (Pi) memory workflow (MEMORY.md + daily logs)
  • evaluation + acceptance tests
  • CLI notes for fast local iteration

Canonical references (read these first)

1) Workspace layout + bootstrap file load order + heartbeat rules: references/openclaw-workspace.md 2) File templates/snippets: references/templates.md 3) Background (agent architecture: planning / memory / tool use): references/architecture.md

Default outputs (workspace files)

Minimum viable workspace (always generate):

  • AGENTS.md (cross-cutting rules; sub-agents only get this + TOOLS.md by default)
  • SOUL.md
  • TOOLS.md
  • IDENTITY.md
  • USER.md
  • HEARTBEAT.md (usually empty to avoid token sink)
  • BOOTSTRAP.md (one-time ritual; delete after completion)

Optional (generate if requested or clearly beneficial):

  • MEMORY.md (curated long-term memory; private/main session only)
  • memory/YYYY-MM-DD.md (daily log seed)

Workflow: build a new agent/team from scratch

Phase 1 — Tight interview (clarifying questions)

Ask only what you need. Prefer 1–2 short rounds.

1) Mission + autonomy - Mission (1 sentence) - Single agent or multi-agent orchestration? - Autonomy: Advisor / Operator / Autopilot

2) Surfaces + boundaries - Channels: Telegram/WhatsApp/Discord/iMessage/Slack/etc. - Private DM only vs group channels? - “Ask before outbound messages” rule (default: ALWAYS ask)

3) Tools + CLI usage - Must it run local openclaw CLI commands? Which quick aliases are desired? - Any repos/paths it should assume?

4) Pi memory - Should it maintain curated MEMORY.md? - Categories: preferences, projects, people/orgs, “never do”, conventions, vocab - Privacy: what must never be stored?

5) Bootstrapping ritual - Any first-run steps (connect channels, create folders, install deps)?

6) Evaluation - What metrics define success? - 5–10 acceptance tests you want it to pass (we’ll propose defaults if none)

Phase 2 — Generate the workspace files

Generate the files listed above. Use the templates but tailor to the user’s answers.

Required global guardrails to include (at minimum):

  • Ask-before-destructive (prefer trash over rm; create backups; show diffs)
  • Ask-before-outbound (never send messages/emails/DMs/calls without explicit approval)
  • Stop-on-CLI-error (unknown flag/exit code → run --help, correct, retry)
  • No secrets in repo (credentials/config belong under ~/.openclaw/…, not the workspace)
  • Group etiquette (don’t claim to be the user; don’t leak private memory)
  • Loop breaker (max iterations; escalate to user with options)

Phase 3 — Orchestration (if multi-agent)

If multi-agent, define roles in AGENTS.md:

  • Planner

- breaks tasks into steps - identifies risks + guardrails - defines acceptance tests

  • Executor

- runs tools/edits files - maintains change log + rollback notes - stops on errors and recovers via --help / docs

  • Critic

- reviews outputs for safety + completeness - checks for policy violations, overreach, and missing requirements - proposes fixes (minimal diffs)

Delegation contract (must be in AGENTS.md):

  • Context to pass: goal, constraints, definition of done, relevant workspace excerpts
  • Explicit do-nots: no destructive actions; no outbound messages; no secrets

Phase 4 — Pi memory workflow (recommended defaults)

  • Append raw notes to memory/YYYY-MM-DD.md (daily log; append-only)
  • Curate durable items into MEMORY.md (preferences, stable facts, conventions)
  • Only load/use MEMORY.md in main private session; avoid in group channels
  • If the user says “remember this”, persist it

Phase 5 — Evaluation + acceptance tests

Provide 5–10 short test prompts. Include at least:

  • Safety test (draft but do not send; ask before sending)
  • CLI recovery test (unknown flag → --help recovery)
  • Pi retention test (store + recall a preference correctly)
  • Orchestration test (delegate; show what context was passed)
  • Group chat etiquette test (avoid leaking private memory)

Workflow: iterate on an existing agent

1) Identify the top failure modes (overreach, loops, verbosity, hallucinations, unsafe actions). 2) Decide if changes belong in: - SOUL.md (tone/persona) - AGENTS.md (rules, delegation, memory workflow) - HEARTBEAT.md (keep tiny; avoid deep thinking) - TOOLS.md (environment notes + CLI aliases) 3) Propose minimal diffs with rollback notes. 4) Add/update acceptance tests.

Deliverable format

When you output a workspace:

  • Print each file with a heading and a fenced code block.
  • If generating a zip, include the complete directory tree and a short “how to install” section.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

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

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

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

74.8%
按下载量换算2,070

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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