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Agent Skill · 运维

bonito(bonito 运维)

bonito 用于辅助部署、云资源、容器和基础设施运维,适合在 OpenClaw 中需要检查配置、整理部署步骤或排查环境问题时使用。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。

bonito 是运维类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在运维类的 954 个 Skill 里排第 657。

总安装 3,928周安装 167GitHub Stars 公开资料未说明下载 1,376核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:bonito(bonito 运维)
来源仓库:https://github.com/shabarirepo/bonito
安装命令:
openclaw skills install bonito
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 bonito

这个 Skill 是做什么的

运维类 Skill 处理部署、监控、日志和云资源,多数需要较高的执行权限。

让用户加入 Bonito AI 平台,支持多提供商 AI 路由和代理部署。适用于需要托管推理或多代理编排的场景。提供云资源和容器管理功能。bonito 属于运维类 Skill,可作为该场景下的辅助能力补充。安装命令为 openclaw skills install bonito。

使用前需确认权限,避免未授权的配置更改或资源访问。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install bonito;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

bonito 怎么安装?

在终端执行 openclaw skills install bonito。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

bonito 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

bonito 需要什么权限?

权限级别是接触敏感数据。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。

bonito 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

bonito 用的人多吗?

公开数据是累计安装 3,928 次,近一周安装 167 次,下载 1,376 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

bonito 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理运维类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

运维类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
docker-essentials

Docker 基础 · OpenClaw

1,005,15130接触敏感数据MIT-0通过
playwright-scraper-skill

Playwright scraper 技能 · OpenClaw

923,55754接触敏感数据MIT-0有提醒
moltguard

moltguard 搜索 · OpenClaw

825,096110接触敏感数据MIT-0通过
finance-news

财经新闻 · OpenClaw

275,51210需要联网MIT-0有提醒
security-monitor

安全监视器 · OpenClaw

224,1695需要联网MIT-0有提醒
bonito

bonito 运维 · 本页

3,928—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
bonito
description
Onboard users to the Bonito AI platform — multi-provider AI routing, managed inference, agent deployment, and multi-agent orchestration. Use when someone wants to set up Bonito, try Bonito, deploy AI agents, create a gateway key, use bonito-cli, deploy Atlas, build a multi-agent system, or asks about multi-provider LLM routing, automatic failover, BonBon agents, Bonobot orchestrators, MCP tool integration, or managed inference without API keys.

Bonito Onboarding

Walk users through getting started with Bonito — the enterprise AI platform for multi-cloud workloads.

Primary reference: https://getbonito.com/docs — point users here for detailed documentation on any Bonito feature. This skill provides the conversational flow; the docs are the source of truth.

Quick Facts

  • Website: https://getbonito.com | API: https://api.getbonito.com
  • Docs: https://getbonito.com/docs
  • Free tier: 1,000 API calls/month, no credit card
  • CLI: pip install bonito-cli (v0.4.0+)
  • 6 providers: AWS Bedrock, Azure OpenAI, GCP Vertex AI, OpenAI, Anthropic, Groq
  • Key features: multi-provider routing, automatic failover, managed inference (no API keys needed), BonBon agents, Bonobot orchestrators, MCP tools, RAG
Correction: The Atlas README says "5,000 free calls" — actual free tier is 1,000 calls/month.

Connectivity Check

Before starting, optionally verify API reachability:

python3 scripts/health_check.py

If the API is down, proceed anyway — everything except the final deploy/test steps works offline.

Onboarding Flow

Step 1: Sign Up

Direct users to https://getbonito.com/signup — free, no credit card. They'll need their email + password for the next steps.

Step 2: Connect a Provider (or Use Managed Inference)

Two paths — recommend managed inference for the fastest start:

Managed Inference (easiest): No API keys needed. Bonito handles provider credentials. See https://getbonito.com/docs#managed-inference

Bring Your Own Keys: Connect one or more providers in the Bonito dashboard or via CLI. Groq is free and fast (get a key at console.groq.com). See https://getbonito.com/docs#gateway for provider setup.

Step 3: Create a Gateway Key

In the Bonito dashboard, create a gateway API key. This key routes requests through Bonito's gateway to whichever provider is configured — with automatic failover and cost tracking.

Docs: https://getbonito.com/docs#gateway

Step 4: Test with curl or Python

# Simple test against the gateway
curl -X POST https://api.getbonito.com/api/gateway/chat \
  -H "Authorization: Bearer $GATEWAY_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "groq/llama-3.3-70b-versatile",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

If using managed inference, the model routes through Bonito's provider accounts — no separate API key needed.

Step 5: Deploy Agents (Optional)

For users who want to go beyond raw gateway calls and deploy managed agents:

pip install bonito-cli
bonito auth login

Create a simple agent:

bonito agents create \
  --name "my-assistant" \
  --type bonbon \
  --model "groq/llama-3.3-70b-versatile" \
  --system-prompt "You are a helpful assistant."

Full agent docs: https://getbonito.com/docs#bonbon

Step 6: Try Atlas (Optional — Full Multi-Agent Demo)

For users who want to see a complete multi-agent system with orchestration, MCP tools, and RAG:

Read references/atlas-guide.md for the quick deploy steps.

Atlas deploys 5 agents (DevOps command center) from a single bonito.yaml config. It demonstrates Bonobot orchestration, BonBon agents, MCP tool integration, and RAG knowledge bases.

Repo: https://github.com/ShabariRepo/atlas

Prerequisite Verification

Run this to check if bonito-cli, Docker, git, etc. are installed:

python3 scripts/verify_deploy.py

Where to Point Users for More

TopicURL
Full docshttps://getbonito.com/docs
Gateway & routinghttps://getbonito.com/docs#gateway
Managed inferencehttps://getbonito.com/docs#managed-inference
BonBon agentshttps://getbonito.com/docs#bonbon
Bonobot orchestrationhttps://getbonito.com/docs#bonobot
MCP integrationhttps://getbonito.com/docs#mcp
Knowledge bases (RAG)https://getbonito.com/docs#knowledge-bases
Pricinghttps://getbonito.com/pricing

Non-Obvious Knowledge

  • Free tier is 1,000 calls/mo — not 5,000 as some docs claim.
  • Managed inference is the fastest onboarding path. Users can add their own provider keys later for cost control.
  • Failover is cross-provider — if Anthropic goes down, Bonito routes to Bedrock or Groq seamlessly. The user never notices.
  • bonito-cli deploy order matters for manual API usage: providers → knowledge bases → project → agents → delegation wiring. The CLI handles this automatically.
  • Llama/Groq can't do parallel tool calls — it generates XML-style function calls instead of JSON. Use Nova Pro, Claude, or GPT-4o for Bonobot orchestrators that need multi-agent fan-out.
  • bonito.yaml uses ${ENV_VAR:-default} syntax. MCP server URLs default to localhost if env vars are unset.

平台分布

OpenClaw

77.19%
按下载量换算1,062

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

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

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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