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Agent Skill · 研究检索

agent-onboarding(Agent 入职)

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

agent-onboarding 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 70,176。

总安装 212周安装 9GitHub Stars 11下载 74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
unknown

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:agent-onboarding(Agent 入职)
来源仓库:https://github.com/b-open-io/prompts
仓库路径:skills/agent-onboarding
安装命令:
npx skills add https://github.com/b-open-io/prompts --skill agent-onboarding
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/b-open-io/prompts --skill agent-onboarding

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

建立标准化 Agent 入职流程,确保角色定义与行为规范一致。包含命名约定、显示名称设定与技能边界划分指导。强制按阶段推进,禁止跳过设计环节直接进入编码阶段。推送 master 分支即代表正式发布,市场平台自动同步最新提交。agent-onboarding 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/agent-onboarding

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/b-open-io/prompts --skill agent-onboarding;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

agent-onboarding 怎么安装?

在终端执行 npx skills add https://github.com/b-open-io/prompts --skill agent-onboarding。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-onboarding 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

agent-onboarding 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。

agent-onboarding 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

agent-onboarding 用的人多吗?

公开数据是累计安装 212 次,近一周安装 9 次,下载 74 次,GitHub 11 星。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。

agent-onboarding 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

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。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agent-onboarding

Agent 入职 · 本页

21211接触敏感数据未明确通过

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

Agent Onboarding

End-to-end checklist for bringing a new agent onto the bOpen team. Work through each phase in order. Do not skip steps.

Plugin repo: ~/code/prompts (bopen-tools on the marketplace) Pushing to master IS publishing — the marketplace picks up the latest commit automatically.


Phase 1: Design the Agent

Before writing a single file, define the agent's identity.

  • Name — choose a lowercase-hyphenated identifier (e.g., code-auditor, front-desk). This becomes the filename and the subagent_type suffix.
  • Display name — the character's name as it appears in chat (e.g., "Satchmo", "Martha", "Johnny").
  • Historical/cultural inspiration — pick a real figure whose expertise mirrors the agent's domain. This grounds the avatar and the system prompt voice.
  • Expertise scope — one clear sentence: what the agent does and what it explicitly does NOT handle.
  • Trigger phrases — what kinds of tasks should route to this agent? List 5–10.
  • Delegation targets — which other agents does this one hand off to?
  • Model — use sonnet for most tasks; opus for complex reasoning, security, or architecture review.
  • Color — pick one: red, orange, yellow, green, teal, blue, purple, pink, gray.
  • Tools — list every tool and skill the agent needs. Agents without a tools: field get full MCP access. Agents with tools: only see what's listed, so be complete.

Phase 2: Write the Agent File

Agents use a folder-based package structure with a symlink for Claude Code compatibility:

agents/
  {name}.md → {name}/{name}.md   (symlink — Claude Code auto-discovers this)
  {name}/
    {name}.md                    (actual agent definition — source of truth)
    SOUL.md                      (optional — personality/persona)
    HEARTBEAT.md                 (optional — execution procedures for Paperclip)
    TOOLS.md                     (optional — tool reference)
    avatar.png                   (optional — agent portrait)

Creating the folder and symlink

mkdir -p agents/{name}
# Write the agent .md file inside the folder
# Then create the symlink at the top level:
ln -sf {name}/{name}.md agents/{name}.md

Claude Code discovers agents/{name}.md (the symlink). Paperclip and ClawNet can reference the folder for the full agent package.

Frontmatter format

---
name: agent-name
display_name: "Display Name"
version: 1.0.0
model: sonnet
description: One-sentence description of what this agent does and when to route to it.
tools: Read, Write, Edit, MultiEdit, Bash, Grep, Glob, WebFetch, Skill(bopen-tools:relevant-skill)
color: blue
---

System prompt structure

Write the body in this order:

  1. Role statement — "You are a [domain] specialist." One sentence.
  2. Mission — What you ship/produce. One sentence.
  3. Self-announcement block — Copy from an existing agent and update the version and specialization. Every agent announces itself at task start.
  4. Expertise section — Bullet list of specific capabilities. Be concrete, not vague.
  5. Key documentation — WebFetch URLs or file references the agent should consult. Embedding these prevents the agent from doing unnecessary research from scratch.
  6. Delegation rules — Explicit list of what this agent does NOT handle and which agent to route to instead.
  7. Output standards — File format, code style, testing expectations.

Key documentation to include

Every agent should have at least one concrete documentation reference. Examples:

  • nextjs: https://nextjs.org/docs, https://sdk.vercel.ai/docs
  • database: https://docs.convex.dev, Bun SQL docs
  • mcp: ~/code/prompts/agents/mcp.md (read the existing Orbit agent for patterns)

Look at existing agents in ~/code/prompts/agents/ for reference. The mcp.md, database.md, and agent-builder.md agents are good structural examples.


Phase 3: Generate an Avatar

Every agent needs a portrait avatar.

Generate with gemskills

Invoke Skill(gemskills:generate-image) or delegate to the gemskills:content agent.

Prompt template:

Portrait of [historical figure name], [brief description of who they are].
Professional headshot style. Clean background. High detail.
Consistent with a team of AI agent avatars.

Specs:

  • Size: 1024x1024
  • Format: PNG
  • Save to: agents/avatars/{name}.png

ClawNet ICO (optional)

If the agent will run as a live ClawNet bot, also generate a 32x32 ICO version for the bot's profile icon. The ICO file goes in the same agents/avatars/ directory as {name}.ico.


Phase 4: Update the Plugin

  • Open ~/code/prompts/.claude-plugin/plugin.json
  • Bump the version (patch for new agents: e.g., 1.0.86 → 1.0.87)
  • The agents array is not in plugin.json for bopen-tools — the plugin auto-discovers agent .md files from the agents/ directory. No manual registration needed.
  • Update ~/code/prompts/skills/deploy-agent-team/references/agent-roster.md — add a row to the roster table with the new agent's subagent_type, model, and best-for summary.
  • Stage all new/modified files: agent .md, avatar PNG, plugin.json, agent-roster.md
  • Commit with a clear message: Add {name} agent with avatar
  • Push to master — this publishes automatically
cd ~/code/prompts
git add agents/{name}.md agents/avatars/{name}.png .claude-plugin/plugin.json skills/deploy-agent-team/references/agent-roster.md
git commit -m "Add {name} agent with avatar"
git push

Phase 5: Update bOpen.ai Roster

  • Visit bopen.ai to check the current team roster
  • The roster may auto-update from the plugin manifest within a few minutes of the push
  • If the agent does not appear after 5 minutes, check whether bopen.ai requires a manual trigger or cache clear
  • Verify: correct display name, correct description, correct avatar

Phase 6: Register in Paperclip (When Applicable)

If the agent will run inside bOpen's Paperclip instance (paperclip.bopen.io), register it there. Paperclip is the control plane — it manages heartbeats, budgets, task assignment, and org hierarchy.

Paperclip agent model

Paperclip agents are NOT the same as Claude Code plugin agents. Key differences:

ConcernClaude Code PluginPaperclip
Identity.md file in plugin repoDB record via API/UI
Personality/promptBody of .md filePrompt template or instructionsFilePath
HierarchyFlat peersStrict tree (reportsTo)
BudgetNonebudgetMonthlyCents with auto-pause at 100%
ExecutionOn-demand subagentHeartbeat protocol (scheduled wakes)
RolesFreeform11 fixed: ceo, cto, cmo, cfo, engineer, designer, pm, qa, devops, researcher, general

Registration via Paperclip UI

  1. Navigate to the Agents page, click "Create Agent"
  2. Agent name — use the display_name from the .md file (e.g., "Martha", "Jerry")
  3. Adapter type — Claude Code for all bOpen agents running Claude
  4. Working directory — /paperclip/.agents/{slug} where {slug} is the name from the agent .md frontmatter (e.g., code-auditor). On Railway persistent volume.
  5. Model — match the model: field from the .md frontmatter (sonnet → Claude Sonnet, opus → Claude Opus)
  6. Role — map to the closest Paperclip enum. Use title field for the actual job description
  7. Reports to — select the agent's manager in the org tree
  8. Budget — set monthly spend limit in cents. Guidelines:

- Opus agents: $50/month (5000 cents) - Sonnet agents: $20/month (2000 cents) - Haiku agents: $5/month (500 cents) - CEO/CTO: higher budgets as needed

  1. Capabilities — paste the description: from the .md frontmatter
  2. Environment check — click "Test now" to verify adapter, API key, and working directory

Role mapping guide

bOpen Agent TypePaperclip RoleTitle (freeform)
CEO / strategistceoChief Executive Officer
Engineering leadctoChief Technology Officer
Directory/routingcmoFront Desk / Directory Service
Financial oversightcfoChief Financial Officer
Most specialistsengineer[Actual specialty] Specialist
UI/UX agentsdesignerUI/UX Designer
Project coordinatorspmProject Manager
Testing/auditingqa[Code Auditor / Tester]
Infra/CI/CDdevopsInfrastructure Lead
Research agentsresearcherLead Researcher
Everything elsegeneral[Actual role description]

Heartbeat protocol awareness

Agents running in Paperclip must follow the heartbeat protocol defined in the Paperclip skill (see Quick Reference table for path). Reference that skill in the agent's system prompt or install it in their working directory.

Dual-ecosystem agents

Most bOpen agents exist in BOTH ecosystems:

  • Claude Code plugin: personality, system prompt, tools, skills (source of truth)
  • Paperclip: runtime config, hierarchy, budget, heartbeat scheduling

The .md file in the plugin repo is always the source of truth for who the agent IS. Paperclip owns HOW it runs (schedule, budget, reporting chain). Never duplicate the system prompt — reference it or paste it into Paperclip's prompt template field.

Environment requirements

For Paperclip on Railway:

  • ANTHROPIC_API_KEY must be set as Railway env var
  • Working directories on /paperclip/ volume persist across deploys
  • First Claude Code invocation is slow (cold start) — environment check may timeout but still works
  • Agents run as node user via gosu entrypoint (not root)

Phase 7: Deploy as ClawNet Bot (Optional)

Only if the agent needs a live, always-on bot instance (e.g., a 24/7 support agent, a monitoring bot).

  • Invoke Skill(clawnet:clawnet-cli) for the deployment workflow
  • Initialize a BAP identity for the bot — this is its permanent on-chain identity
  • Configure the bot's connection to the ClawNet network
  • ClawNet repos: ~/code/clawnet (core) and ~/code/clawnet-bot (bot runner)
  • After deployment, hand off to Johnny (clawnet-bot:clawnet-mechanic) for ongoing health and maintenance

Johnny handles: uptime monitoring, reconnects, key rotation, and ClawNet-specific debugging.


Phase 8: Notify Martha

After any new agent is deployed:

  • Tell Martha (bopen-tools:front-desk) about the new agent's name, trigger phrases, and delegation rules
  • Martha handles routing for the team — she needs to know who's available and what they handle
  • Update the skills/front-desk/references/service-providers.md file if Martha's routing reference needs updating

Phase 9: Verify

  • Spawn the new agent with a simple test task relevant to its domain
  • Confirm it announces itself correctly (name, version, specialization, mission)
  • Confirm it has access to the right tools and skills (check the tools: field)
  • Confirm it knows its documentation references (ask it to fetch one)
  • Confirm it delegates correctly (give it a task outside its scope and verify it routes properly)
  • Confirm the avatar appears on bopen.ai

Quick Reference

ItemLocation
Agent files~/code/prompts/agents/{name}.md
Avatars~/code/prompts/agents/avatars/{name}.png
Plugin manifest~/code/prompts/.claude-plugin/plugin.json
Agent roster~/code/prompts/skills/deploy-agent-team/references/agent-roster.md
ClawNet core~/code/clawnet
ClawNet bot runner~/code/clawnet-bot
Bot maintenanceJohnny (clawnet-bot:clawnet-mechanic)
Routing updatesMartha (bopen-tools:front-desk)
Avatar generationSkill(gemskills:generate-image) or gemskills:content agent
Paperclip instancehttps://paperclip.bopen.io
Paperclip repo~/code/paperclip (b-open-io/paperclip)
Paperclip skill~/code/paperclip/skills/paperclip/SKILL.md
Tortuga plugin~/code/tortuga-plugin (@bopen-io/tortuga-plugin)
Agent working dirs/paperclip/.agents/{slug} (Railway volume)

平台分布

Codex

33.05%
按下载量换算24

Claude

32.47%
按下载量换算24

Cursor

17.95%
按下载量换算13

Gemini CLI

8.76%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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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