Agent审查
- 作者仓库星标 39
- 作者更新于 实时读取
- 作者仓库 awesome-omni-skill
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @diegosouzapw · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 即装即用
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: hire
description: Interactive hiring wizard to set up a new AI team member. Guides the user through role design vi…
category: AI 智能
runtime: 无特殊运行时
---
# hire 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“When to Use / The Interview / 3 core questions, asked one at a time:”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“When to Use / The Interview / 3 core questions, asked one at a time:”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文出现了 `/hire` 这类斜杠命令;如果你的 Agent 支持命令触发,优先用命令开场,再补充目标和边界。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“When to Use / The Interview / 3 core questions, asked one at a time:”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: hire
description: Interactive hiring wizard to set up a new AI team member. Guides the user through role design vi…
category: AI 智能
source: diegosouzapw/awesome-omni-skill
---
# hire
## 什么时候使用
- 用于审阅代码、文档或方案并给出可执行反馈 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「When to Use / The Interview / 3 core questions, asked one at a time:」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "hire" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> When to Use / The Interview / 3 core questions, asked one at a time:
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} hire
Set up a new AI team member through a guided conversation. Not a config generator - a hiring process.
When to Use
User says something like:
- "I want to hire a new agent"
- "I need help with X" (where X implies a new agent role)
- "Let's add someone to the team"
/hire
The Interview
3 core questions, asked one at a time:
Q1: "What do you need help with?" Let them describe the problem, not a job title. "I'm drowning in code reviews" beats "I need a code reviewer."
- Listen for: scope, implied autonomy level, implied tools needed
Q2: "What's their personality? Formal, casual, blunt, cautious, creative?" Or frame it as: "If this were a human colleague, what would they be like?"
- Listen for: communication style, vibe, how they interact
Q3: "What should they never do?" The red lines. This is where trust gets defined.
- Listen for: boundaries, safety constraints, access limits
Q4: Dynamic (optional)
After Q1-Q3, assess whether anything is ambiguous or needs clarification. If so, ask ONE follow-up question tailored to what's unclear. Examples:
- "You mentioned monitoring - should they alert you immediately or batch updates?"
- "They'll need access to your codebase - any repos that are off-limits?"
- "You said 'casual' - are we talking friendly-professional or meme-level casual?"
If Q1-Q3 were clear enough, skip Q4 entirely.
Summary Card
After the interview, present a summary:
🎯 Role: [one-line description]
🧠 Name: [suggested name from naming taxonomy]
🤖 Model: [selected model] ([tier])
⚡ Personality: [2-3 word vibe]
🔧 Tools: [inferred from conversation]
🚫 Boundaries: [key red lines]
🤝 Autonomy: [inferred level: high/medium/low]
Then ask: "Want to tweak anything, or are we good?"
Model Selection
Before finalizing, select an appropriate model for the agent.
Step 1: Discover available models
Run openclaw models list or check the gateway config to see what's configured.
Step 2: Categorize by tier
Map discovered models to capability tiers:
| Tier | Models (examples) | Best for |
|---|---|---|
| reasoning | claude-opus-, gpt-5, gpt-4o, deepseek-r1 | Strategy, advisory, complex analysis, architecture |
| balanced | claude-sonnet-*, gpt-4-turbo, gpt-4o-mini | Research, writing, general tasks |
| fast | claude-haiku-, gpt-3.5, local/ollama | High volume, simple tasks, drafts |
| code | codex-, claude-sonnet-, deepseek-coder | Coding, refactoring, tests |
Use pattern matching on model names - don't hardcode specific versions.
Step 3: Match role to tier
Based on the interview:
- Heavy reasoning/advisory/strategy → reasoning tier
- Research/writing/creative → balanced tier
- Code-focused → code tier (or balanced if not available)
- High-volume/monitoring → fast tier
Step 4: Select and confirm
Pick the best available model for the role. In the summary card, add:
🤖 Model: [selected model] ([tier] - [brief reason])
If multiple good options exist or you're unsure, ask: "For a [role type] role, I'd suggest [model] (good balance of capability and cost). Or [alternative] if you want [deeper reasoning / faster responses / lower cost]. Preference?"
Notes
- Don't assume any specific provider - work with what's available
- Cheaper is better when capability is sufficient
- The user's default model isn't always right for every agent
- If only one model is available, use it and note it in the summary
Optional Extras
After the summary is confirmed, offer:
"Want to set up periodic performance reviews?"
- If yes: ask preferred frequency (weekly, biweekly, monthly)
- Create a cron job that triggers a review conversation
- Review covers: what went well, what's not working, scope/permission adjustments
- At the end of each review, ask: "Want to keep this schedule, change frequency, or stop reviews?"
Onboarding assignment (if relevant to the role)
- Suggest a small first task to test the new agent
- Something real but low-stakes, so the user can see them in action
What to Generate
Create an agent directory at agents/<name>/ with:
Always unique (generated fresh):
- AGENTS.md - Role definition, responsibilities, operational rules, what they do freely vs ask first
- IDENTITY.md - Name, emoji, creature type, vibe, core principles
Start from template, customize based on interview:
- SOUL.md - Base from workspace SOUL.md template, customize vibe/boundaries sections
- TOOLS.md - Populated with inferred tools and access notes
- HEARTBEAT.md - Empty or with initial periodic tasks if relevant to role
Symlink to shared (default, opinionated):
- USER.md →
../../USER.md(they need to know who they work for) - MEMORY.md →
../../MEMORY.md(shared team context)
Mention to the user: "I've linked USER.md and MEMORY.md so they know who you are and share team context. You can change this later if you want them more isolated."
Naming
Use craft/role-based names. Check TOOLS.md for the full naming taxonomy:
- Research: Scout, Observer, Surveyor
- Writing: Scribe, Editor, Chronicler
- Code: Smith, Artisan, Engineer
- Analysis: Analyst, Assessor, Arbiter
- Creative: Muse, Artisan
- Oversight: Auditor, Reviewer, Warden
Check existing agents to avoid name conflicts. Suggest a name that fits the role, but let the user override.
Team Awareness
Before generating, check agents/ for existing team members. Note:
- Potential overlaps with existing roles
- Gaps this new hire fills
- How they'll interact with existing agents
Mention any relevant observations: "You already have Scout for research - this new role would focus specifically on..."
After Setup
- Tell the user what was created and where
- Add the agent to OpenClaw config with the selected model:
Or guide them to run{ "id": "<name>", "workspace": "/path/to/clawd/agents/<name>", "model": "<selected-model>" }openclaw agents add - If monthly reviews were requested, confirm the cron schedule
- Update any team roster if one exists
Important
- This is a CONVERSATION, not a form. Be natural.
- Infer as much as possible from context. Don't ask what you can figure out.
- The user might not know what they want exactly. Help them figure it out.
- Keep the whole process under 5 minutes for the simple case.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核