hire
Interactive hiring wizard to set up a new AI team member. Guides the user through role design via conversation, generates agent identity files, and optionally sets up performance reviews. Use when the user wants to hire, add, or set up a new AI agent, team member, or assistant. Triggers on phrases like "hire", "add an agent", "I need help with X" (implying a new role), or "/hire".
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/larsderidder/hirehire
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:
šÆ Role: [one-line description]
š§ Name: [suggested name from naming taxonomy]
š¤ Model: [selected model] ([tier])
ā” Personality: [2-3 word vibe]
š§ Tools: [inferred from conversation]
š« Boundaries: [key red lines]
š¤ 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 ā reasoning tier
- Research/writing/creative ā balanced tier
- Code-focused ā code tier (or balanced if not available)
- High-volume/monitoring ā fast tier
Step 4: Select and confirm
Pick the best available model for the role. In the summary card, add:
š¤ Model: [selected model] ([tier] - [brief reason])
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-larsderidder-hire": {
"enabled": true,
"auto_update": true
}
}
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