Installable skillMIT

Employee

An MCP server that provides on-demand skill loading for AI coding assistants.

BY modbenderUPDATED Oct 28, 2026
INTENDED FORβ—ˆOpenClawInstall in a listed agent.

instructions.md

---
name: employee-b6032981969b
slug: employee
version: 1.0.0
description: Create and manage virtual AI employees with persistent memory, defined roles, and graduated autonomy. Hire, train, and delegate tasks to specialized workers.
metadata: {"clawdbot":{"emoji":"πŸ‘”","requires":{"bins":[]},"os":["linux","darwin","win32"]}}
---

## Architecture

Employees live in ~/employee/ with per-employee folders. See `employee-template.md` for setup.

```
~/employee/
β”œβ”€β”€ registry.json          # Index of all employees + status
β”œβ”€β”€ employees/
β”‚   └── {name}/
β”‚       β”œβ”€β”€ employee.json  # Role, permissions, stats
β”‚       β”œβ”€β”€ memory/
β”‚       β”‚   └── context.md # Persistent learnings
β”‚       └── logs/          # Work history by date
└── shared/
    └── protocols.md       # Common instructions
```

## Quick Reference

| Topic | File |
|-------|------|
| Setup templates | `employee-template.md` |
| Autonomy levels | `autonomy.md` |
| Task routing | `routing.md` |
| Lifecycle commands | `lifecycle.md` |

## Core Rules

### 1. One Role Per Employee
- Each employee has a single clear domain (researcher, reviewer, support)
- Never generalist catch-alls
- Scope defined in `employee.json` β†’ `role` and `permissions`

### 2. Memory is Mandatory
- Load `memory/context.md` before every task
- Employees remember context across sessions
- Log learnings after each task

### 3. Escalate Uncertainty
- Employees say "I don't know" rather than guess
- Escalation triggers defined in `employee.json`
- Never confident hallucinations

### 4. Graduated Autonomy
| Level | Behavior |
|-------|----------|
| shadow | Watches, doesn't act (onboarding) |
| draft-only | Creates drafts, human sends |
| review | Acts, human approves before external effect |
| autonomous | Full delegation within permissions |

See `autonomy.md` for promotion criteria.

### 5. Explicit Permissions
- Read vs write access per system
- File access paths whitelisted
- `canSpawn` and `canMessage` flags
- Code Reviewer can comment, cannot merge

### 6. Task Routing
When request arrives:
1. Explicit: "Luna, do X" β†’ route to Luna
2. Implicit: match against `registry.json` roles β†’ suggest
3. See `routing.md` for auto-delegation rules

### 7. Reporting
Each employee provides:
- Daily: What I did, what needs attention, what's coming
- Weekly: Tasks completed, escalations, token usage

### 8. Lifecycle
| Command | Action |
|---------|--------|
| hire {name} as {role} | Create employee |
| train {name} on [docs] | Add to memory |
| evaluate {name} | Performance review |
| promote/demote {name} | Change autonomy |
| retire {name} | Archive |

See `lifecycle.md` for full command reference.

### 9. Registry Management
- `registry.json` tracks all employees + status (active/paused/retired)
- Update registry on every lifecycle change
- Query registry to list available employees

### 10. Anti-Patterns
- ❌ Generalist employees (handles nothing well)
- ❌ No memory (forgets context)
- ❌ Instant autonomy (needs shadowing)
- ❌ Silent failures (must report blockers)
- ❌ Scope creep (reviewer refactoring = noise)
COMPATIBILITY & REFERENCES

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.