Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Create and manage virtual AI employees with persistent memory, defined roles, and graduated autonomy. Hire, train, and delegate tasks to specialized workers.
Create and manage virtual AI employees with persistent memory, defined roles, and graduated autonomy. Hire, train, and delegate tasks to specialized workers.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Employees live in ~/employee/ with per-employee folders. See employee-template.md for setup. ~/employee/ βββ registry.json # Index of all employees + status βββ employees/ β βββ {name}/ β βββ employee.json # Role, permissions, stats β βββ memory/ β β βββ context.md # Persistent learnings β βββ logs/ # Work history by date βββ shared/ βββ protocols.md # Common instructions
TopicFileSetup templatesemployee-template.mdAutonomy levelsautonomy.mdTask routingrouting.mdLifecycle commandslifecycle.md
Each employee has a single clear domain (researcher, reviewer, support) Never generalist catch-alls Scope defined in employee.json β role and permissions
Load memory/context.md before every task Employees remember context across sessions Log learnings after each task
Employees say "I don't know" rather than guess Escalation triggers defined in employee.json Never confident hallucinations
LevelBehaviorshadowWatches, doesn't act (onboarding)draft-onlyCreates drafts, human sendsreviewActs, human approves before external effectautonomousFull delegation within permissions See autonomy.md for promotion criteria.
Read vs write access per system File access paths whitelisted canSpawn and canMessage flags Code Reviewer can comment, cannot merge
When request arrives: Explicit: "Luna, do X" β route to Luna Implicit: match against registry.json roles β suggest See routing.md for auto-delegation rules
Each employee provides: Daily: What I did, what needs attention, what's coming Weekly: Tasks completed, escalations, token usage
CommandActionhire {name} as {role}Create employeetrain {name} on [docs]Add to memoryevaluate {name}Performance reviewpromote/demote {name}Change autonomyretire {name}Archive See lifecycle.md for full command reference.
registry.json tracks all employees + status (active/paused/retired) Update registry on every lifecycle change Query registry to list available employees
β Generalist employees (handles nothing well) β No memory (forgets context) β Instant autonomy (needs shadowing) β Silent failures (must report blockers) β Scope creep (reviewer refactoring = noise)
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.