Agent Autonomy Primitives
Turn any AI agent into a self-directing worker using five composable primitives: typed memory, task files, project grouping, template schemas, and heartbeat loops.
Prerequisites
npm install -g clawvault
clawvault init
The Five Primitives
1. Typed Memory
Every memory has a type. The type determines where it lives and how it's retrieved.
| Type | Directory | When to Use |
|---|
decision | decisions/ | Recording a choice with rationale |
lesson | lessons/ | Something learned from experience |
person | people/ | Contact info, relationship context |
commitment | commitments/ | Promise made, deliverable owed |
preference | preferences/ | How someone likes things done |
fact | inbox/ | Raw information to file later |
project | projects/ | Workstream with goals and status |
Store with type:
clawvault remember decision "Chose Resend over SendGrid" --content "Lower cost, better DX, webhook support"
clawvault remember lesson "LLMs rewrite keywords during compression" --content "Always post-process with regex"
Rule: If you know WHAT KIND of thing it is, use the right command. Dumping everything into daily notes defeats retrieval later.
2. Task Primitives
A task is a markdown file with YAML frontmatter in tasks/:
---
status: open
priority: high
owner: your-agent-name
project: my-project
due: 2026-03-01
tags: [infrastructure, deploy]
estimate: 2h
---
# Deploy API to production
## Context
Server provisioned. Need Dockerfile fix.
## Next Steps
- Fix binding to 0.0.0.0
- Add health endpoint
- Push and verify
Create tasks:
clawvault task add "Deploy API to production" \
--priority high \
--owner my-agent \
--project my-project \
--due 2026-03-01 \
--tags "infrastructure,deploy"
Update status:
clawvault task update deploy-api-to-production --status in-progress
clawvault task done deploy-api-to-production --reason "Deployed, health check passing"
Statuses: open → in-progress → done (or blocked)
Priorities: critical > high > medium > low
3. Project Grouping
Projects group related tasks with metadata:
clawvault project add "Outbound Engine" \
--owner pedro \
--client versatly \
--tags "gtm,sales" \
--deadline 2026-03-15
Tasks reference projects via the project field. Filter tasks by project:
clawvault task list --project outbound-engine
4. Template Schemas
Templates are YAML schema definitions that control what fields exist on every primitive. They live in templates/ in your vault.
See references/template-customization.md for full customization guide.
Key points:
- Vault templates override builtins — drop a
task.md in templates/ to change the schema
- Add fields (e.g.,
sprint, effort, client) by editing the template
- Remove fields you don't need
- Change defaults (e.g., default priority =
high)
- Validation is advisory — warns but never blocks
5. Heartbeat Loop
The heartbeat is the autonomy mechanism. Wire it into your agent's periodic wake cycle.
Every heartbeat (e.g., every 30 minutes):
1. clawvault task list --owner <agent-name> --status open
2. Sort by: priority (critical first), then due date (soonest first)
3. Pick the highest-impact task executable RIGHT NOW
4. Execute it
5. On completion: clawvault task done <slug> --reason "what was done"
6. On blocker: clawvault task update <slug> --status blocked --blocked-by "reason"
7. If new work discovered: clawvault task add "new task" --priority <p> --project <proj>
8. If lesson learned: clawvault remember lesson "what happened"
9. Go back to sleep
Implementation for OpenClaw agents:
Add to your HEARTBEAT.md:
## Task-Driven Autonomy
Every heartbeat:
1. `clawvault task list --owner <your-name> --status open` → your work queue
2. Sort by priority + due date
3. Pick highest-impact task you can execute NOW
4. Work it. Update status. Mark done. Report.
5. Check for tasks due within 24h — those get priority
For cron-based agents, schedule a recurring job:
Schedule: every 30 minutes
Action: Read task queue, pick highest priority, execute, report
Composing Primitives into Autonomy
The power is in composition, not any single primitive:
Wake → Read memory → Check tasks → Execute → Learn → Update memory → Sleep
↑ |
└──────────────────────────────────────┘
Each cycle compounds:
- Memory feeds context into task execution (decisions, lessons, preferences inform how work gets done)
- Task execution generates new memories (lessons learned, decisions made, commitments created)
- Lessons improve future execution (mistakes aren't repeated)
- Wiki-links (
[[entity-name]]) build a knowledge graph across all files
- Projects provide scope boundaries so the agent doesn't drift
Adapting to Your Setup
See references/adaptation-guide.md for detailed patterns on:
- Wiring primitives into existing agent frameworks (OpenClaw, LangChain, CrewAI, custom)
- Choosing which primitives to adopt (start minimal, add as needed)
- Multi-agent collaboration through shared vaults
- Migrating from other memory systems
Quick Start: Zero to Autonomous in 5 Minutes
# 1. Install and init
npm install -g clawvault
clawvault init
# 2. Create your first project
clawvault project add "My Project" --owner my-agent
# 3. Create tasks
clawvault task add "Set up monitoring" --priority high --owner my-agent --project my-project
clawvault task add "Write API docs" --priority medium --owner my-agent --project my-project
# 4. Wire into heartbeat (add to HEARTBEAT.md or cron)
# "Every 30min: clawvault task list --owner my-agent --status open, pick top task, execute"
# 5. Start working
clawvault task update set-up-monitoring --status in-progress
# ... do the work ...
clawvault task done set-up-monitoring --reason "Prometheus + Grafana configured"
clawvault remember lesson "UptimeRobot free tier only checks every 5min" --content "Use Better Stack for <1min checks"
Anti-Patterns
| Don't | Do Instead |
|---|
| Store everything in one big memory file | Use typed memory — decisions/, lessons/, people/ |
| Create tasks without owner/project | Always set --owner and --project |
| Ask "what should I work on?" | Read your task queue and decide |
| Forget lessons after learning them | clawvault remember lesson immediately |
| Skip marking tasks done | Always task done --reason — the ledger tracks transitions |
| Create tasks for vague ideas | Put ideas in backlog/, promote to tasks/ when ready |
| Modify template schemas constantly | Stabilize schemas early — field renames break existing files |
Obsidian Integration
Because everything is markdown + YAML frontmatter, Obsidian renders your agent's workspace as a human-readable dashboard:
- Kanban board — open
all-tasks.base in Obsidian Bases, drag between status columns
- Blocked view —
blocked.base shows what needs human input
- By owner —
by-owner.base shows what each agent is working on
- By project —
by-project.base scopes views per workstream
The same file is both the agent's data structure AND the human's UI. No sync layer needed.
