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luciusrockwing

Windowed Autonomy

by luciusrockwing · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install autonomy-windowed
Description
Time-windowed autonomous task queue. Autonomy works only during specific time windows (e.g., 8 AM - 8 PM UTC), while cron jobs run overnight. Separates conce...
README (SKILL.md)

Windowed Autonomy

Transform your agent from reactive to autonomous worker during specific time windows.


Concept

The agent works autonomously only during defined time windows. Outside windows, the agent only replies HEARTBEAT_OK. Cron jobs run overnight when autonomy is disabled.

🌙 Overnight (10 PM - 8 AM UTC):  Autonomy OFF
☀️ Daytime (8 AM - 10 PM UTC):   Autonomy ON

Clear separation: Day = work on queue, Night = cron maintenance


How It Works

1. Time Windows

Define active windows in tasks/QUEUE.md:

## ⏰ Autonomy Windows

- 🌙 Overnight: 20:00 - 08:00 UTC → Autonomy OFF
- ☀️ Daytime: 08:00 - 20:00 UTC → Autonomy ON

2. Heartbeat Flow

During Active Window:

Heartbeat → Check urgent → No → Read QUEUE → Pick task → Work 15-30 min → Update QUEUE → Log

Outside Active Window:

Heartbeat → Check urgent → No → Reply "HEARTBEAT_OK" → Sleep

Urgent Override:

Heartbeat → Check urgent → YES → Work immediately (even outside window)

3. Window Transitions

Window Opens (8:00 AM):

  • Autonomous mode enabled
  • Start pulling from queue
  • Log to tasks/MODE_HISTORY.md: "Window opened"

Window Closes (8:00 PM):

  • Autonomous mode disabled
  • Wrap up current task if in progress
  • Log transition: "Window closed"
  • Switch to standby mode (HEARTBEAT_OK only)

Schedule Examples

Time Activity Mode
00:00 GitHub backup (cron) Overnight (no autonomy)
02:00 Heartbeat check Standby (HEARTBEAT_OK)
03:00 Temp cleanup (cron) Overnight (no autonomy)
08:00 Window opens ✅ Autonomy ON
09:00 Work on task Autonomy
12:00 GitHub backup (cron) Autonomy (pause for backup)
14:00 Work on task Autonomy
20:00 Window closes ❌ Autonomy OFF
23:00 Daily ops + memory (cron) Overnights (no autonomy)

Queue Structure

# Task Queue

## ⏰ Autonomy Windows
- 🌙 Overnight: 20:00 - 08:00 UTC → Autonomy OFF
- ☀️ Daytime: 08:00 - 20:00 UTC → Autonomy ON

---

## 🔴 Ready (can be picked up during windows)
- [ ] @priority:high [Task description]
- [ ] @priority:medium [Task description]

## 🟡 In Progress
- [ ] @agent: @priority:high [Task description]
  - Started: 2026-02-16 14:00 UTC

## 🔵 Blocked
- [ ] @priority:medium [Task] (needs: [what's blocking])

## ✅ Done Today
- [x] @agent: @priority:high [Task]
  - Completed: 2026-02-16 14:25 UTC

## 💡 Ideas
- [Idea for future work]

Priority System

Priority affects task selection order during windows:

Priority When to use Selection
@priority:urgent Time-sensitive, deadline \x3C 6h Pick FIRST, even outside window
@priority:high Important, deadline 24h Pick first in window
@priority:medium Normal importance Pick second in window
@priority:low Nice to have Pick last in window

Window Types

Full Day Window (Default)

Active: 8 AM - 8 PM UTC (12 hours)

Use when:

  • youris available during these hours
  • Tasks are not time-sensitive
  • Want predictable work schedule

Heartbeat frequency: Every 2 hours (6 sessions/day)

Extended Window

Active: 6 AM - 10 PM UTC (16 hours)

Use when:

  • Want more work hours
  • yourhas varied schedule

Heartbeat frequency: Every 2 hours (8 sessions/day)

Limited Window

Active: 10 AM - 6 PM UTC (8 hours)

Use when:

  • Want controlled token budget
  • yourhas focused availability

Heartbeat frequency: Every 2-3 hours (3-4 sessions/day)


Token Budget

Recommended: 4-6 sessions/day, ~5-10K tokens each = 20-60K/day

Session strategy:

Window Type Sessions/day Tokens Schedule
Full Day (12h) 6 30-60K Every 2 hours
Extended (16h) 8 40-80K Every 2 hours
Limited (8h) 4 20-40K Every 2-3 hours

When to stop:

  • Window closes (time-based)
  • Tokens remaining \x3C 5K
  • Queue empty
  • youris actively messaging (human priority)

Urgent Tasks Override

Definition: Tasks that cannot wait for window to open

Add to queue with @priority:urgent:

## 🔴 Ready
- [ ] @priority:urgent Emergency: [task description]

Behavior:

  • Autonomy works immediately, even if outside window
  • Override all other considerations
  • Complete urgent task, then check window status

Wrapping Up When Window Closes

If in middle of task when window closes:

  1. Check task progress:

    • If > 80% complete → Finish it
    • If \x3C 80% complete → Save progress, move to In Progress, stop
  2. Save state:

## 🟡 In Progress
- [ ] @agent: @priority:high [Task description]
  - Started: 2026-02-16 19:30 UTC
  - Progress at window close: Completed X section, need to do Y
  - Resume: 2026-02-17 08:00 UTC (next window)
  1. Log to tasks/MODE_HISTORY.md:
## [2026-02-16 20:00 UTC] Window Closed
Status: Task in progress (60% complete)
Action: Saved state, will resume in next window

Mode History Tracking

File: tasks/MODE_HISTORY.md

# Window Mode Transitions

## [2026-02-16 08:00 UTC] Window Opened
Mode: Daytime window
Queue state: 3 tasks ready
Expected sessions: 6

## [2026-02-16 20:00 UTC] Window Closed
Mode: Overnight (standby)
Sessions completed: 5
Tasks completed: 4
Tasks remaining: 1 (in progress, resume tomorrow)

## [2026-02-17 08:00 UTC] Window Opened
Mode: Daytime window
Resumed task in progress

Coordinating With Cron

Daytime (Autonomy ON):

  • Light cron runs fine (Ollama monitor, disk check) - no conflict
  • Heavy cron (backup) - autonomy pauses during execution

Overnight (Autonomy OFF):

  • All cron jobs run freely
  • No autonomy conflicts

Cron schedule:

Time Cron Job Autonomy Mode
Every 5 min Ollama monitor Any (low impact)
Every hour Disk check Any (low impact)
00:00 GitHub backup OFF (overnight)
03:00 Temp cleanup OFF (overnight)
08:00 Window opens ON
12:00 GitHub backup ON (pause during)
14:00 Daily ops + memory (Sun) ON (pause during)
20:00 Window closes OFF (overnight)
23:00 Daily ops + memory OFF (overnight)

GOALS.md Integration

Link queue tasks to RA's long-term goal: MONEY

Add goal references:

- [ ] @priority:high Competitor pricing analysis (GOAL: monetization strategy)
- [ ] @priority:medium Write sales email template (GOAL: improve conversion)

Work toward goals during windows:

  • Research tasks during early window (fresh energy)
  • Writing tasks during mid window (flow state)
  • Review tasks during late window (wind down)

.learnings/ Integration

After completing tasks, add findings to .learnings/:

## [LRN-20260216-001] task-completion
Task: [Task description]

Completed during: Daytime window (14:00-14:25 UTC)
Tokens used: 8K

Key findings: [summarize]

Daily Routine

Window Opens (8:00 AM)

  1. Check queue for tasks in 🔴 Ready
  2. Pick highest priority task
  3. Work 15-30 minutes
  4. Update queue (In Progress or Done)

During Window (9 AM - 8 PM)

  1. Every 2 hours: heartbeat, check queue
  2. Work on next highest priority task
  3. Update queue after completion
  4. Log progress to memory/[today].md

Window Closes (8:00 PM)

  1. Check if task in progress
  2. If yes: Save progress or finish if close
  3. Move to Done Today or keep in In Progress
  4. Log transition tasks/MODE_HISTORY.md
  5. Switch to standby (HEARTBEAT_OK only)

Overnight (8 PM - 8 AM)

  1. Every heartbeat: Check urgent only
  2. If no urgent: Reply HEARTBEAT_OK
  3. Cron jobs run freely
  4. No autonomous work

Task Output Format

## Task: [Title]

**Completed during:** [Window type] [Time range]
**Duration:** X minutes
**Tokens:** YK

### Work Done
[Describe what was accomplished]

### Output
[Attach output file or content]

### Next Steps
[What to do next - add to Ideas if task spawns follow-up]

Evolving Over Time

The "slowly evolve" approach:

This mode allows The agent to gradually take on more work:

Week 1-2:

  • Conservative: 4 sessions/day, limited window
  • Monitor performance, adjust schedule

Week 3-4:

  • Expand: 6 sessions/day, extended window if needed
  • Add more task types to queue

Month 2:

  • Optimize: Tailor window to RA's actual schedule and peak productivity times
  • Adjust based on what yourfinds valuable

Key: Start small, expand based on feedback and results.


When to Use This Skill

Use this skill when:

  • You want predictable work schedule
  • You want autonomy to work during specific hours
  • Tasks are not time-sensitive (can wait for window)
  • You want clear temporal separation between autonomy and maintenance
  • You're okay with "slowly evolving" - start small, expand over time

When NOT to Use This Skill

Do not use this skill when:

  • You want 24/7 autonomous work → Use autonomy-type-based for type-based filtering
  • Tasks are highly time-sensitive → Use urgency override or different approach
  • You want task-based separation rather than time-based → Use autonomy-type-based
  • youris awake during non-standard hours → Adjust windows to match schedule

Quick Reference

Default window: 8 AM - 8 PM UTC (adjustable) Session frequency: Every 2-3 hours during window Priority order: urgent (override) → highmediumlow Queue location: tasks/QUEUE.md


See templates/QUEUE.md for full template structure

Usage Guidance
This skill is coherent and appears to do what it says: manage a time-windowed autonomous task queue by reading and writing local task/memory files. Before installing: (1) Confirm you are comfortable with the agent having read/write access to the workspace paths named (memory/, tasks/, GOALS.md, .learnings) and that those files don't contain secrets you don't want persisted; (2) Verify how your agent runtime exposes token-usage and 'human active' signals — the skill assumes those signals exist but doesn't define how to get them; (3) Decide whether you want the 'urgent' override (allows work outside windows) and whether the agent should be allowed to edit GOALS.md or .learnings automatically; (4) Test in a conservative, limited window and review MODE_HISTORY and logs to ensure behavior matches expectations. If you want tighter control, restrict file-permission scope or add an approval step for urgent tasks and edits to goal files.
Capability Analysis
Type: OpenClaw Skill Name: autonomy-windowed Version: 1.0.0 The skill bundle provides detailed instructions for an AI agent to manage its tasks, schedule, and logging based on time windows. All file operations are directed to specific, internal markdown files within its workspace (e.g., `tasks/QUEUE.md`, `memory/YYYY-MM-DD.md`, `tasks/MODE_HISTORY.md`, `GOALS.md`, `.learnings/`). There are no instructions for data exfiltration, unauthorized execution, persistence, or other malicious activities. The instructions, while extensive, are focused on the agent's self-management and operational workflow, which is a legitimate function for an autonomous agent.
Capability Assessment
Purpose & Capability
Name/description match the actual instructions: the skill coordinates autonomous work during configured time windows and uses local queue/checkpoint files (tasks/QUEUE.md, memory/*, tasks/MODE_HISTORY.md). It does not request unrelated binaries, env vars, or external services.
Instruction Scope
Instructions direct the agent to read and write many workspace files (QUEUE.md, MODE_HISTORY.md, memory/episodic/[today].md, GOALS.md, .learnings). That is consistent with a task queue. Two points to note: (1) the SKILL assumes the agent/runtime can determine 'tokens remaining' and whether the human (RA) is actively messaging — the skill does not specify how to obtain those signals, which is a gap in the doc; (2) the agent is given discretionary authority (urgent override, choosing tasks, updating GOALS.md/.learnings), which is functional but grants broad action within the workspace.
Install Mechanism
Instruction-only skill with no install spec and no downloaded code. Nothing is written to disk by an installer — the only writes are the runtime file operations the instructions describe.
Credentials
The skill requests no environment variables or credentials. The only privileges it needs are read/write access to project workspace files (task and memory files), which is proportionate to its stated purpose.
Persistence & Privilege
always: false and the skill does not request persistent platform-level privileges or modifications to other skills. It does instruct writing to its own workspace files (mode history, memory files), which is expected for this kind of skill.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install autonomy-windowed
  3. After installation, invoke the skill by name or use /autonomy-windowed
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release - time-windowed autonomous task queue system. Works only during defined windows (e.g., 8 AM - 8 PM UTC). Day = autonomy, night = cron maintenance. Predictable schedule with controlled token budget.
Metadata
Slug autonomy-windowed
Version 1.0.0
License
All-time Installs 3
Active Installs 3
Total Versions 1
Frequently Asked Questions

What is Windowed Autonomy?

Time-windowed autonomous task queue. Autonomy works only during specific time windows (e.g., 8 AM - 8 PM UTC), while cron jobs run overnight. Separates conce... It is an AI Agent Skill for Claude Code / OpenClaw, with 705 downloads so far.

How do I install Windowed Autonomy?

Run "/install autonomy-windowed" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Windowed Autonomy free?

Yes, Windowed Autonomy is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Windowed Autonomy support?

Windowed Autonomy is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Windowed Autonomy?

It is built and maintained by luciusrockwing (@luciusrockwing); the current version is v1.0.0.

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