smithery.ai

checkpoint-mode

Pause for review every N tasks - selective autonomy pattern

First seen Mar 20, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,357 B
  • docs SUMMARY.md 82 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Checkpoint Mode Skill

Overview

Implements selective autonomy - shorter bursts of autonomous work with feedback loops.

Research Source: "Use Agents or Be Left Behind" by Tim Dettmers


Philosophy

"More than 90% of code should be written by agents, but iteratively design systems with shorter bursts of autonomy with feedback loops."
— Tim Dettmers, 2026

Problem with Perpetual Autonomy:

  • Can waste resources on wrong approach
  • No opportunity for course correction
  • User feels disconnected from progress

Solution:

  • Pause after N tasks or M minutes
  • Generate summary of accomplishments
  • Wait for explicit approval to continue

When to Use

Use Checkpoint Mode For:

  • Novel projects where approach may need adjustment
  • High-cost operations (expensive API calls, cloud resources)
  • Learning phases where user wants to guide direction
  • Regulated environments requiring audit trail

Use Perpetual Mode For:

  • Well-defined PRDs with clear requirements
  • Established patterns with high confidence
  • Overnight builds where interruption isn't desired
  • CI/CD pipelines requiring full automation

Configuration

# Enable checkpoint mode
LOKI_AUTONOMY_MODE=checkpoint

# Pause frequency
LOKI_CHECKPOINT_FREQUENCY=10  # tasks
LOKI_CHECKPOINT_TIME=60  # minutes

# Always pause after these phases
LOKI_CHECKPOINT_PHASES="architecture,deployment"

Checkpoint Workflow

[Work on 10 tasks] → [Pause] → [Generate Summary] → [Wait for Approval]
                                                           ↓
                                              [User reviews and approves]
                                                           ↓
                                                    [Resume work]

On Checkpoint:

  1. Generate Summary

```markdown # Checkpoint Summary

## Tasks Completed (10) - Implemented POST /api/todos endpoint - Added unit tests (95% coverage) - Set up CI/CD pipeline - ...

## Next Actions - Deploy to staging - Run integration tests - Security audit

## Resources Used - 15 minutes elapsed - 3 Haiku agents, 2 Sonnet agents - Estimated cost: $0.45 ```

  1. Create Approval Signal

```bash # System writes: .loki/signals/CHECKPOINTSUMMARY2026-01-14-10-30.md

# User reviews and creates: .loki/signals/CHECKPOINT_APPROVED ```

  1. Wait for Approval

- Orchestrator pauses execution - Monitors for approval signal - Resumes when signal detected


Agent Instructions (Orchestrator)

When LOKIAUTONOMYMODE=checkpoint:

completed_tasks = load_completed_tasks()
tasks_since_checkpoint = completed_tasks - last_checkpoint_count

if tasks_since_checkpoint >= CHECKPOINT_FREQUENCY:
    # Pause and generate summary
    summary = generate_checkpoint_summary()
    write_signal("CHECKPOINT_SUMMARY", summary)

    # Wait for approval
    log_info("Waiting for checkpoint approval...")
    while not signal_exists("CHECKPOINT_APPROVED"):
        sleep(5)

    # Resume work
    remove_signal("CHECKPOINT_APPROVED")
    log_info("Checkpoint approved. Resuming work...")
    last_checkpoint_count = completed_tasks

Comparison with Other Modes

Mode Best For Approval Frequency Use Case
Perpetual Overnight builds Never Fully automated CI/CD
Checkpoint Novel projects Every 10 tasks Learning new domain
Supervised Critical systems Every task Production deployments

Metrics

Track checkpoint effectiveness:

{
  "checkpoint_id": "cp-2026-01-14-001",
  "tasks_completed": 10,
  "time_elapsed_minutes": 15,
  "approval_time_seconds": 45,
  "course_corrections": 0,
  "user_satisfaction": "approved_without_changes"
}

Storage: .loki/metrics/checkpoint-mode/


References


Version: 1.0.0