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Checkpoint Mode

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asklokesh
checkpoint-mode

Pause for review every N tasks - selective autonomy pattern

Overview

Publisherasklokesh
Repositoryloki-mode
Skill namecheckpoint-mode
Stars
1.1K
Forks
206
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by asklokesh on GitHub. Read the source before you install it.

Installation

Install the Checkpoint Mode AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/asklokesh/loki-mode/tree/main/examples/agent-skills/checkpoint-mode
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/asklokesh/loki-mode.git /tmp/loki-mode
mkdir -p .claude/skills
cp -r /tmp/loki-mode/examples/agent-skills/checkpoint-mode .claude/skills/checkpoint-mode
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Checkpoint Mode in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Checkpoint Mode on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Checkpoint Mode is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

bash
# 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
  2. Create Approval Signal

    bash
    # System writes:
    .loki/signals/CHECKPOINT_SUMMARY_2026-01-14-10-30.md
    
    # User reviews and creates:
    .loki/signals/CHECKPOINT_APPROVED
  3. Wait for Approval

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

Agent Instructions (Orchestrator)

When LOKI_AUTONOMY_MODE=checkpoint:

python
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

ModeBest ForApproval FrequencyUse Case
PerpetualOvernight buildsNeverFully automated CI/CD
CheckpointNovel projectsEvery 10 tasksLearning new domain
SupervisedCritical systemsEvery taskProduction deployments

Metrics

Track checkpoint effectiveness:

json
{
  "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

Frequently asked questions

What does the Checkpoint Mode AI skill do?

Pause for review every N tasks - selective autonomy pattern

Why use Checkpoint Mode on TypingMind?

Because you install it once and use it with any model. Checkpoint Mode is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Checkpoint Mode in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/asklokesh/loki-mode/tree/main/examples/agent-skills/checkpoint-mode. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Checkpoint Mode?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Checkpoint Mode?

As many as you like. As long as a model supports skills, you can use Checkpoint Mode with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Checkpoint Mode AI skill free?

It is published on GitHub by asklokesh. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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