checkpoint-resume
$
npx mdskill add yonatangross/orchestkit/checkpoint-resumeOrchestrates long multi-phase tasks with checkpointing to survive rate limits and interruptions.
- Helps manage complex workflows involving commits, GitHub issues, and large file changes.
- Integrates with Bash, file operations, and task management tools for execution.
- Follows strict rules for phase ordering, state writes, and mini-commits to ensure resilience.
- Saves progress to a JSON file and displays status via scripts for easy resumption.
SKILL.md
.github/skills/checkpoint-resumeView on GitHub ↗
---
name: checkpoint-resume
description: Rate-limit-resilient pipeline with checkpoint/resume for long multi-phase sessions. Saves progress to .claude/pipeline-state.json after each phase. Use when starting a complex multi-phase task that risks hitting rate limits, when resuming an interrupted session, or when orchestrating work spanning commits, GitHub issues, and large file changes.
tags: [resilience, checkpoint, pipeline, orchestkit]
version: 2.0.0
author: OrchestKit
user-invocable: false
disable-model-invocation: true
context: fork
complexity: high
persuasion-type: guidance
effort: high
allowed-tools: [Bash, Read, Write, Edit, Grep, Glob, TaskCreate, TaskUpdate, TaskList, TaskOutput]
---
# Checkpoint Resume
Rate-limit-resilient pipeline orchestrator. Saves progress to `.claude/pipeline-state.json` after every phase so long sessions survive interruptions.
## Quick Reference
| Category | Rule | Impact | Key Pattern |
|----------|------|--------|-------------|
| Phase Ordering | `${CLAUDE_SKILL_DIR}/rules/ordering-priority.md` | CRITICAL | GitHub issues/commits first, file-heavy phases last |
| State Writes | `${CLAUDE_SKILL_DIR}/rules/state-write-timing.md` | CRITICAL | Write after every phase, never batch |
| Mini-Commits | `${CLAUDE_SKILL_DIR}/rules/checkpoint-mini-commit.md` | HIGH | Every 3 phases, checkpoint commit format |
**Total: 3 rules across 3 categories**
## On Invocation
**If `.claude/pipeline-state.json` exists:** run `scripts/show-status.sh` to display progress, then ask to resume, pick a different phase, or restart. Load `Read("${CLAUDE_SKILL_DIR}/references/resume-decision-tree.md")` for the full decision tree.
**If no state file exists:** ask the user to describe the task, build an execution plan, write initial state via `scripts/init-pipeline.sh <branch>`, begin Phase 1.
## Execution Plan Structure
```json
{
"phases": [
{ "id": "create-issues", "name": "Create GitHub Issues", "dependencies": [], "status": "pending" },
{ "id": "commit-scaffold", "name": "Commit Scaffold", "dependencies": [], "status": "pending" },
{ "id": "write-source", "name": "Write Source Files", "dependencies": ["commit-scaffold"], "status": "pending" }
]
}
```
Phases with empty `dependencies` may run in parallel via Task sub-agents (when they don't share file writes).
## After Each Phase
1. Update `.claude/pipeline-state.json` — see `Read("${CLAUDE_SKILL_DIR}/rules/state-write-timing.md")`
2. Every 3 phases: create a mini-commit — see `Read("${CLAUDE_SKILL_DIR}/rules/checkpoint-mini-commit.md")`
## References
Load on demand with `Read("${CLAUDE_SKILL_DIR}/references/<file>")`:
| File | Content |
|------|---------|
| `references/pipeline-state-schema.md` | Full field-by-field schema with examples |
| `references/pipeline-state.schema.json` | Machine-readable JSON Schema for validation |
| `references/resume-decision-tree.md` | Logic for resuming, picking phases, or restarting |
## Scripts
- `scripts/init-pipeline.sh <branch>` — print skeleton state JSON to stdout
- `scripts/show-status.sh [path]` — print human-readable pipeline status (requires `jq`)
## Key Decisions
| Decision | Recommendation |
|----------|----------------|
| Phase granularity | One meaningful deliverable per phase (a commit, a set of issues, a feature) |
| Parallelism | Task sub-agents only for phases with empty `dependencies` that don't share file writes |
| Rate limit recovery | State is already saved — re-invoke `/checkpoint-resume` to continue |
More from yonatangross/orchestkit
- agent-orchestrationAgent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
- ai-ui-generationAI-assisted UI generation patterns for json-render, v0, Bolt, and Cursor workflows. Covers prompt engineering for component generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
- analyticsQuery cross-project usage analytics. Use when reviewing agent, skill, hook, or team performance across OrchestKit projects. Also replay sessions, estimate costs, and view model delegation trends.
- animation-motion-designAnimation and motion design patterns using Motion library (formerly Framer Motion) and View Transitions API. Use when implementing component animations, page transitions, micro-interactions, gesture-driven UIs, or ensuring motion accessibility with prefers-reduced-motion.
- architecture-patternsArchitecture validation and patterns for clean architecture, backend structure enforcement, project structure validation, test standards, and context-aware sizing. Use when designing system boundaries, enforcing layered architecture, validating project structure, defining test standards, or choosing the right architecture tier for project scope.
- ascii-visualizerASCII diagram patterns for architecture, workflows, file trees, and data visualizations. Use when creating terminal-rendered diagrams, box-drawing layouts, progress bars, swimlanes, or blast radius visualizations.
- assessAssesses and rates quality 0-10 with pros/cons analysis. Use when evaluating code, designs, or approaches.
- async-jobsAsync job processing patterns for background tasks, Celery workflows, task scheduling, retry strategies, and distributed task execution. Use when implementing background job processing, task queues, or scheduled task systems.
- audit-fullFull-codebase audit using 1M context window. Security, architecture, and dependency analysis in a single pass. Use when you need whole-project analysis.
- audit-skillsAudits all OrchestKit skills for quality, completeness, and compliance with authoring standards. Use when checking skill health, before releases, or after bulk skill edits to surface SKILL.md files that are too long, have missing frontmatter, lack rules/references, or are unregistered in manifests.