sdlc-checkpoint

Persist crash-safe SDLC checkpoint state to YAML and verify resume routing.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/gleeb/ai-registry --skill sdlc-checkpoint
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sdlc-checkpoint
Source: https://github.com/gleeb/ai-registry/tree/main/systems/sdlc/skills/sdlc-checkpoint
Command: npx skills add https://github.com/gleeb/ai-registry --skill sdlc-checkpoint

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

sdlc-checkpoint prevents SDLC workflow drift by persisting crash-safe checkpoint state and providing deterministic resume routing across planning and execution hubs.

Core Features & Use Cases

  • Crash-safe checkpointing: Write-ahead updates to .sdlc/*.yaml before each sub-agent dispatch, ensuring progress can be resumed after interruptions.
  • Resume verification & routing: verify.sh cross-references checkpoint state against real on-disk artifacts (including staging-doc progress) and recommends the next action.
  • Dispatch auditing: Optional dispatch/response logging to .sdlc/dispatch-log.jsonl via dispatch-log for traceability and debugging.
  • Git-integrated story lifecycle: Coordinates branch/commit/merge boundaries for each story branch, enabling consistent continuation across machines.

Quick Start

Load the sdlc-checkpoint skill and run checkpoint.sh continue after receiving a /sdlc-continue-checkpoint command.

Frequently Asked Questions about sdlc-checkpoint

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I resume an SDLC workflow safely after a crash interrupts multi-agent task execution?

Resume verification cross-references checkpoint state against real on-disk artifacts and staging-doc progress, recommending the next action. It writes coordinator, planning, and execution YAML before dispatch to prevent workflow drift across planning and execution hubs.

What is write-ahead checkpointing for SDLC state management and when is it needed?

Crash-safe write-ahead checkpointing persists workflow state to `.sdlc/*.yaml` files before each sub-agent dispatch. It is needed when orchestrating multi-agent story planning and task execution to prevent workflow drift and enable deterministic continuation after interruptions.

How do I set up dispatch logging for SDLC orchestration to trace multi-agent handoffs?

Enable optional dispatch logging to write dispatch and response records to `.sdlc/dispatch-log.jsonl`. This provides dispatch-log correlation for deterministic continuation, traceability, and debugging across multi-agent story planning and task execution handoffs.

Does this checkpointing approach support git branch lifecycle management for story branches?

Yes, the git-integrated story lifecycle coordinates branch, commit, and merge boundaries for each story branch. This checkpointing approach enables consistent continuation of SDLC workflows and multi-agent task execution across different machines.

Can I verify staging-doc progress against checkpoint state before resuming task execution?

Yes, the `verify.sh` script cross-references checkpoint state against real on-disk artifacts, including staging-doc progress. It validates expected artifacts before resume and recommends the next action for verification-driven routing during task execution.

What are the limitations of file-based YAML checkpointing for multi-agent SDLC orchestration?

File-based YAML checkpointing limitations include reliance on local `.sdlc/*.yaml` files, requiring write-ahead updates before each sub-agent dispatch. It lacks distributed locking for concurrent multi-agent writes, making it best suited for sequential SDLC orchestration workflows.