How does this skill update my project wiki?

It analyzes the 'state.json' and 'decisions.md' files to identify new patterns, then updates files in your 'context/' folder to ensure the AI's future knowledge reflects the latest changes.

What happens if a workflow is blocked or failed?

The skill is designed not to archive failed or blocked workflows automatically, keeping them in the active directory for further investigation until resolved.

Can I archive a workflow manually?

Yes, while it typically runs automatically at the final step of a workflow, you can trigger it at any time by telling Claude to 'archive this workflow'.

Does it automatically close Jira tickets?

Yes, if configured with Atlassian MCP tools, it transitions stories to their final status (e.g., 'Done' or 'Closed') and adds a summary comment to the ticket.

What happens to my files during the archival process?

Files are moved from the '.ai-dev-team/workflow/active/' directory to the 'archive/' directory with a date-stamped prefix. No data is deleted; it is simply reorganized for long-term history.

Workflow Archival & Knowledge Sync

Name: Workflow Archival & Knowledge Sync
Author: marcel-Ngan

bymarcel-Ngan

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生产力与工作流

Automates the closure of development tasks by archiving project folders, updating local documentation, and synchronizing status with Jira.

关于

The Workflow Archival skill streamlines the transition from active development to project completion by formalizing the storage of historical data. It automatically moves completed task folders to a date-stamped archive, extracts valuable architectural patterns and pitfalls into a project wiki, and performs a final batch sync with Jira to ensure team visibility. This process ensures that every AI-driven development cycle leaves behind a clean workspace and a rich trail of documentation for future agents and human collaborators.

主要功能

Automated folder migration from active to archival directories with date-based naming
Bidirectional Jira synchronization for story transitions, decision logs, and comments
Context preservation by copying story history into a permanent project reference folder
Intelligent wiki updates that capture new architectural patterns and solution summaries
Metric extraction from workflow metadata to track development velocity and iteration counts
1 GitHub stars

使用场景

Updating external project management tools with final implementation details and completion metrics
Finalizing a feature EPIC and moving all local development artifacts to long-term storage
Extracting lessons learned from a complex debugging workflow into the project's solution summary

关于

主要功能

Automated folder migration from active to archival directories with date-based naming
Bidirectional Jira synchronization for story transitions, decision logs, and comments
Context preservation by copying story history into a permanent project reference folder
Intelligent wiki updates that capture new architectural patterns and solution summaries
Metric extraction from workflow metadata to track development velocity and iteration counts
1 GitHub stars

使用场景

Updating external project management tools with final implementation details and completion metrics
Finalizing a feature EPIC and moving all local development artifacts to long-term storage
Extracting lessons learned from a complex debugging workflow into the project's solution summary