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OntoLedgy
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local-backlog-manager

Generate hierarchical epic, story, and task markdown files from approved feature specs.

Updated Aug 27, 2026
Search Tags:#requirements traceability#sprint planning#spec-driven development#work item creation#local backlog#filesystem tracker#ticket map generation
One-click install
npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill local-backlog-manager
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: local-backlog-manager
Source: https://github.com/OntoLedgy/ol_ai_context_library/tree/main/skills/local-backlog-manager
Command: npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill local-backlog-manager

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of creating a structured, trackable project backlog from approved feature specifications when no cloud-based tracker MCP (JIRA, Linear, Azure DevOps) is available, eliminating the need for external tracker services for teams using local filesystem-based project tracking.

Core Features & Use Cases

  • Hierarchical Work Item Generation: Creates epic, story, and task markdown files from approved tasks.md feature specs, grouped by requirement for full traceability.
  • Execution Engine Assignment: Auto-classifies tasks as simple (Codex) or complex (Claude) based on complexity rules, with user override options before publishing.
  • Automated Board and Ticket Map Generation: Produces a browsable tracker index and canonical ticket map linking tasks back to their source specs for downstream sprint planning and execution.
  • Use Case: Engineering teams using local filesystems instead of cloud trackers can automate backlog creation after spec approval, keeping all work items git-diffable and reviewable in pull requests.

Quick Start

Use the local-backlog-manager skill to convert the approved feature spec stored in documentation/specs/your-feature-name/ into a structured local filesystem backlog of epics, stories, and tasks with full requirements traceability.

Frequently Asked Questions about local-backlog-manager

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

FAQPage Schema
How do I generate a local filesystem backlog from approved feature specifications?▼

The skill creates a local filesystem backlog by parsing approved tasks.md feature specifications and generating hierarchical epic, story, and task markdown files. It groups these work items by requirement to ensure full traceability for local project tracking.

What is the best way to maintain requirements traceability without a cloud-based tracker like JIRA?▼

The best way to maintain requirements traceability without a cloud tracker is using a local backlog. The skill generates a canonical ticket map linking generated tasks back to source specs, keeping all work items git-diffable and reviewable in pull requests for audit-trail preservation.

Can I auto-classify backlog tasks for different execution engines like Codex or Claude?▼

Yes, you can auto-classify backlog tasks for execution engines like Codex or Claude. The skill applies complexity rules to automatically assign simple tasks to Codex and complex tasks to Claude, with user override options available before finalizing the backlog.

How does spec-driven development work with a filesystem tracker for sprint planning?▼

Spec-driven development with a filesystem tracker works by converting approved feature specs into structured work items. The skill produces a browsable tracker index and auto-generated board views to facilitate downstream sprint planning and task execution directly from the local backlog.

Do I need a cloud-based tracker MCP to create an audit-trail-preserved backlog?▼

No, you do not need a cloud-based tracker MCP to create an audit-trail-preserved backlog. The skill eliminates external tracker dependencies by generating work items directly on the local filesystem, keeping the entire backlog store git-diffable and reviewable in pull requests.

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