release-planner

Generate prioritized, capacity-aligned feature lists from steering documentation.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill release-planner-ontoledgy
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: release-planner
Source: https://github.com/OntoLedgy/ol_ai_context_library/tree/main/skills/release-planner
Command: npx skills add https://github.com/OntoLedgy/ol_ai_context_library --skill release-planner-ontoledgy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Release planning is often disjointed, with product goals disconnected from actionable feature lists, stakeholder-aligned roadmaps, and tracker artifacts. This leads to scope creep, misalignment, and delayed downstream work like feature specs and backlog tasks. The release-planner skill solves this by turning approved steering documentation into a prioritized, capacity-aligned feature list, published roadmap, and pre-created tracker epics ready for immediate use.

Core Features & Use Cases

  • Capacity-aligned prioritization: Ranks candidate features using MoSCoW priority and T-shirt sizing against team capacity, with clear minimum, target, and stretch scope tiers to enforce 15% headroom and avoid overcommitment.
  • Cross-platform roadmap publishing: Automatically publishes a structured release plan page to Confluence, Notion, ADO Wiki, or local files for stakeholder review and alignment.
  • Tracker epic pre-creation: Creates empty, properly tagged epics in JIRA, Linear, Azure DevOps, or local tracker systems for each in-scope feature, so downstream skills can immediately link specs and tasks without manual setup.
  • Use Case: A product team preparing for an MVP launch can use this skill to turn steering docs into an approved feature shortlist, share a roadmap with stakeholders, and create JIRA epics for each feature so engineers can start writing specs the same day.

Quick Start

Use the release-planner skill to plan the Q3 2025 release by prioritizing features from the approved steering docs, publishing a roadmap to Confluence, and creating JIRA epics for each in-scope feature.

Frequently Asked Questions about release-planner

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

FAQPage Schema
How do I create a capacity-aligned release plan from approved steering docs?

Release planning from steering docs applies MoSCoW prioritization and T-shirt sizing to rank features against team capacity, ensuring 15% headroom and generating minimum, target, and stretch scope tiers to prevent overcommitment.

Can I automatically create JIRA epics for features in a release plan?

Tracker epic pre-creation automatically generates empty, properly tagged epics in JIRA, Linear, or Azure DevOps for each in-scope feature, enabling downstream skills to immediately link specs and tasks without manual setup.

How do I publish a release roadmap to Confluence or Notion for stakeholder review?

Roadmap publishing automatically generates a structured release plan page to Confluence, Notion, ADO Wiki, or local files, enabling immediate cross-functional stakeholder review and alignment.

What is the best way to prioritize features for an MVP launch without scope creep?

Prioritizing features for an MVP launch uses MoSCoW priority and T-shirt sizing against team capacity to create clear minimum, target, and stretch scope tiers, enforcing 15% headroom to eliminate scope creep.

Does release planning work with Azure DevOps and Linear tracker systems?

Release planning integrates with Azure DevOps, Linear, and JIRA to pre-create properly tagged feature epics, and publishes roadmaps to ADO Wiki, Confluence, Notion, or local files for cross-functional alignment.

Why does my release planning fail to align teams and delay downstream feature specs?

Disjointed release planning disconnects product goals from actionable feature lists and tracker artifacts, causing misalignment and delayed downstream work, which structured capacity-aligned prioritization and pre-created epics solve.