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.