feature-results

Generate a structured Markdown post-launch feature results document.

20|4|Updated Oct 4, 2025
One-click install
npx skills add https://github.com/coalesce-labs/catalyst --skill feature-results
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: feature-results
Source: https://github.com/coalesce-labs/catalyst/tree/main/plugins/pm/skills/feature-results
Command: npx skills add https://github.com/coalesce-labs/catalyst --skill feature-results

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-launch analysis and results documentation to capture what shipped and what we learned.

Core Features & Use Cases

  • Consolidates goals, metrics, RCA, segment insights, and next steps into a single post-launch results document.
  • Pulls original hypotheses and targets from PRDs and MCPs to compare planned vs actual outcomes.
  • Generates structured outputs (executive summary, results, calibration, and follow-up actions) suitable for executive updates and team alignment.

Quick Start

Run the feature-results workflow after a feature ships: provide the feature name, ship date, original hypothesis, and actual results to generate the comprehensive results document.

Frequently Asked Questions about feature-results

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

FAQPage Schema
How do I automate post-launch analysis and document feature results after a release?

Automate post-launch analysis by running the feature-results workflow with the feature name, ship date, original hypothesis, and actual results. It consolidates goals, metrics, root-cause-analysis, and learnings into a structured Markdown report.

What should be included in a post-launch feature results document?

A comprehensive feature results document includes an executive summary, original hypothesis, primary metrics, segment breakdowns, root-cause-analysis, calibration, and next steps. This structure captures what shipped and what was learned for stakeholder communication.

How do I compare planned outcomes versus actual results after a feature launch?

Compare planned versus actual results by pulling original hypotheses and targets from PRDs and MCPs. The feature-results workflow matches these inputs against actual post-launch metrics to generate a calibration analysis within the final Markdown report.

Can I generate an executive summary and stakeholder update from post-launch metrics?

Yes, you can generate an executive summary and stakeholder update by feeding post-launch metrics into the feature-results workflow. It outputs structured Markdown artifacts containing results, analysis, and follow-up actions suitable for team alignment.

Do I need a PRD or MCP connection to perform segment analysis after a launch?

No, a PRD or MCP connection is not strictly required to perform segment analysis, but connecting them allows the feature-results workflow to automatically pull original hypotheses and targets, enriching the post-launch calibration and root-cause-analysis.

What is the best way to consolidate root-cause-analysis and next steps for a shipped feature?

The best way to consolidate root-cause-analysis and next steps is using a structured post-launch workflow. It captures segment insights and follow-up actions, outputting a comprehensive Markdown results document that aligns stakeholders on what was learned.