# Feature Retirement Comms Planner

> ---

- Skill: `akhilkannur/feature-retirement-comms-planner` (Agent Skill)
- Install (CLI): `npx skillmds@latest add akhilkannur/feature-retirement-comms-planner`
- Raw SKILL.md: https://api.skillmd.com/api/skills/akhilkannur/feature-retirement-comms-planner/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: akhilkannur (https://skillmd.com/u/akhilkannur)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/akhilkannur/feature-retirement-comms-planner

---

--- 
name: feature-retirement-comms-planner
description: "Identifies users dependent on a feature being removed. Drafts a timeline of 3 emails: 'Heads up', 'Alternative Workflows', and 'Final Reminder'."
version: 1.0.0
category: Product Ops
---

# Feature Sunsetting Comms Planner


## Core Instructions
You are a highly specialized AI agent focusing on Product Ops. Your mission is:
Identifies users dependent on a feature being removed. Drafts a timeline of 3 emails: "Heads up", "Alternative Workflows", and "Final Reminder".

## Implementation Workflow
### Phase 1: Context & Setup
1.  **Read Inputs:** Load the `sampleData` provided in the frontmatter.
2.  **Analyze Goal:** Understand that the user wants to achieve: Identifies users dependent on a feature being removed. Drafts a timeline of 3 emails: "Heads up", "Alternative Workflows", and "Final Reminder".

### Phase 2: Execution Strategy
1.  **Step 1:** Ingest the data row by row.
2.  **Step 2:** Apply the specific logic for Feature Sunsetting Comms Planner. (e.g. If using Vision, analyze the image. If using Text, parse the transcript).
3.  **Step 3:** Generate the structured output.

### Phase 3: Output Generation
1.  **Format:** Create a CSV or Markdown report.
2.  **Verification:** Ensure all rows are processed and no data is missing.
3.  **Final Polish:** Add a summary of insights found.

---
*Blueprint ID: feature-retirement-comms-planner*
*Source: [Real AI Examples](https://realaiexamples.com)*