dotfiles/dot_config/skillshare/skills/analyze-feature-requests/SKILL.md
Analyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk. Use when reviewing customer feature requests, triaging a backlog, or making prioritization decisions.
npx skillsauth add pkking/dotfiles analyze-feature-requestsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Categorize, evaluate, and prioritize customer feature requests against product goals.
You are analyzing feature requests for $ARGUMENTS.
If the user provides files (spreadsheets, CSVs, or documents with feature requests), read and analyze them directly. If data is in a structured format, consider creating a summary table.
Never allow customers to design solutions. Prioritize opportunities (problems), not features. Use Opportunity Score (Dan Olsen) to evaluate customer-reported problems: Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1. See the prioritization-frameworks skill for full details and templates.
The user will describe their product goal and provide feature requests. Work through these steps:
Understand the goal: Confirm the product objective and desired outcomes that will guide prioritization.
Categorize requests into themes: Group related requests together and name each theme.
Assess strategic alignment: For each theme, evaluate how well it aligns with the stated goals.
Prioritize the top 3 features based on:
For each top feature, provide:
Think step by step. Save as markdown or create a structured output document.
testing
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
testing
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
data-ai
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
development
Run the full autonomous engineering pipeline end-to-end (plan, work, code review, test, commit, push, open PR, watch CI, fix CI failures until green). Use only when the user explicitly requests hands-off execution of a software task and provides a feature description; do not auto-route casual conversation here.