Claude Skills by luokai0

Acceptance criteria define the observable behavior that must be true for a story or feature to be considered done. This skill turns feature context into concise, testable Given/When/Then scenarios that engineers and QA can verify without guessing intent.

An edge cases document systematically catalogs the unusual, boundary, and error scenarios for a feature. While happy-path flows are typically well-specified, edge cases often get discovered in production — causing bugs, poor user experience, and support burden. Documenting edge cases upfront ensures engineering handles them intentionally and QA knows what to test.

A launch checklist is a comprehensive verification document that ensures all functions are ready before releasing a feature or product. It coordinates across engineering, QA, design, marketing, support, legal, and operations to prevent launch-day surprises. Good launch checklists surface blockers early and create shared accountability for launch readiness.

A Product Requirements Document is the primary specification artifact that communicates what to build and why. It bridges the gap between problem understanding and engineering implementation by providing clear requirements, success criteria, and scope boundaries. A good PRD enables engineering to build the right thing while maintaining flexibility on implementation details.

Release notes communicate product changes to users in a way that highlights value and builds excitement. Unlike changelogs (which document what changed technically), release notes translate changes into user benefits. Good release notes help users discover new capabilities, understand improvements, and trust that issues are being addressed.

User stories are concise descriptions of functionality from the user's perspective. They capture who needs something, what they need, and why — without prescribing how to build it. Good user stories enable teams to break large features into estimable, deliverable increments while maintaining focus on user value.

An Architecture Decision Record documents a significant technical decision along with its context and consequences. ADRs capture the "why" behind architectural choices so future team members understand the reasoning — especially important when they question why something was done a particular way. This skill follows Michael Nygard's lightweight ADR format.

A design rationale document captures the "why" behind design decisions—the context, constraints, alternatives considered, and reasoning that led to a particular solution. While designs themselves show what was built, rationale documents preserve institutional knowledge about why it was built that way.

A solution brief is a concise, one-page document that communicates the proposed solution to a problem. It serves as the bridge between problem understanding and detailed specification, providing enough context for stakeholders to align on the approach without getting lost in implementation details. The one-page constraint forces clarity and prioritization.

A spike summary documents the results of a time-boxed exploration — a focused investigation to reduce uncertainty before committing to implementation. Spikes answer specific questions like "Can we integrate with this API?" or "Is this technology viable for our use case?" The summary captures findings so the team can make informed decisions without the spike participants needing to repeat explanations.

A competitive analysis provides structured insight into the competitive landscape, helping product teams understand where they stand relative to alternatives and identify opportunities for differentiation. Rather than exhaustively cataloging every competitor, an effective analysis focuses on actionable insights that inform product strategy.

An interview synthesis transforms raw user research data into structured insights that drive product decisions. Rather than simply listing what participants said, a good synthesis identifies patterns across conversations, connects observations to underlying user needs, and translates findings into actionable recommendations.

A stakeholder summary documents the people and groups who have interest in or influence over a project, capturing their needs, concerns, and relationships. Effective stakeholder management often determines project success more than technical execution, making this document essential for navigating organizational complexity.

A lessons log entry captures significant learning from projects, incidents, or experiences in a format that's useful to future teams who weren't there. Unlike retrospectives (which focus on team improvement), lessons logs focus on organizational knowledge that transcends individual teams—patterns, anti-patterns, and hard-won wisdom.

A pivot decision document captures the analysis and rationale behind a strategic direction change—or the decision to stay the course. Based on the Lean Startup concept of "pivot or persevere," this artifact ensures major strategic decisions are made with evidence, communicated clearly, and preserved for organizational learning.

Refinement notes capture the outcomes of backlog refinement (grooming) sessions—what was discussed, what was estimated, and what decisions were made. They serve as a quick reference for team members who missed the session and a historical record of how stories evolved from idea to ready-for-sprint.

A retrospective is a structured reflection that helps teams learn from their experiences and continuously improve. By regularly examining what went well, what didn't, and what to change, teams build a culture of learning and adaptation. The value isn't just in the discussion—it's in the documented actions and follow-through.

A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.

An experiment design document defines all parameters needed to run a rigorous A/B test or controlled experiment. It ensures the team aligns on what you're testing, how you'll measure success, and how long to run the test before drawing conclusions. Good experiment design prevents common pitfalls: underpowered tests, unclear success criteria, and decisions based on noise rather than signal.

An experiment results document captures what happened when you tested a hypothesis, including statistical outcomes, segment analysis, learnings, and clear recommendations. Good results documentation turns individual experiments into organizational knowledge that improves future decision-making.

An instrumentation spec defines what analytics events to track, when to fire them, and what properties to include. It serves as a contract between product and engineering, ensuring consistent data collection that enables accurate measurement. Good instrumentation specs prevent the "we can't answer that question because we didn't track it" problem.

A hypothesis is a testable prediction about how a change will affect user behavior or business outcomes. It transforms assumptions into explicit statements that can be validated or invalidated through experimentation. Well-formed hypotheses prevent teams from building features based on untested beliefs and create shared understanding of what success looks like.

A Jobs to be Done (JTBD) canvas captures the complete picture of why customers "hire" products to make progress in their lives. Based on Clayton Christensen's framework, JTBD goes beyond features and demographics to understand the underlying motivations—functional, emotional, and social—that drive customer behavior.

An Opportunity Solution Tree (OST) is a visual framework for product discovery that connects business outcomes to customer opportunities and potential solutions. Developed by Teresa Torres, it prevents the common trap of jumping straight to solutions by ensuring every feature idea traces back to a customer need and measurable outcome.

A problem statement is a concise document that frames the problem you're solving, articulates the impact on users and the business, and defines clear success criteria. It serves as the foundation for all subsequent product work by ensuring alignment on *what* problem to solve before jumping to *how* to solve it.

Acceptance criteria define the observable behavior that must be true for a story or feature to be considered done. This skill turns feature context into concise, testable Given/When/Then scenarios that engineers and QA can verify without guessing intent.

An edge cases document systematically catalogs the unusual, boundary, and error scenarios for a feature. While happy-path flows are typically well-specified, edge cases often get discovered in production — causing bugs, poor user experience, and support burden. Documenting edge cases upfront ensures engineering handles them intentionally and QA knows what to test.

A launch checklist is a comprehensive verification document that ensures all functions are ready before releasing a feature or product. It coordinates across engineering, QA, design, marketing, support, legal, and operations to prevent launch-day surprises. Good launch checklists surface blockers early and create shared accountability for launch readiness.

A Product Requirements Document is the primary specification artifact that communicates what to build and why. It bridges the gap between problem understanding and engineering implementation by providing clear requirements, success criteria, and scope boundaries. A good PRD enables engineering to build the right thing while maintaining flexibility on implementation details.

Release notes communicate product changes to users in a way that highlights value and builds excitement. Unlike changelogs (which document what changed technically), release notes translate changes into user benefits. Good release notes help users discover new capabilities, understand improvements, and trust that issues are being addressed.

User stories are concise descriptions of functionality from the user's perspective. They capture who needs something, what they need, and why — without prescribing how to build it. Good user stories enable teams to break large features into estimable, deliverable increments while maintaining focus on user value.

An Architecture Decision Record documents a significant technical decision along with its context and consequences. ADRs capture the "why" behind architectural choices so future team members understand the reasoning — especially important when they question why something was done a particular way. This skill follows Michael Nygard's lightweight ADR format.

A design rationale document captures the "why" behind design decisions—the context, constraints, alternatives considered, and reasoning that led to a particular solution. While designs themselves show what was built, rationale documents preserve institutional knowledge about why it was built that way.

A solution brief is a concise, one-page document that communicates the proposed solution to a problem. It serves as the bridge between problem understanding and detailed specification, providing enough context for stakeholders to align on the approach without getting lost in implementation details. The one-page constraint forces clarity and prioritization.

A spike summary documents the results of a time-boxed exploration — a focused investigation to reduce uncertainty before committing to implementation. Spikes answer specific questions like "Can we integrate with this API?" or "Is this technology viable for our use case?" The summary captures findings so the team can make informed decisions without the spike participants needing to repeat explanations.

A competitive analysis provides structured insight into the competitive landscape, helping product teams understand where they stand relative to alternatives and identify opportunities for differentiation. Rather than exhaustively cataloging every competitor, an effective analysis focuses on actionable insights that inform product strategy.

An interview synthesis transforms raw user research data into structured insights that drive product decisions. Rather than simply listing what participants said, a good synthesis identifies patterns across conversations, connects observations to underlying user needs, and translates findings into actionable recommendations.

A stakeholder summary documents the people and groups who have interest in or influence over a project, capturing their needs, concerns, and relationships. Effective stakeholder management often determines project success more than technical execution, making this document essential for navigating organizational complexity.

This skill produces decision-usable personas from one canonical template pack.

A lessons log entry captures significant learning from projects, incidents, or experiences in a format that's useful to future teams who weren't there. Unlike retrospectives (which focus on team improvement), lessons logs focus on organizational knowledge that transcends individual teams—patterns, anti-patterns, and hard-won wisdom.

A pivot decision document captures the analysis and rationale behind a strategic direction change—or the decision to stay the course. Based on the Lean Startup concept of "pivot or persevere," this artifact ensures major strategic decisions are made with evidence, communicated clearly, and preserved for organizational learning.

Refinement notes capture the outcomes of backlog refinement (grooming) sessions—what was discussed, what was estimated, and what decisions were made. They serve as a quick reference for team members who missed the session and a historical record of how stories evolved from idea to ready-for-sprint.

A retrospective is a structured reflection that helps teams learn from their experiences and continuously improve. By regularly examining what went well, what didn't, and what to change, teams build a culture of learning and adaptation. The value isn't just in the discussion—it's in the documented actions and follow-through.

A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.

An experiment design document defines all parameters needed to run a rigorous A/B test or controlled experiment. It ensures the team aligns on what you're testing, how you'll measure success, and how long to run the test before drawing conclusions. Good experiment design prevents common pitfalls: underpowered tests, unclear success criteria, and decisions based on noise rather than signal.

An experiment results document captures what happened when you tested a hypothesis, including statistical outcomes, segment analysis, learnings, and clear recommendations. Good results documentation turns individual experiments into organizational knowledge that improves future decision-making.

An instrumentation spec defines what analytics events to track, when to fire them, and what properties to include. It serves as a contract between product and engineering, ensuring consistent data collection that enables accurate measurement. Good instrumentation specs prevent the "we can't answer that question because we didn't track it" problem.

This skill creates new PM skills for the pm-skills library. It produces a Skill Implementation Packet — a complete design document with draft files — in a staging area for review before promotion to canonical locations.

When the user wants to build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion.

When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products.