AI Skill Pod

Skill library

Ready-to-use skills for business teams. Add one to your pod and everyone's AI uses the same version.

Product

  • A/B test plan Official
    Writes an A/B test brief: hypothesis, primary and guardrail metrics, MDE, sample size and duration with the math, stop rules, and a decision rule set in advance.
  • Competitor product teardown Official
    Writes a competitor teardown from public pages or trial notes: onboarding steps, pricing, core loop, strengths, gaps, what to copy or not, unverified marked.
  • Feature prioritization with RICE Official
    Scores a backlog with RICE or ICE, shows the math per item, tests sensitivity, recommends a cut line for capacity, and flags dependencies.
  • PRD from messy notes Official
    Turns notes, Slack threads, and call notes into a PRD: problem with evidence, goals and non-goals, metrics, must/should/could requirements, and flagged gaps.
  • Release notes from merged changes Official
    Writes customer-facing release notes from merged PRs or tickets, grouped New, Improved, Fixed, benefit-first, plus an internal changelog.
  • Roadmap update for stakeholders Official
    Writes a Now/Next/Later roadmap update: what moved and why, outcomes not just features, dated commitments apart, what we're not doing, and asks.
  • Spec review before build Official
    Reviews a PRD or spec before build for ambiguity, missing empty/loading/error/permission states, metrics, rollout, and a first-time user walk-through.
  • User interview guide Official
    Writes a user interview guide with a screener, warm-up, past-behavior questions with no hypotheticals or leading, probes, and a wrap-up.
  • User interview synthesis Official
    Synthesizes interview notes into themes with participant counts, quotes, jobs-to-be-done, insights vs. assumptions, and recommendations with confidence.
  • User stories with acceptance criteria Official
    Turns a feature into user stories with Given/When/Then acceptance criteria, edge cases, out-of-scope notes, and an INVEST check per story.