product-taste-intuition
npx skills add https://github.com/liqiongyu/lenny_skills_plus --skill product-taste-intuition
Agent 安装分布
Skill 文档
Product Taste & Intuition
Scope
Covers
- Developing product taste (what âgoodâ looks like) through deliberate exposure, observation, and critique
- Using intuition as a hypothesis generator (turning âgut feelâ into testable hypotheses)
- Building a repeatable practice loop (exposure hours â analysis â validation â updated taste rules)
When to use
- âHelp me improve my product taste / product sense.â
- âCalibrate what âgood onboardingâ looks like for our product category.â
- âTurn my intuition about this flow into testable hypotheses.â
- âCreate a structured way to study great products and extract patterns.â
When NOT to use
- You need to decide what to build (use
problem-definition,prioritizing-roadmap, ordefining-product-vision). - You need user evidence first (use
conducting-user-interviewsorusability-testing). - You want aesthetic critique only (this is product experience: value, UX, clarity, trust, speedânot just visuals).
- You canât name any target user, use case, or the âtaste domainâ you want to improve (weâll narrow first).
Inputs
Minimum required
- Taste domain to improve (pick 1): onboarding, activation, navigation/IA, editor/workflow, pricing/packaging UX, notifications, retention loops, trust/safety, performance/latency feel, copy/voice
- Target user + top job-to-be-done for that domain
- 3â10 benchmark products/experiences to study (or âunknownâplease proposeâ)
- Time box (e.g., 60â120 min sprint; or a 2â4 week practice plan)
- Constraints (platform, geography, accessibility, compliance, brand voice, etc.)
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If inputs remain missing, proceed with explicit assumptions and provide 2 scope options (narrow vs broad).
Outputs (deliverables)
Produce a Taste Calibration Pack (in-chat Markdown; or as files if requested):
- Taste Calibration Brief (domain, target user/job, what âgoodâ means, constraints)
- Benchmark Set (5â10 products) + âwhy theseâ + what to study
- Product Study Notes (1 page per benchmark) using a consistent critique template
- Taste Rules + Anti-Patterns (do/donât rules derived from evidence)
- Intuition â Hypothesis Log (testable hypotheses + predicted signals)
- Validation Plan (qual + quant checks; smallest viable tests)
- Practice Plan (2â4 weeks: exposure hours + weekly synthesis cadence)
- Risks / Open questions / Next steps (always included)
Templates: references/TEMPLATES.md
Workflow (8 steps)
1) Intake + pick the taste domain (narrow the problem)
- Inputs: User context; references/INTAKE.md.
- Actions: Choose 1 taste domain and 1 âmomentâ (e.g., first-run onboarding). Define target user + job + constraints. Set time box.
- Outputs: Taste Calibration Brief (draft).
- Checks: A stakeholder can answer: âWhat specific experience are we calibrating taste for?â
2) Define âgood tasteâ as decision criteria (not vibes)
- Inputs: Domain + user/job.
- Actions: Draft 6â10 criteria (e.g., clarity, time-to-value, trust, agency, error recovery, perceived speed, cognitive load). Add explicit tradeoffs (what youâll sacrifice).
- Outputs: Criteria list + tradeoffs section in the brief.
- Checks: Criteria are observable in-product (you can point to UI/behavior), not generic adjectives.
3) Build the benchmark set (exposure hours, curated)
- Inputs: Known benchmarks (or none).
- Actions: Select 5â10 exemplars (direct, adjacent, and at least 1 âgold standardâ). For each: what youâre studying and why itâs relevant.
- Outputs: Benchmark Set table.
- Checks: Set includes at least 2 âoutside the categoryâ references to avoid local maxima.
4) Study like a voracious user (structured observation)
- Inputs: Benchmarks; critique template.
- Actions: Use each product as the target user. Capture micro-moments: friction, delight, confusion, trust breaks. Record âwhat happenedâ before âwhy itâs good/badâ.
- Outputs: Product Study Notes (draft).
- Checks: Each benchmark note includes at least 3 concrete moments with screenshots/quotes if available (or precise descriptions).
5) Synthesize: turn observations into taste rules + anti-patterns
- Inputs: Study notes across benchmarks.
- Actions: Cluster patterns. Convert into rules: DO/DO NOT, plus rationale and where it applies. Add anti-patterns that create âAI slopâ (generic, incoherent, misaligned experiences).
- Outputs: Taste Rules + Anti-Patterns.
- Checks: Each rule is backed by ⥠2 observations from different benchmarks (or explicitly marked âhypothesisâ).
6) Intuition as hypothesis generator (make it testable)
- Inputs: Rules + your gut reactions.
- Actions: Write intuition statements (âIt feels off becauseâ¦â) and convert into testable hypotheses with predicted signals and counter-signals.
- Outputs: Intuition â Hypothesis Log.
- Checks: Each hypothesis has a clear falsification condition (âIf X doesnât change after Y, we were wrong.â).
7) Validate with smallest viable checks (qual + quant)
- Inputs: Hypothesis log; available data/research access.
- Actions: Choose the lightest validation per hypothesis: usability task, intercept prompt, session replay review, funnel slice, A/B smoke test, copy test, etc. Define success metrics and sample.
- Outputs: Validation Plan with owners/cadence if known.
- Checks: Validation steps are feasible within the stated time box and donât require sensitive data.
8) Create a practice loop + quality gate + finalize
- Inputs: Draft pack.
- Actions: Build a 2â4 week practice plan (exposure hours schedule + weekly synthesis). Run references/CHECKLISTS.md and score with references/RUBRIC.md. Add Risks/Open questions/Next steps.
- Outputs: Final Taste Calibration Pack.
- Checks: A reader can follow the practice plan without additional context; assumptions are explicit.
Quality gate (required)
- Use references/CHECKLISTS.md and references/RUBRIC.md.
- Always include: Risks, Open questions, Next steps.
Examples
Example 1 (Onboarding): âCalibrate our onboarding taste vs best-in-class. Target users are first-time PMs. Time box: 90 minutes. Output a Taste Calibration Pack.â
Expected: benchmark set, critique notes, taste rules, hypotheses, and a lightweight validation plan.
Example 2 (B2B workflow UX): âMy gut says our âcreate projectâ flow feels slow and confusing. Turn that into testable hypotheses and a validation plan.â
Expected: intuitionâhypothesis log with falsification conditions and smallest viable checks.
Boundary example: âTell me what good taste is in general.â
Response: require a specific domain + target user/job; otherwise produce a menu of domain options and propose a narrow starting point.