[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M751BS4NHVMMSRCXKSZ3YCZ2":3,"skill-same:01M751BS4NHVMMSRCXKSZ3YCZ2":49},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":26,"commitSha":27,"skillDirectory":28,"forksCount":29,"repositoryHtmlUrl":30,"repositoryHomepageUrl":31,"ownerHtmlUrl":32,"ownerBlogUrl":31,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M751BS4NHVMMSRCXKSZ3YCZ2","plg-motion-designer",null,"Use when designing a product-led, self-serve activation motion for signups. Triggers on \"design our PLG motion\", \"self-serve onboarding\", \"what is our aha moment\", \"define activation\", \"activation rate\", \"time-to-value\", \"onboarding funnel\", \"in-product nudges\", \"set activation milestones\", \"signup to value\", \"free-to-paid\", \"PQL\". Defines the aha moment, the activation milestones to it, and the in-product nudges and metric gates between each step. Do NOT use for outbound\u002Fsales-led launch sequencing - use [[launch-plan-sequencer]] instead; for arming a human sales team with collateral, use [[sales-enablement-kit]] instead; for the page that captures the signup, use [[landing-page-copy]]; for pricing tiers and the paywall, use [[saas-pricing]] and [[pricing-strategy]].","SkillMedev\u002Fskills","SkillMedev","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F298078254?v=4","01M74ZSGTQ918CB0VXW4EG3RMX","SkillMe","01M74ZSGVBT497NA95CBT8JTY4",25,"MIT","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fplg-motion-designer\u002FSKILL.md",[],[],"2026-11-11 18:11:01",false,"---\nname: plg-motion-designer\ndescription: Use when designing a product-led, self-serve activation motion for signups. Triggers on \"design our PLG motion\", \"self-serve onboarding\", \"what is our aha moment\", \"define activation\", \"activation rate\", \"time-to-value\", \"onboarding funnel\", \"in-product nudges\", \"set activation milestones\", \"signup to value\", \"free-to-paid\", \"PQL\". Defines the aha moment, the activation milestones to it, and the in-product nudges and metric gates between each step. Do NOT use for outbound\u002Fsales-led launch sequencing - use [[launch-plan-sequencer]] instead; for arming a human sales team with collateral, use [[sales-enablement-kit]] instead; for the page that captures the signup, use [[landing-page-copy]]; for pricing tiers and the paywall, use [[saas-pricing]] and [[pricing-strategy]].\nmetadata:\n  title: \"PLG Motion Designer\"\n---\n\n# PLG Motion Designer\n\nA product-led motion lives or dies on one number most teams never define: the\npercentage of signups who reach value before they churn in silence. You design\nthe path from `signup → aha moment → activated` and instrument the gates between\neach step, so the product sells itself instead of waiting on a human. The most\ncommon failure is a vanity definition of activation - \"created an account\" - that\ncorrelates with nothing. This skill fixes the definition first, then builds the\nmotion around it.\n\n## When to use this skill\n\nReach for it once positioning and the offer are set ([[positioning-statement]],\n[[messaging-hierarchy]]) and the self-serve product can be signed up for without\na sales call. It owns the *in-product* journey; the acquisition page is\n[[landing-page-copy]], the paywall economics are [[saas-pricing]] \u002F\n[[pricing-strategy]], and the broad launch plan is [[go-to-market-planner]] and\n[[launch-plan-sequencer]]. Run it before [[launch-day-runbook]] so the motion is\nlive and measured when traffic hits.\n\n## Step 1 - Define the aha moment off behavior, not opinion\n\nThe aha moment is the *first* in-product action after which a user's odds of\nretaining jump sharply. Find it, do not guess it:\n\n1. List the 8-12 candidate first-week actions a user can take.\n2. For each, compare week-4 retention of users who did it vs. didn't. The aha\n   action is the one with the widest retention gap that a *new* user can plausibly\n   reach in the first session.\n3. Pin it to a number, not a vibe: not \"sends a message\" but \"sends a message to\n   a second person.\" Slack's was ~2,000 messages sent by a team; the shape\n   (frequency x breadth x time) matters more than the figure.\n\nA crisp aha definition reads: **\"\u003Ccount> of \u003Ccore action> across \u003Cbreadth> within\n\u003Ctime window>.\"** If you cannot fill that template, you do not yet know your aha\nmoment - and every downstream nudge is guesswork.\n\n## Step 2 - Reverse-engineer activation milestones to it\n\nActivation is reaching the aha moment. Work backward and name the 3-5 *ordered*\nmilestones a user must clear to get there. Each milestone is a discrete, logged\nevent - the rungs of the ladder:\n\n```\n  M0  Signup            account created\n  M1  Setup             the one config without which value is impossible\n  M2  First action      core action done once (the \"empty state\" defeated)\n  M3  Aha moment        the Step-1 definition is met  ← ACTIVATED\n  M4  Habit \u002F PQL       repeated value → ready to convert (hand to saas-pricing)\n```\n\nRules that keep the ladder honest:\n- Strip every step that is not on the critical path to value. Each extra step\n  leaks users.\n- Order them; a milestone a user reaches *out of order* is mislabeled.\n- M2 is the empty-state killer - the single hardest drop, where a blank product\n  meets a new user. Design it deliberately (templates, sample data, a guided\n  first action).\n\n## Step 3 - Gate each step with a metric\n\nEvery transition between milestones gets two numbers, and you do not move on\nuntil they are instrumented:\n\n- **Step conversion rate** - % who advance Mₙ → Mₙ₊₁. This localizes the leak.\n- **Time-to-value (TTV)** - median time from signup to M3 (aha). The headline\n  speed metric; long TTV silently kills self-serve.\n- **Activation rate** - % of signups who reach M3 within the TTV window. The one\n  number the whole motion optimizes.\n\nThe biggest single drop in step conversion is your bottleneck - fix it before\ntouching anything else. Optimizing a 90% step while a 30% step bleeds upstream is\nthe classic waste.\n\n## Step 4 - Place in-product nudges only on the gaps\n\nNudges are interventions to lift a specific step's conversion - never decoration.\nFor each *leaking* step, pick the lightest nudge that moves it:\n\n| Leak | Nudge | Note |\n|---|---|---|\n| Stalls at M1 setup | Inline checklist \u002F progress bar | Show the path; reduce the unknown |\n| Empty state at M2 | Templates, sample data, guided first action | Defeat the blank screen |\n| Drops before aha | Contextual tooltip at the moment of need | In-product beats email here |\n| Goes dark after signup | Lifecycle email tied to the *missed* milestone | Behavior-triggered, not drip |\n| Hits aha, no repeat | Habit loop: trigger → action → reward | Build toward M4 \u002F PQL |\n\nDiscipline: one nudge per leak, instrument its effect, keep it only if step\nconversion rises. Over-nudging (badges, popups, tours everywhere) trains users to\ndismiss everything and buries the one that matters.\n\n## Runnable artifact - activation funnel diagnostic\n\nDrop your per-milestone counts in; it returns step conversion, where the funnel\nleaks worst, TTV, and the overall activation rate. Self-contained Python.\n\n```python\n# activation_funnel.py  -  python3 activation_funnel.py\nfrom statistics import median\n\n# Ordered milestones: signup is M0, aha is the activation gate.\nMILESTONES = [\"M0 signup\", \"M1 setup\", \"M2 first action\", \"M3 aha (ACTIVATED)\"]\nCOUNTS     = [10000,        6200,        3900,             2600]   # users reaching each\nAHA_INDEX  = 3                                                     # index of the aha milestone\nTTV_HOURS  = [0.5, 6.0, 22.0, 34.0, 48.0, 70.0]                   # signup→aha per activated user\n\ndef report():\n    print(f\"{'transition':\u003C34}{'reached':>9}{'step conv':>11}\")\n    worst = (\"\", 1.0)\n    for i in range(1, len(MILESTONES)):\n        conv = COUNTS[i] \u002F COUNTS[i - 1]\n        arrow = f\"{MILESTONES[i-1].split()[0]} -> {MILESTONES[i].split()[0]}\"\n        print(f\"{arrow:\u003C34}{COUNTS[i]:>9}{conv:>10.0%}\")\n        if conv \u003C worst[1]:\n            worst = (arrow, conv)\n    activation = COUNTS[AHA_INDEX] \u002F COUNTS[0]\n    print(\"-\" * 54)\n    print(f\"activation rate (signup -> aha){'':\u003C3}{activation:>20.1%}\")\n    print(f\"median time-to-value (hours){'':\u003C6}{median(TTV_HOURS):>20.1f}\")\n    print(f\"biggest leak{'':\u003C22}{worst[0]:>16}  ({worst[1]:.0%})\")\n\nreport()\n```\n\nWorked output for the sample numbers above:\n\n```\ntransition                          reached  step conv\nM0 -> M1                               6200        62%\nM1 -> M2                               3900        63%\nM2 -> M3                               2600        67%\n------------------------------------------------------\nactivation rate (signup -> aha)                  26.0%\nmedian time-to-value (hours)                      28.0\nbiggest leak                          M0 -> M1  (62%)\n```\n\nRead: 26% activation with the worst leak at the very first setup step (M0→M1) and\na 28-hour TTV. The move is a Step-4 nudge on setup (inline checklist) and a hard\nlook at why first value takes a day - not a new feature, not more signups.\n\n## Fill-in template - the activation spec\n\n```\nAha moment:    \u003Ccount> of \u003Ccore action> across \u003Cbreadth> within \u003Ctime window>\nActivation =   reaching the aha moment within \u003CTTV window>\n\nMilestones (ordered, each a logged event):\n  M0 Signup        → event: ______\n  M1 Setup         → event: ______   gate: step conv ____%  nudge: ______\n  M2 First action  → event: ______   gate: step conv ____%  nudge: ______\n  M3 Aha\u002FACTIVATED → event: ______   gate: step conv ____%\n  M4 Habit \u002F PQL   → event: ______   (hand to saas-pricing for conversion)\n\nNorth-star gate:   activation rate = ____%   (target: ____%)\nSpeed gate:        median TTV = ____         (target: ____)\nCurrent bottleneck: step ______ at ____%  →  intervention: ______\n```\n\n## Quality bar\n\n- The aha moment fits the `\u003Ccount> of \u003Caction> across \u003Cbreadth> within \u003Cwindow>`\n  template and is backed by a retention gap, not an opinion.\n- Every milestone is a discrete logged event, ordered, on the critical path to\n  value - no decorative steps.\n- Each transition has a step-conversion number and the whole motion has an\n  activation rate and a median TTV. If a step is uninstrumented, the motion is\n  not done.\n- Exactly one nudge sits on each *leaking* step, and each nudge has a measured\n  before\u002Fafter on that step's conversion.\n- The single biggest leak is named, and the recommended action targets it - not\n  a healthier step.\n- M4\u002FPQL hands cleanly to [[saas-pricing]] \u002F [[pricing-strategy]] for conversion;\n  this skill stops at activation.\n\n## Do NOT\n\n- Do NOT define activation as \"signed up\" or \"completed onboarding tour.\" Those\n  correlate with nothing; activation is reaching *value*.\n- Do NOT optimize a healthy step while an upstream step bleeds. Fix the biggest\n  leak first.\n- Do NOT carpet the product in tours, badges, and popups. One nudge per leak,\n  kept only if it moves the number.\n- Do NOT use this for sales-led or outbound launch sequencing - that is\n  [[launch-plan-sequencer]] and [[launch-day-runbook]].\n- Do NOT use this to arm a human sales team with decks, one-pagers, or objection\n  handling - a PLG motion replaces the rep; for the sales-led path use\n  [[sales-enablement-kit]] instead.\n- Do NOT design the signup\u002Facquisition page or the paywall here - that is\n  [[landing-page-copy]] and [[saas-pricing]] \u002F [[pricing-strategy]].\n- Do NOT invent the aha-moment number to look good in a deck. An unbacked\n  activation target sends the whole motion chasing the wrong behavior.\n- Do NOT confuse a long TTV with a feature gap; it is usually a leaking step or a\n  missing nudge, found in Step 3.\n\n## Deliverable\n\nA one-page activation spec: the aha-moment definition with its retention backing,\nthe ordered milestone ladder, the step-conversion \u002F TTV \u002F activation-rate gates,\none nudge per leaking step with its measured lift, the named current bottleneck\nand the intervention for it, and a clean handoff at M4\u002FPQL to\n[[saas-pricing]] for conversion. Fits inside the GTM launch built by\n[[go-to-market-planner]] and [[launch-plan-sequencer]].\n","# PLG Motion Designer\n\nA product-led motion lives or dies on one number most teams never define: the\npercentage of signups who reach value before they churn in silence. You design\nthe path from `signup → aha moment → activated` and instrument the gates between\neach step, so the product sells itself instead of waiting on a human. The most\ncommon failure is a vanity definition of activation - \"created an account\" - that\ncorrelates with nothing. This skill fixes the definition first, then builds the\nmotion around it.\n\n## When to use this skill\n\nReach for it once positioning and the offer are set ([[positioning-statement]],\n[[messaging-hierarchy]]) and the self-serve product can be signed up for without\na sales call. It owns the *in-product* journey; the acquisition page is\n[[landing-page-copy]], the paywall economics are [[saas-pricing]] \u002F\n[[pricing-strategy]], and the broad launch plan is [[go-to-market-planner]] and\n[[launch-plan-sequencer]]. Run it before [[launch-day-runbook]] so the motion is\nlive and measured when traffic hits.\n\n## Step 1 - Define the aha moment off behavior, not opinion\n\nThe aha moment is the *first* in-product action after which a user's odds of\nretaining jump sharply. Find it, do not guess it:\n\n1. List the 8-12 candidate first-week actions a user can take.\n2. For each, compare week-4 retention of users who did it vs. didn't. The aha\n   action is the one with the widest retention gap that a *new* user can plausibly\n   reach in the first session.\n3. Pin it to a number, not a vibe: not \"sends a message\" but \"sends a message to\n   a second person.\" Slack's was ~2,000 messages sent by a team; the shape\n   (frequency x breadth x time) matters more than the figure.\n\nA crisp aha definition reads: **\"\u003Ccount> of \u003Ccore action> across \u003Cbreadth> within\n\u003Ctime window>.\"** If you cannot fill that template, you do not yet know your aha\nmoment - and every downstream nudge is guesswork.\n\n## Step 2 - Reverse-engineer activation milestones to it\n\nActivation is reaching the aha moment. Work backward and name the 3-5 *ordered*\nmilestones a user must clear to get there. Each milestone is a discrete, logged\nevent - the rungs of the ladder:\n\n```\n  M0  Signup            account created\n  M1  Setup             the one config without which value is impossible\n  M2  First action      core action done once (the \"empty state\" defeated)\n  M3  Aha moment        the Step-1 definition is met  ← ACTIVATED\n  M4  Habit \u002F PQL       repeated value → ready to convert (hand to saas-pricing)\n```\n\nRules that keep the ladder honest:\n- Strip every step that is not on the critical path to value. Each extra step\n  leaks users.\n- Order them; a milestone a user reaches *out of order* is mislabeled.\n- M2 is the empty-state killer - the single hardest drop, where a blank product\n  meets a new user. Design it deliberately (templates, sample data, a guided\n  first action).\n\n## Step 3 - Gate each step with a metric\n\nEvery transition between milestones gets two numbers, and you do not move on\nuntil they are instrumented:\n\n- **Step conversion rate** - % who advance Mₙ → Mₙ₊₁. This localizes the leak.\n- **Time-to-value (TTV)** - median time from signup to M3 (aha). The headline\n  speed metric; long TTV silently kills self-serve.\n- **Activation rate** - % of signups who reach M3 within the TTV window. The one\n  number the whole motion optimizes.\n\nThe biggest single drop in step conversion is your bottleneck - fix it before\ntouching anything else. Optimizing a 90% step while a 30% step bleeds upstream is\nthe classic waste.\n\n## Step 4 - Place in-product nudges only on the gaps\n\nNudges are interventions to lift a specific step's conversion - never decoration.\nFor each *leaking* step, pick the lightest nudge that moves it:\n\n| Leak | Nudge | Note |\n|---|---|---|\n| Stalls at M1 setup | Inline checklist \u002F progress bar | Show the path; reduce the unknown |\n| Empty state at M2 | Templates, sample data, guided first action | Defeat the blank screen |\n| Drops before aha | Contextual tooltip at the moment of need | In-product beats email here |\n| Goes dark after signup | Lifecycle email tied to the *missed* milestone | Behavior-triggered, not drip |\n| Hits aha, no repeat | Habit loop: trigger → action → reward | Build toward M4 \u002F PQL |\n\nDiscipline: one nudge per leak, instrument its effect, keep it only if step\nconversion rises. Over-nudging (badges, popups, tours everywhere) trains users to\ndismiss everything and buries the one that matters.\n\n## Runnable artifact - activation funnel diagnostic\n\nDrop your per-milestone counts in; it returns step conversion, where the funnel\nleaks worst, TTV, and the overall activation rate. Self-contained Python.\n\n```python\n# activation_funnel.py  -  python3 activation_funnel.py\nfrom statistics import median\n\n# Ordered milestones: signup is M0, aha is the activation gate.\nMILESTONES = [\"M0 signup\", \"M1 setup\", \"M2 first action\", \"M3 aha (ACTIVATED)\"]\nCOUNTS     = [10000,        6200,        3900,             2600]   # users reaching each\nAHA_INDEX  = 3                                                     # index of the aha milestone\nTTV_HOURS  = [0.5, 6.0, 22.0, 34.0, 48.0, 70.0]                   # signup→aha per activated user\n\ndef report():\n    print(f\"{'transition':\u003C34}{'reached':>9}{'step conv':>11}\")\n    worst = (\"\", 1.0)\n    for i in range(1, len(MILESTONES)):\n        conv = COUNTS[i] \u002F COUNTS[i - 1]\n        arrow = f\"{MILESTONES[i-1].split()[0]} -> {MILESTONES[i].split()[0]}\"\n        print(f\"{arrow:\u003C34}{COUNTS[i]:>9}{conv:>10.0%}\")\n        if conv \u003C worst[1]:\n            worst = (arrow, conv)\n    activation = COUNTS[AHA_INDEX] \u002F COUNTS[0]\n    print(\"-\" * 54)\n    print(f\"activation rate (signup -> aha){'':\u003C3}{activation:>20.1%}\")\n    print(f\"median time-to-value (hours){'':\u003C6}{median(TTV_HOURS):>20.1f}\")\n    print(f\"biggest leak{'':\u003C22}{worst[0]:>16}  ({worst[1]:.0%})\")\n\nreport()\n```\n\nWorked output for the sample numbers above:\n\n```\ntransition                          reached  step conv\nM0 -> M1                               6200        62%\nM1 -> M2                               3900        63%\nM2 -> M3                               2600        67%\n------------------------------------------------------\nactivation rate (signup -> aha)                  26.0%\nmedian time-to-value (hours)                      28.0\nbiggest leak                          M0 -> M1  (62%)\n```\n\nRead: 26% activation with the worst leak at the very first setup step (M0→M1) and\na 28-hour TTV. The move is a Step-4 nudge on setup (inline checklist) and a hard\nlook at why first value takes a day - not a new feature, not more signups.\n\n## Fill-in template - the activation spec\n\n```\nAha moment:    \u003Ccount> of \u003Ccore action> across \u003Cbreadth> within \u003Ctime window>\nActivation =   reaching the aha moment within \u003CTTV window>\n\nMilestones (ordered, each a logged event):\n  M0 Signup        → event: ______\n  M1 Setup         → event: ______   gate: step conv ____%  nudge: ______\n  M2 First action  → event: ______   gate: step conv ____%  nudge: ______\n  M3 Aha\u002FACTIVATED → event: ______   gate: step conv ____%\n  M4 Habit \u002F PQL   → event: ______   (hand to saas-pricing for conversion)\n\nNorth-star gate:   activation rate = ____%   (target: ____%)\nSpeed gate:        median TTV = ____         (target: ____)\nCurrent bottleneck: step ______ at ____%  →  intervention: ______\n```\n\n## Quality bar\n\n- The aha moment fits the `\u003Ccount> of \u003Caction> across \u003Cbreadth> within \u003Cwindow>`\n  template and is backed by a retention gap, not an opinion.\n- Every milestone is a discrete logged event, ordered, on the critical path to\n  value - no decorative steps.\n- Each transition has a step-conversion number and the whole motion has an\n  activation rate and a median TTV. If a step is uninstrumented, the motion is\n  not done.\n- Exactly one nudge sits on each *leaking* step, and each nudge has a measured\n  before\u002Fafter on that step's conversion.\n- The single biggest leak is named, and the recommended action targets it - not\n  a healthier step.\n- M4\u002FPQL hands cleanly to [[saas-pricing]] \u002F [[pricing-strategy]] for conversion;\n  this skill stops at activation.\n\n## Do NOT\n\n- Do NOT define activation as \"signed up\" or \"completed onboarding tour.\" Those\n  correlate with nothing; activation is reaching *value*.\n- Do NOT optimize a healthy step while an upstream step bleeds. Fix the biggest\n  leak first.\n- Do NOT carpet the product in tours, badges, and popups. One nudge per leak,\n  kept only if it moves the number.\n- Do NOT use this for sales-led or outbound launch sequencing - that is\n  [[launch-plan-sequencer]] and [[launch-day-runbook]].\n- Do NOT use this to arm a human sales team with decks, one-pagers, or objection\n  handling - a PLG motion replaces the rep; for the sales-led path use\n  [[sales-enablement-kit]] instead.\n- Do NOT design the signup\u002Facquisition page or the paywall here - that is\n  [[landing-page-copy]] and [[saas-pricing]] \u002F [[pricing-strategy]].\n- Do NOT invent the aha-moment number to look good in a deck. An unbacked\n  activation target sends the whole motion chasing the wrong behavior.\n- Do NOT confuse a long TTV with a feature gap; it is usually a leaking step or a\n  missing nudge, found in Step 3.\n\n## Deliverable\n\nA one-page activation spec: the aha-moment definition with its retention backing,\nthe ordered milestone ladder, the step-conversion \u002F TTV \u002F activation-rate gates,\none nudge per leaking step with its measured lift, the named current bottleneck\nand the intervention for it, and a clean handoff at M4\u002FPQL to\n[[saas-pricing]] for conversion. Fits inside the GTM launch built by\n[[go-to-market-planner]] and [[launch-plan-sequencer]].\n",{"name":5,"metadata":24,"description":7},{"title":25},"PLG Motion Designer","main","97a13607d669157a4a16d5ba79b77f208319f7b9","skills\u002Fplg-motion-designer",3,"https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills","https:\u002F\u002Fskillme.dev","https:\u002F\u002Fgithub.com\u002FSkillMedev","MCP-native catalog of Claude Agent Skills. Browse, recommend, install, and auto-apply skills in chat. Open source, every skill free and clonable on GitHub.","2026-10-14 03:19:31",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add SkillMedev\u002Fskills --skill plg-motion-designer",{"tool":41,"command":42},"bunx","bunx skills add SkillMedev\u002Fskills --skill plg-motion-designer",{"tool":44,"command":45},"pnpm","pnpm dlx skills add SkillMedev\u002Fskills --skill plg-motion-designer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fplg-motion-designer\u002FSKILL.md",true,[],[50,58,65,72,79,86],{"skillNo":51,"name":52,"nameZh":6,"description":53,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":54,"categories":55,"keywords":56,"publishedAt":57},"01M75271B256DF3FX2VG5VRYEE","zone-2-cardio-plan","Use when someone asks to build a steady-state cardio plan, train an aerobic base or Zone 2, structure easy or endurance weekly cardio, train by heart-rate zones, or improve resting heart rate, VO2, or endurance. Builds a heart-rate-zone aerobic training block with session structure, modality choice, and progression. General fitness guidance, not medical advice. Do NOT use to design a strength or lifting program (use Strength Training Plan), high-intensity interval conditioning, HIIT, or circuits (use Conditioning & HIIT Program), or a mobility\u002Fflexibility routine (use Mobility Routine).","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzone-2-cardio-plan\u002FSKILL.md",[],[],"2026-11-11 18:27:18",{"skillNo":59,"name":60,"nameZh":6,"description":61,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":62,"categories":63,"keywords":64,"publishedAt":57},"01M7526VP1QBBKYBE17S1WR86Y","youtube-script-writer","Writes retention-engineered long-form YouTube scripts on a hook\u002Fbody\u002Fpayoff architecture - a first-30-seconds hook that survives the retention cliff, a beat-sheet body with mini-hooks and bridges, timed pattern interrupts, and a payoff that over-delivers - with B-roll and editing cues marked inline. Use when someone says \"script my next video\", \"my retention graph dies at the start\", \"tighten this draft\", or \"outline a video on X\". Do NOT use for the 3-second opener of TikTok, Reels, or Shorts - use video-hook-writer instead; do NOT use for spoken voiceover synced to on-screen tutorial actions - use narration-script instead; do NOT use for a sales demo built on a buyer's discovery notes - use demo-script instead; do NOT use to design the thumbnail and title - use thumbnail-concept instead.","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fyoutube-script-writer\u002FSKILL.md",[],[],{"skillNo":66,"name":67,"nameZh":6,"description":68,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":69,"categories":70,"keywords":71,"publishedAt":57},"01M7526P2T0WKMHDXS4Q58237T","win-back-campaign","Designs segmented win-back email sequences for dormant users - dormancy tiers, a three-beat sequence with a single proportional incentive, and a suppression rule - and measures success by re-activation, not opens. Use when someone says \"our users went quiet\", \"design a win-back campaign\", \"how do I re-engage lapsed customers\", \"should we email people who haven't logged in for months\", or lifecycle messaging has stopped landing with a lapsed segment. Do NOT use for recovering an unfinished checkout - use abandoned-cart-sequence instead. Do NOT use for diagnosing and fixing why active customers cancel - use churn-reduction instead. Do NOT use for building always-on onboarding or nurture flows - use email-drip-builder instead.","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwin-back-campaign\u002FSKILL.md",[],[],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":76,"categories":77,"keywords":78,"publishedAt":57},"01M7526HF2RCDJ50P93WRZRHVV","wikipedia-style","Writes neutral, verifiable, encyclopedic prose following Wikipedia's core content policies and manual of style - NPOV, inline citations, notability-backed claims, and a strict ban on promotional language. Use when someone asks \"write this like a Wikipedia article\", \"draft a Wikipedia page for this company or person\", \"make this neutral and encyclopedic\", or \"why does my article draft keep getting rejected\". Do NOT use for persuasive or opinion writing - use op-ed-writer instead; for thesis-driven academic papers, use academic-essay; for verifying claims in existing text, use fact-checker.","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwikipedia-style\u002FSKILL.md",[],[],{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":57},"01M7526D43CTGRKGKNQ2GB0KVX","whitepapers","Structures and writes authoritative B2B whitepapers - a standalone executive summary, a data-sized problem statement, methodology, evidence-driven findings, recommendations, and a soft call to action - flagging every claim that needs a real citation. Use when a marketer asks \"write a whitepaper on this topic\", \"turn our research into a lead-gen asset\", \"make this credible enough for executives\", or a draft reads like a product pitch instead of analysis. Do NOT use for customer-story-driven proof - use case-study-builder instead; for policy audiences, use policy-brief.","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwhitepapers\u002FSKILL.md",[],[],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":57},"01M75268423Y3K50SY5WC2NX2G","white-space-analysis","Finds unmet market gaps by ranking jobs-to-be-done on importance versus satisfaction, overlaying them against current solutions and workarounds, and validating that each gap is real, winnable, and worth winning. Use when someone asks \"where are the gaps in this market\", \"what's underserved here\", \"where should we play next\", or is hunting for product, feature, or market-entry opportunities. Do NOT use for profiling competitors and building battle cards - use competitive-intelligence instead; for putting a dollar figure on an identified opportunity - use market-sizing instead; for extracting jobs-to-be-done from raw customer interviews - use jtbd-extractor instead.","https:\u002F\u002Fgithub.com\u002FSkillMedev\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwhite-space-analysis\u002FSKILL.md",[],[]]