[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6D9JDF53R00F5TP0DTMS11K":3,"skill-same:01M6D9JDF53R00F5TP0DTMS11K":79},{"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":23,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":50,"ownerDescription":51,"updatedAt":52,"install":53,"resources":66},"01M6D9JDF53R00F5TP0DTMS11K","game-audience",null,"Use only for video game projects; identify player segments by taste, behavior, platform, genre affinity, and motivation","GeorgeQLe\u002Fagentic-skills","GeorgeQLe","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F21134126?v=4","01M6D2JP418S0VGJGF8M93EC3H","George Le","01M6D2JPBAKYD82TA5FS6HKQ3D",1,"MIT","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fgame\u002Fclaude\u002Fgame-audience\u002Farchive\u002Fv0.3\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35],"game","game audience","research","Video","projects","behavior","v0","use","only","visual","platform","taste","2026-11-10 10:12:30",false,"---\nname: game-audience\ndescription: Use only for video game projects; identify player segments by taste, behavior, platform, genre affinity, and motivation\ntype: research\nversion: v0.3\ninterview_depth: light\nvisual_tier: visual\n---\n\n# Game Audience\n\n## Report-First Approval Gate\n\nDefault to report-only: present findings, evidence coverage, assumptions, recommended artifact path, and proposed file changes in a pre-approval alignment page plus a concise conversation summary for user approval before creating or updating canonical research, spec, or task files.\n\nDo not write or overwrite synthesized deliverables until the user explicitly approves, unless the user invoked an explicit write\u002Fupdate\u002Ffix mode or clearly asked to write files upfront. Raw evidence capture may be persisted before analysis when reproducibility requires it; report those raw paths separately and still gate synthesized research\u002Freport writes.\n\nWhen stopping for approval, build and attempt to open the alignment preview page first, then ask the user to review it and approve, question, or request adjustments. Do not include `Recommended next skill`, `Recommended next command`, or downstream routing language. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.\n\n## Staged Research Workflow\n\nUse this staged workflow for synthesized research or report outputs that would create or update canonical research, spec, or task files.\n\n1. **Stage 1 - Research and clarify.** Perform the research, run required source\u002Fcode checks, and ask any needed clarification questions. Write only a non-canonical working packet: flat mode uses `research\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`; product-path mode uses `research\u002F{slug}\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`. Replace `\u003Cskill>` with this skill's `name` value. Do not create or update canonical research, spec, or task files in Stage 1. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet.\n2. **Stage 2 - Review alignment.** Consume the working packet and build the `review` HTML alignment page. The page must render the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and approval gates. Stop for either feedback-only YAML or final compiled YAML. Feedback-only YAML revises the working packet and page, then remains in Stage 2.\n3. **Stage 3 - Finalize approved artifacts.** Consume final compiled YAML only when it has no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet to `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-working-path>`, remove the active working packet, write the approved canonical artifacts to the unchanged output paths below, and convert the alignment page to `confirmed` with the approval record preserved.\n\nCanonical output paths remain unchanged. Search logs and other supporting evidence remain allowed only where this skill's output contract already requires them.\n\nIdentify the target player audience for a video game.\n\n## Evidence And Feedback Handling\n\nTreat user feedback as input to evaluate, not as automatic ground truth.\n\n- For factual, evidentiary, technical, or source-backed claims: verify against available evidence. If the user appears to misunderstand the evidence or states something factually incorrect, push back clearly and cite the evidence. Do not rewrite findings merely to agree.\n- For taste, brand, positioning preference, risk appetite, prioritization, or other subjective judgment calls: weigh user feedback heavily and adapt the recommendation unless it conflicts with verified evidence.\n- When feedback mixes facts and preference, separate them explicitly: correct the factual part, then incorporate the preference where it is a legitimate judgment call.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Output\n\nWrite or update `research\u002Fgame-audience.md` with target segments, platform fit, genre familiarity, motivations, adjacent audiences, and risky assumptions to validate.\n\n## Next-Step Routing\n\nAfter writing the artifact, recommend the next contextual game-pack skill in the final response as `Recommended next skill: \u003Ccommand>`.\n\nDefault recommendation: `\u002Fgame-fantasy`.\n\nIf prototype, playtest, or market evidence invalidates an upstream assumption, route back to the earliest affected artifact (`\u002Fgame-audience`, `\u002Fgame-fantasy`, `\u002Fgame-genre-map`, or `\u002Fgame-comparables`) and explain the evidence. Otherwise, follow the default game sequence:\n\n`\u002Fgame-audience` -> `\u002Fgame-fantasy` -> `\u002Fgame-genre-map` -> `\u002Fgame-comparables` -> `\u002Fgame-core-loop` -> `\u002Fgame-prototype-test` -> `\u002Fgame-playtest-metrics` -> `\u002Fgame-store-page-test` -> `\u002Fgame-launch` -> `\u002Fgame-roadmap`\n\nIf the next artifact already exists and is current, recommend `\u002Fgame-workflow` to identify the first missing or stale game-pack artifact.\n\n## Task Classification\n\nWhen this skill produces follow-up work, file it by execution semantics:\n\n- Immediately actionable implementation or documentation work goes in `tasks\u002Ftodo.md`.\n- Human-only external actions tied to automated steps go in `tasks\u002Fmanual-todo.md` with `_(blocks: Step N.X)_` or `_(after: Step N.X)_`; repo edits, SDK wiring, generated assets, local commands, tests, audits, and authenticated CLI\u002FAPI work stay in `tasks\u002Ftodo.md`.\n- One-time condition-gated records, baselines, or future measurements go in `tasks\u002Frecord-todo.md` with source, condition, non-blocking reason, evidence, and promotion rule.\n- Cadence-based reviews, playtests, adoption checks, investor updates, retros, or docs-health checks go in `tasks\u002Frecurring-todo.md` with cadence, owner\u002Fagent, next due, evidence path, and escalation conditions.\n- Do not put non-blocking records or recurring obligations in `tasks\u002Ftodo.md` unless they have been explicitly promoted into current execution work.\n\n## Context Gathering\n\n**Step 1 — Scope questions.** Before researching, ask the user 1–3 questions via `AskUserQuestion` to understand: their product\u002Fservice, target audience, and what they hope to learn or decide from this research.\n\n**Step 2 — Research.** Conduct research scoped by the user's answers.\n\n**Step 3 — Findings validation.** Before building the alignment page, present the 3–5 most important findings and ask the user to validate or correct any critical assumptions.\n\n## Alignment Page\n\nWhen this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page following `ALIGNMENT-PAGE.md` in this skill's directory. Output: `alignment\u002Fgame-audience-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n","# Game Audience\n\n## Report-First Approval Gate\n\nDefault to report-only: present findings, evidence coverage, assumptions, recommended artifact path, and proposed file changes in a pre-approval alignment page plus a concise conversation summary for user approval before creating or updating canonical research, spec, or task files.\n\nDo not write or overwrite synthesized deliverables until the user explicitly approves, unless the user invoked an explicit write\u002Fupdate\u002Ffix mode or clearly asked to write files upfront. Raw evidence capture may be persisted before analysis when reproducibility requires it; report those raw paths separately and still gate synthesized research\u002Freport writes.\n\nWhen stopping for approval, build and attempt to open the alignment preview page first, then ask the user to review it and approve, question, or request adjustments. Do not include `Recommended next skill`, `Recommended next command`, or downstream routing language. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.\n\n## Staged Research Workflow\n\nUse this staged workflow for synthesized research or report outputs that would create or update canonical research, spec, or task files.\n\n1. **Stage 1 - Research and clarify.** Perform the research, run required source\u002Fcode checks, and ask any needed clarification questions. Write only a non-canonical working packet: flat mode uses `research\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`; product-path mode uses `research\u002F{slug}\u002F_working\u002Fpreliminary-\u003Cskill>-research.md`. Replace `\u003Cskill>` with this skill's `name` value. Do not create or update canonical research, spec, or task files in Stage 1. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet.\n2. **Stage 2 - Review alignment.** Consume the working packet and build the `review` HTML alignment page. The page must render the full preliminary packet, evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and approval gates. Stop for either feedback-only YAML or final compiled YAML. Feedback-only YAML revises the working packet and page, then remains in Stage 2.\n3. **Stage 3 - Finalize approved artifacts.** Consume final compiled YAML only when it has no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet to `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-working-path>`, remove the active working packet, write the approved canonical artifacts to the unchanged output paths below, and convert the alignment page to `confirmed` with the approval record preserved.\n\nCanonical output paths remain unchanged. Search logs and other supporting evidence remain allowed only where this skill's output contract already requires them.\n\nIdentify the target player audience for a video game.\n\n## Evidence And Feedback Handling\n\nTreat user feedback as input to evaluate, not as automatic ground truth.\n\n- For factual, evidentiary, technical, or source-backed claims: verify against available evidence. If the user appears to misunderstand the evidence or states something factually incorrect, push back clearly and cite the evidence. Do not rewrite findings merely to agree.\n- For taste, brand, positioning preference, risk appetite, prioritization, or other subjective judgment calls: weigh user feedback heavily and adapt the recommendation unless it conflicts with verified evidence.\n- When feedback mixes facts and preference, separate them explicitly: correct the factual part, then incorporate the preference where it is a legitimate judgment call.\n- When uncertain, say what is known, what is inferred, and what would change the conclusion.\n\n## Output\n\nWrite or update `research\u002Fgame-audience.md` with target segments, platform fit, genre familiarity, motivations, adjacent audiences, and risky assumptions to validate.\n\n## Next-Step Routing\n\nAfter writing the artifact, recommend the next contextual game-pack skill in the final response as `Recommended next skill: \u003Ccommand>`.\n\nDefault recommendation: `\u002Fgame-fantasy`.\n\nIf prototype, playtest, or market evidence invalidates an upstream assumption, route back to the earliest affected artifact (`\u002Fgame-audience`, `\u002Fgame-fantasy`, `\u002Fgame-genre-map`, or `\u002Fgame-comparables`) and explain the evidence. Otherwise, follow the default game sequence:\n\n`\u002Fgame-audience` -> `\u002Fgame-fantasy` -> `\u002Fgame-genre-map` -> `\u002Fgame-comparables` -> `\u002Fgame-core-loop` -> `\u002Fgame-prototype-test` -> `\u002Fgame-playtest-metrics` -> `\u002Fgame-store-page-test` -> `\u002Fgame-launch` -> `\u002Fgame-roadmap`\n\nIf the next artifact already exists and is current, recommend `\u002Fgame-workflow` to identify the first missing or stale game-pack artifact.\n\n## Task Classification\n\nWhen this skill produces follow-up work, file it by execution semantics:\n\n- Immediately actionable implementation or documentation work goes in `tasks\u002Ftodo.md`.\n- Human-only external actions tied to automated steps go in `tasks\u002Fmanual-todo.md` with `_(blocks: Step N.X)_` or `_(after: Step N.X)_`; repo edits, SDK wiring, generated assets, local commands, tests, audits, and authenticated CLI\u002FAPI work stay in `tasks\u002Ftodo.md`.\n- One-time condition-gated records, baselines, or future measurements go in `tasks\u002Frecord-todo.md` with source, condition, non-blocking reason, evidence, and promotion rule.\n- Cadence-based reviews, playtests, adoption checks, investor updates, retros, or docs-health checks go in `tasks\u002Frecurring-todo.md` with cadence, owner\u002Fagent, next due, evidence path, and escalation conditions.\n- Do not put non-blocking records or recurring obligations in `tasks\u002Ftodo.md` unless they have been explicitly promoted into current execution work.\n\n## Context Gathering\n\n**Step 1 — Scope questions.** Before researching, ask the user 1–3 questions via `AskUserQuestion` to understand: their product\u002Fservice, target audience, and what they hope to learn or decide from this research.\n\n**Step 2 — Research.** Conduct research scoped by the user's answers.\n\n**Step 3 — Findings validation.** Before building the alignment page, present the 3–5 most important findings and ask the user to validate or correct any critical assumptions.\n\n## Alignment Page\n\nWhen this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page following `ALIGNMENT-PAGE.md` in this skill's directory. Output: `alignment\u002Fgame-audience-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n",{"name":5,"type":26,"version":41,"description":7,"visual_tier":33,"interview_depth":42},"v0.3","light","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fgame\u002Fclaude\u002Fgame-audience\u002Farchive\u002Fv0.3",0,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills","https:\u002F\u002Fagentic-skills-blush.vercel.app","https:\u002F\u002Fgithub.com\u002FGeorgeQLe","georgeqle.com","George Le is a futurist and serial tech entrepreneur who wants to work toward a world where humanity is free from robotic tasks.","2026-11-10 04:07:24",{"source":8,"skillName":5,"commands":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill game-audience",{"tool":59,"command":60},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill 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source-checkout-only fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fsource-checkout-allowed\u002FSKILL.md",[],[87,88,89,32,30,90],"source checkout allowed","checkout","fixture","valid",{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":36},"01M6G0NFZ3R1MNB1E3DVTM0WB7","deck-install-valid","Valid deck install fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fdeck-install\u002FSKILL.md",[],[98,99,100,90,89,30],"deck install 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