[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G0AKVCX46CTZ95D20KBCCP":3,"skill-same:01M6G0AKVCX46CTZ95D20KBCCP":75},{"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":26,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":54,"repositoryHtmlUrl":55,"repositoryHomepageUrl":56,"ownerHtmlUrl":57,"ownerBlogUrl":58,"ownerDescription":59,"updatedAt":60,"install":61,"resources":74},"01M6G0AKVCX46CTZ95D20KBCCP","youtube-concept-research",null,"Research a proposed YouTube video concept against successful direct and adjacent content, then extract evidence-backed lessons, concept variants, packaging directions, and differentiated execution guidance","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\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-concept-research\u002Farchive\u002Fv0.2\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"youtube concept research","youtube","research","extract","retention","guidance","evidence","packaging","channel","v0","direct","format","browse","Video","execution","content","search","2026-11-10 10:12:30",false,"---\nname: youtube-concept-research\ndescription: Research a proposed YouTube video concept against successful direct and adjacent content, then extract evidence-backed lessons, concept variants, packaging directions, and differentiated execution guidance\ntype: research\nversion: v0.2\nargument-hint: \"\\\"\u003Cvideo concept>\\\" [--channel \u003Cslug>] [--comparables N] [--angle search|browse|packaging|retention|format|all]\"\n---\n\n## Pack Availability Guard\n\nBefore telling the user to run a skill from another project-local pack, check `.agents\u002Fproject.json.enabled_packs`. If the target pack is not enabled, recommend `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# YouTube Concept Research\n\nInvoke as `$youtube-concept-research`.\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\nResearch a proposed YouTube video concept before scripting or production. Start from the user's idea, find successful direct and adjacent videos, explain what likely worked from public evidence, and translate the lessons into differentiated concept directions. Use `$youtube-competitive-research` when the user already has specific reference videos and wants to know why they worked. Use `$youtube-search-positioning` when the task is only keyword\u002Fsearch opportunity research.\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## Inputs\n\n- Required: a video concept, rough title, thesis, audience question, or topic idea.\n- Optional `--channel \u003Cslug>`: compare the concept against existing channel evidence under `research\u002Fyoutube\u002Fdata\u002F\u003Cslug>\u002F` and strategy artifacts such as channel audit, portfolio, peer benchmark, positioning, or programming.\n- Optional `--comparables N`: target number of comparable videos to inspect. Default 8, max 20.\n- Optional `--angle search|browse|packaging|retention|format|all`: default `all`.\n\n## Workflow\n\n1. Parse the concept into:\n   - audience job: problem, desire, identity, fear, curiosity, or aspiration served.\n   - content promise: what the viewer expects to learn, feel, decide, or see resolved.\n   - likely discovery mode: search, browse\u002Fhome, suggested, Shorts, or community\u002Ffandom.\n   - adjacent spaces: same topic, same audience job, same format, and counter-positioned angles.\n   - constraints: creator fit, product\u002Fbrand fit, production feasibility, and claims needing external verification.\n2. Build a query set. Include direct topic queries, problem\u002Fsearch-intent queries, browse-curiosity phrasings, adjacent-category analogs, and same-format\u002Fdifferent-niche examples.\n3. Find public comparable videos through YouTube search, available local tooling, or supplied URLs. Include:\n   - direct comparables on the same topic.\n   - audience-job comparables serving the same viewer need.\n   - format comparables with a transferable structure.\n   - counter-position comparables that prove a different angle can work.\n4. Require `yt-dlp` for public metadata when video URLs are selected:\n\n   ```bash\n   command -v yt-dlp\n   ```\n\n5. Select a transcript Python interpreter. Prefer a workspace-local `.venv`; create it if missing. Install `youtube-transcript-api` into `.venv` only when the import check fails and network access is available.\n6. Persist raw evidence under `research\u002Fyoutube\u002Fdata\u002F\u003Cvideo-id>\u002F`:\n   - `metadata-YYYY-MM-DD.json`: raw `yt-dlp --dump-json \"VIDEO_URL\"` output.\n   - `transcript\u002F\u003Cvideo-id>.json`: raw transcript JSON when available.\n   - `transcript\u002Ftranscript-summary.json`: transcript text or failure reason.\n   - `api\u002Fcomment-threads-YYYY-MM-DD.json`: optional public comments when an already-authorized API path is available.\n7. Score each comparable for usefulness, not just raw popularity:\n   - views\u002Fday or recent momentum.\n   - apparent outlier status relative to the channel when public channel evidence is available.\n   - title\u002Fthumbnail promise clarity.\n   - transcript\u002Fstructure evidence availability.\n   - audience overlap with the concept.\n   - discovery-mode fit.\n   - production feasibility for the user's channel.\n8. Analyze market lessons:\n   - Packaging: title pattern, thumbnail promise, specificity, stakes, novelty, expectation match, and avoidable clickbait.\n   - Search\u002Fbrowse fit: whether the concept should lean toward query satisfaction, curiosity, identity, trend, story, or suggested-video adjacency.\n   - Hook and retention: first 30-60 seconds, setup length, proof, tension loops, examples, pattern changes, payoff, and CTA.\n   - Format: essay, tutorial, teardown, case study, build-in-public, experiment, challenge, reaction, documentary, interview, Shorts, or hybrid.\n   - Audience signal: comment themes only when comments were captured; separate praise, objections, confusion, requests, and noise.\n9. Produce 3-5 concept variants. At minimum include the best search-led, browse-led, and differentiated\u002Fcounter-positioned variants when evidence supports them.\n10. Recommend one primary direction and explain what to adapt, avoid, or counter-position. If the evidence is weak, recommend the minimum follow-up research rather than over-committing.\n\n## Output\n\nCreate the `research\u002Fyoutube\u002F` and `research\u002Fyoutube\u002Fdata\u002F\u003Cvideo-id>\u002F` directories if they do not exist.\n\nWrite:\n\n```text\nresearch\u002Fyoutube\u002Fconcept-research-\u003Cslug>-YYYY-MM-DD.md\n```\n\nUse this structure:\n\n```markdown\n# YouTube Concept Research - [Concept]\n\n> Concept: [user concept]\n> Channel: [slug or not provided]\n> Date captured: YYYY-MM-DD\n> Evidence: [raw paths and search notes used]\n> Angle: search \u002F browse \u002F packaging \u002F retention \u002F format \u002F all\n\n## Evidence Coverage\n\n| Comparable | Type | Metadata | Transcript | Comments | Notes |\n|---|---|---|---|---|---|\n| [Title](URL) | Direct \u002F audience-job \u002F format \u002F counter-position | Available \u002F Missing | Available \u002F Missing | Available \u002F Missing \u002F Not requested | ... |\n\n## Concept Brief\n\n[Audience job, promise, likely discovery mode, constraints, and claims needing verification.]\n\n## Search And Discovery Map\n\n| Query \u002F surface | Intent | Evidence | Opportunity | Caveat |\n|---|---|---|---|---|\n| ... | Search \u002F browse \u002F suggested \u002F Shorts \u002F community | ... | ... | ... |\n\n## Comparable Performance Snapshot\n\n| Video | Published | Duration | Views | Likes | Comments | Views\u002Fday | Comparable value |\n|---|---|---:|---:|---:|---:|---:|---|\n| ... | ... | ... | ... | ... | ... | ... | Direct \u002F audience-job \u002F format \u002F counter-position |\n\n## Why These Videos Likely Worked\n\n1. [Hypothesis] - [public evidence]\n2. [Hypothesis] - [public evidence]\n3. [Hypothesis] - [public evidence]\n\n## Audience Jobs And Market Pattern\n\n[What viewers repeatedly respond to, what category promises are common, and what gaps remain.]\n\n## Packaging Lessons\n\n- **Title patterns**: ...\n- **Thumbnail promises**: ...\n- **Specificity and stakes**: ...\n- **Expectation match risks**: ...\n\n## Hook, Structure, And Retention Lessons\n\n- **Opening 30-60 seconds**: ...\n- **Proof and examples**: ...\n- **Tension \u002F payoff**: ...\n- **CTA \u002F ending**: ...\n\n## Concept Variants\n\n| Variant | Discovery mode | Core promise | Evidence | Risk | Recommendation |\n|---|---|---|---|---|---|\n| ... | Search \u002F browse \u002F suggested \u002F Shorts \u002F community | ... | ... | ... | ... |\n\n## Recommended Direction\n\n[Primary concept direction, why it is strongest, what to adapt, what to avoid, and how to differentiate.]\n\n## Title And Thumbnail Territories\n\n| Territory | Example title pattern | Thumbnail direction | Evidence | Risk |\n|---|---|---|---|---|\n| ... | ... | ... | ... | ... |\n\n## Draft Video Architecture\n\n[High-level outline only: hook, setup, proof\u002Fexamples, turn, payoff, CTA. Do not write a full script unless explicitly asked.]\n\n## Risks Of Copying\n\n[What would be derivative, off-brand, unsupported by evidence, or risky to imitate.]\n\n## Open Questions And Evidence Gaps\n\n[Missing transcript, missing comments, uncertain search demand, absent owner analytics, private metrics unavailable, or factual claims needing independent verification.]\n```\n\n## Constraints\n\n- Separate observed public evidence from performance hypotheses and recommendations.\n- Do not treat public views as proof of CTR, retention, satisfaction, revenue, subscriber conversion, or profitability.\n- Do not infer private YouTube Studio metrics unless the user provides them.\n- Do not optimize only for clicks; evaluate title\u002Fthumbnail promise against likely watch-time and expectation match.\n- Do not invent metrics, transcripts, comments, thumbnail details, rankings, or distribution causes.\n- Do not recommend copying another creator's title, thumbnail, hook, format identity, or brand. Translate lessons into differentiated execution.\n- Date every search\u002Franking observation and state personalization, geography, and account caveats.\n- When the concept relies on factual, legal, medical, financial, political, or current-event claims, recommend independent source verification outside YouTube.\n- Do not bypass login walls, bot protections, access controls, or private YouTube Studio data.\n- Archive existing canonical artifacts before replacing them under `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-relative-path>`.\n\n## Approved Artifact Handoff\n\nAfter an approved synthesized write, explicit write\u002Fupdate mode, or any direct artifact mutation:\n\n- List every created or updated synthesized artifact path in the final response.\n- State the verification performed, such as readback, schema\u002Fcheck command, or why no executable verification applies for a Markdown-only strategy artifact.\n- Check and report the relevant git status for intended artifacts when the project is a git repository. If intended artifacts are modified or untracked, make the next action shipping, committing, or an explicit dirty-artifact handoff before recommending downstream strategy work.\n- Do not imply the research workflow is complete while approved artifacts remain untracked or uncommitted unless the user explicitly asked not to ship.\n- If stopping for approval before writing, the approval request remains the next action; do not include downstream routing.\n\n## Intent-Aware Routing\n\nBefore applying the default `## Next-Skill Routing` sequence, classify the user's immediate intent and route to the missing action that best serves that intent:\n\n- Strategy refresh: recommend the missing or stale positioning, programming, portfolio, metrics, or product-media artifact.\n- Recording prep: recommend the missing series spec, script, build proof, walkthrough guide, or validation artifact needed before recording.\n- Upload prep: recommend packaging, title\u002Fthumbnail, description, chapters, or final metadata work before broader strategy work.\n- Performance review: recommend metrics, cadence, portfolio, peer benchmark, or owner-analytics export work before new content planning.\n- Owner analytics or private\u002Fmanual platform evidence: route to an explicit manual\u002Fguide handoff instead of inventing unavailable metrics.\n- Dirty intended artifacts: route to shipping\u002Fcommit\u002Fhandoff first, not another creator strategy skill.\n\nUse the default next-skill sequence only when no stronger user intent, missing artifact, manual blocker, or dirty-artifact handoff applies.\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\u002Fyoutube-concept-research-{topic}.html`.\n","## Pack Availability Guard\n\nBefore telling the user to run a skill from another project-local pack, check `.agents\u002Fproject.json.enabled_packs`. If the target pack is not enabled, recommend `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# YouTube Concept Research\n\nInvoke as `$youtube-concept-research`.\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\nResearch a proposed YouTube video concept before scripting or production. Start from the user's idea, find successful direct and adjacent videos, explain what likely worked from public evidence, and translate the lessons into differentiated concept directions. Use `$youtube-competitive-research` when the user already has specific reference videos and wants to know why they worked. Use `$youtube-search-positioning` when the task is only keyword\u002Fsearch opportunity research.\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## Inputs\n\n- Required: a video concept, rough title, thesis, audience question, or topic idea.\n- Optional `--channel \u003Cslug>`: compare the concept against existing channel evidence under `research\u002Fyoutube\u002Fdata\u002F\u003Cslug>\u002F` and strategy artifacts such as channel audit, portfolio, peer benchmark, positioning, or programming.\n- Optional `--comparables N`: target number of comparable videos to inspect. Default 8, max 20.\n- Optional `--angle search|browse|packaging|retention|format|all`: default `all`.\n\n## Workflow\n\n1. Parse the concept into:\n   - audience job: problem, desire, identity, fear, curiosity, or aspiration served.\n   - content promise: what the viewer expects to learn, feel, decide, or see resolved.\n   - likely discovery mode: search, browse\u002Fhome, suggested, Shorts, or community\u002Ffandom.\n   - adjacent spaces: same topic, same audience job, same format, and counter-positioned angles.\n   - constraints: creator fit, product\u002Fbrand fit, production feasibility, and claims needing external verification.\n2. Build a query set. Include direct topic queries, problem\u002Fsearch-intent queries, browse-curiosity phrasings, adjacent-category analogs, and same-format\u002Fdifferent-niche examples.\n3. Find public comparable videos through YouTube search, available local tooling, or supplied URLs. Include:\n   - direct comparables on the same topic.\n   - audience-job comparables serving the same viewer need.\n   - format comparables with a transferable structure.\n   - counter-position comparables that prove a different angle can work.\n4. Require `yt-dlp` for public metadata when video URLs are selected:\n\n   ```bash\n   command -v yt-dlp\n   ```\n\n5. Select a transcript Python interpreter. Prefer a workspace-local `.venv`; create it if missing. Install `youtube-transcript-api` into `.venv` only when the import check fails and network access is available.\n6. Persist raw evidence under `research\u002Fyoutube\u002Fdata\u002F\u003Cvideo-id>\u002F`:\n   - `metadata-YYYY-MM-DD.json`: raw `yt-dlp --dump-json \"VIDEO_URL\"` output.\n   - `transcript\u002F\u003Cvideo-id>.json`: raw transcript JSON when available.\n   - `transcript\u002Ftranscript-summary.json`: transcript text or failure reason.\n   - `api\u002Fcomment-threads-YYYY-MM-DD.json`: optional public comments when an already-authorized API path is available.\n7. Score each comparable for usefulness, not just raw popularity:\n   - views\u002Fday or recent momentum.\n   - apparent outlier status relative to the channel when public channel evidence is available.\n   - title\u002Fthumbnail promise clarity.\n   - transcript\u002Fstructure evidence availability.\n   - audience overlap with the concept.\n   - discovery-mode fit.\n   - production feasibility for the user's channel.\n8. Analyze market lessons:\n   - Packaging: title pattern, thumbnail promise, specificity, stakes, novelty, expectation match, and avoidable clickbait.\n   - Search\u002Fbrowse fit: whether the concept should lean toward query satisfaction, curiosity, identity, trend, story, or suggested-video adjacency.\n   - Hook and retention: first 30-60 seconds, setup length, proof, tension loops, examples, pattern changes, payoff, and CTA.\n   - Format: essay, tutorial, teardown, case study, build-in-public, experiment, challenge, reaction, documentary, interview, Shorts, or hybrid.\n   - Audience signal: comment themes only when comments were captured; separate praise, objections, confusion, requests, and noise.\n9. Produce 3-5 concept variants. At minimum include the best search-led, browse-led, and differentiated\u002Fcounter-positioned variants when evidence supports them.\n10. Recommend one primary direction and explain what to adapt, avoid, or counter-position. If the evidence is weak, recommend the minimum follow-up research rather than over-committing.\n\n## Output\n\nCreate the `research\u002Fyoutube\u002F` and `research\u002Fyoutube\u002Fdata\u002F\u003Cvideo-id>\u002F` directories if they do not exist.\n\nWrite:\n\n```text\nresearch\u002Fyoutube\u002Fconcept-research-\u003Cslug>-YYYY-MM-DD.md\n```\n\nUse this structure:\n\n```markdown\n# YouTube Concept Research - [Concept]\n\n> Concept: [user concept]\n> Channel: [slug or not provided]\n> Date captured: YYYY-MM-DD\n> Evidence: [raw paths and search notes used]\n> Angle: search \u002F browse \u002F packaging \u002F retention \u002F format \u002F all\n\n## Evidence Coverage\n\n| Comparable | Type | Metadata | Transcript | Comments | Notes |\n|---|---|---|---|---|---|\n| [Title](URL) | Direct \u002F audience-job \u002F format \u002F counter-position | Available \u002F Missing | Available \u002F Missing | Available \u002F Missing \u002F Not requested | ... |\n\n## Concept Brief\n\n[Audience job, promise, likely discovery mode, constraints, and claims needing verification.]\n\n## Search And Discovery Map\n\n| Query \u002F surface | Intent | Evidence | Opportunity | Caveat |\n|---|---|---|---|---|\n| ... | Search \u002F browse \u002F suggested \u002F Shorts \u002F community | ... | ... | ... |\n\n## Comparable Performance Snapshot\n\n| Video | Published | Duration | Views | Likes | Comments | Views\u002Fday | Comparable value |\n|---|---|---:|---:|---:|---:|---:|---|\n| ... | ... | ... | ... | ... | ... | ... | Direct \u002F audience-job \u002F format \u002F counter-position |\n\n## Why These Videos Likely Worked\n\n1. [Hypothesis] - [public evidence]\n2. [Hypothesis] - [public evidence]\n3. [Hypothesis] - [public evidence]\n\n## Audience Jobs And Market Pattern\n\n[What viewers repeatedly respond to, what category promises are common, and what gaps remain.]\n\n## Packaging Lessons\n\n- **Title patterns**: ...\n- **Thumbnail promises**: ...\n- **Specificity and stakes**: ...\n- **Expectation match risks**: ...\n\n## Hook, Structure, And Retention Lessons\n\n- **Opening 30-60 seconds**: ...\n- **Proof and examples**: ...\n- **Tension \u002F payoff**: ...\n- **CTA \u002F ending**: ...\n\n## Concept Variants\n\n| Variant | Discovery mode | Core promise | Evidence | Risk | Recommendation |\n|---|---|---|---|---|---|\n| ... | Search \u002F browse \u002F suggested \u002F Shorts \u002F community | ... | ... | ... | ... |\n\n## Recommended Direction\n\n[Primary concept direction, why it is strongest, what to adapt, what to avoid, and how to differentiate.]\n\n## Title And Thumbnail Territories\n\n| Territory | Example title pattern | Thumbnail direction | Evidence | Risk |\n|---|---|---|---|---|\n| ... | ... | ... | ... | ... |\n\n## Draft Video Architecture\n\n[High-level outline only: hook, setup, proof\u002Fexamples, turn, payoff, CTA. Do not write a full script unless explicitly asked.]\n\n## Risks Of Copying\n\n[What would be derivative, off-brand, unsupported by evidence, or risky to imitate.]\n\n## Open Questions And Evidence Gaps\n\n[Missing transcript, missing comments, uncertain search demand, absent owner analytics, private metrics unavailable, or factual claims needing independent verification.]\n```\n\n## Constraints\n\n- Separate observed public evidence from performance hypotheses and recommendations.\n- Do not treat public views as proof of CTR, retention, satisfaction, revenue, subscriber conversion, or profitability.\n- Do not infer private YouTube Studio metrics unless the user provides them.\n- Do not optimize only for clicks; evaluate title\u002Fthumbnail promise against likely watch-time and expectation match.\n- Do not invent metrics, transcripts, comments, thumbnail details, rankings, or distribution causes.\n- Do not recommend copying another creator's title, thumbnail, hook, format identity, or brand. Translate lessons into differentiated execution.\n- Date every search\u002Franking observation and state personalization, geography, and account caveats.\n- When the concept relies on factual, legal, medical, financial, political, or current-event claims, recommend independent source verification outside YouTube.\n- Do not bypass login walls, bot protections, access controls, or private YouTube Studio data.\n- Archive existing canonical artifacts before replacing them under `docs\u002Fhistory\u002Farchive\u002FYYYY-MM-DD\u002FHHMMSS\u002F\u003Coriginal-relative-path>`.\n\n## Approved Artifact Handoff\n\nAfter an approved synthesized write, explicit write\u002Fupdate mode, or any direct artifact mutation:\n\n- List every created or updated synthesized artifact path in the final response.\n- State the verification performed, such as readback, schema\u002Fcheck command, or why no executable verification applies for a Markdown-only strategy artifact.\n- Check and report the relevant git status for intended artifacts when the project is a git repository. If intended artifacts are modified or untracked, make the next action shipping, committing, or an explicit dirty-artifact handoff before recommending downstream strategy work.\n- Do not imply the research workflow is complete while approved artifacts remain untracked or uncommitted unless the user explicitly asked not to ship.\n- If stopping for approval before writing, the approval request remains the next action; do not include downstream routing.\n\n## Intent-Aware Routing\n\nBefore applying the default `## Next-Skill Routing` sequence, classify the user's immediate intent and route to the missing action that best serves that intent:\n\n- Strategy refresh: recommend the missing or stale positioning, programming, portfolio, metrics, or product-media artifact.\n- Recording prep: recommend the missing series spec, script, build proof, walkthrough guide, or validation artifact needed before recording.\n- Upload prep: recommend packaging, title\u002Fthumbnail, description, chapters, or final metadata work before broader strategy work.\n- Performance review: recommend metrics, cadence, portfolio, peer benchmark, or owner-analytics export work before new content planning.\n- Owner analytics or private\u002Fmanual platform evidence: route to an explicit manual\u002Fguide handoff instead of inventing unavailable metrics.\n- Dirty intended artifacts: route to shipping\u002Fcommit\u002Fhandoff first, not another creator strategy skill.\n\nUse the default next-skill sequence only when no stronger user intent, missing artifact, manual blocker, or dirty-artifact handoff applies.\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\u002Fyoutube-concept-research-{topic}.html`.\n",{"name":5,"type":29,"version":49,"description":7,"argument-hint":50},"v0.2","\"\u003Cvideo concept>\" [--channel \u003Cslug>] [--comparables N] [--angle search|browse|packaging|retention|format|all]","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-concept-research\u002Farchive\u002Fv0.2",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":62,"prompt":72,"zipAvailable":73},[63,66,69],{"tool":64,"command":65},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-concept-research",{"tool":67,"command":68},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-concept-research",{"tool":70,"command":71},"pnpm","pnpm dlx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-concept-research","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-concept-research\u002Farchive\u002Fv0.2\u002FSKILL.md",true,[],[76,88,98,110,123,134],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":44},"01M6G0NJES15RJKZE6YZ0TSYGF","source-checkout-allowed","Valid source-checkout-only fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fsource-checkout-allowed\u002FSKILL.md",[],[83,84,85,86,36,87],"source checkout allowed","checkout","fixture","only","valid",{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":44},"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",[],[95,96,97,87,85,36],"deck install valid","deck","install",{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":104,"publishedAt":44},"01M6G0ND3QZQC4MDZ9NVB97PT2","codex-pack-guard-valid","Valid Codex Pack Availability Guard fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-pack-guard\u002FSKILL.md",[],[105,106,107,87,108,109,85,36],"codex pack guard valid","pack","guard","codex","availability",{"skillNo":111,"name":112,"nameZh":6,"description":113,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":114,"categories":115,"keywords":119,"publishedAt":44},"01M6G0NA9YB3NKGZKD3S96JMNB","codex-missing-skill-valid","Valid Codex missing skill fallback fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-missing-skill-fallback\u002FSKILL.md",[116],{"categoryNo":117,"categoryName":118,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[120,121,87,108,36,122,85],"codex missing skill valid","missing","fallback",{"skillNo":124,"name":125,"nameZh":6,"description":126,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":127,"categories":128,"keywords":130,"publishedAt":44},"01M6G0N7PC0EKFD40ZWQAXSAQ9","codex-base-skill-fallback-valid","Valid Codex base skill fallback fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fcodex-base-skill-fallback\u002FSKILL.md",[129],{"categoryNo":117,"categoryName":118,"taxonomyType":21,"taxonomyTypeDesc":22},[87,108,122,131,132,133,36,85],"base skill","codex base skill fallback valid","base",{"skillNo":135,"name":136,"nameZh":6,"description":137,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":138,"categories":139,"keywords":140,"publishedAt":44},"01M6G0N4VRR2YKZQ6N3Y6S2BQA","claude-pack-guard-valid","Valid Claude Pack Availability Guard fixture.","https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Ftests\u002Ffixtures\u002Fskill-install-routing\u002Fvalid\u002Fclaude-pack-guard\u002FSKILL.md",[],[87,107,106,141,109,36,85],"claude pack guard valid"]