[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G07Q59KBC67BAJ13QAPP38":3,"skill-same:01M6G07Q59KBC67BAJ13QAPP38":87},{"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":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":53,"commitSha":54,"skillDirectory":55,"forksCount":56,"repositoryHtmlUrl":57,"repositoryHomepageUrl":58,"ownerHtmlUrl":59,"ownerBlogUrl":60,"ownerDescription":61,"updatedAt":62,"install":63,"resources":76},"01M6G07Q59KBC67BAJ13QAPP38","youtube-cadence-diagnosis",null,"Diagnose YouTube publishing cadence, gaps, streaks, and post-gap performance effects against channel and peer evidence","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-cadence-diagnosis\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"youtube cadence diagnosis","cadence","diagnosis","youtube","alignment","post","gap","visual","artifact","peer","performance","publishing","evidence","only","channel","v0","page","diagnose","research","2026-11-10 10:12:30",false,"---\nname: youtube-cadence-diagnosis\ndescription: Diagnose YouTube publishing cadence, gaps, streaks, and post-gap performance effects against channel and peer evidence\ntype: research\nversion: v0.6\nrequired_conventions: [alignment-page]\nargument-hint: \"\u003Cchannel slug or handle> [--peer \u003Cchannel>...] [--count N]\"\ncontext_intake: artifact_only\nvisual_tier: visual\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 `npx skillpacks install \u003Cpack>` instead of the target skill. Only the currently running skill and skills verified available in the active session or project-local install state are directly recommendable. For unavailable pack skills, recommend `npx skillpacks install \u003Cpack-or-skill>`; for unavailable base skills, recommend `npx skillpacks init` before the skill.\n\n# YouTube Cadence Diagnosis\n\nInvoke as `$youtube-cadence-diagnosis`.\n\n## Report-First Approval Gate\n\nDefault to scope-first approval: before synthesized research, inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions in a `review` alignment page plus a concise conversation summary.\n\nDo not perform synthesized research, rank candidates, make recommendations, or write working packets or canonical deliverables until final compiled YAML approves the research scope. Minimal pre-approval discovery may identify available files, source categories, and open questions; label it as scope evidence, not findings.\n\nAfter approved research-scope YAML, perform the research and write only the non-canonical working packet defined in the staged workflow. Then update the `review` alignment page with findings and stop again for feedback-only YAML or final compiled YAML artifact approval before creating or updating canonical research, spec, or task files.\n\nDo 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 - Scope discovery and approval.** Inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions. Build the `review` HTML alignment page before synthesized research. The page must render the proposed scope, available source categories, known context, assumptions\u002Fconfidence, proposed working-packet and canonical output paths, and research-scope approval gates. Stop for final compiled YAML approval of the research scope. Do not perform synthesized research, rank candidates, make recommendations, or write working packets, canonical research, spec, or task files in Stage 1.\n2. **Stage 2 - Research and artifact review.** Only after approved research-scope YAML with no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback, perform the synthesized research, run required source\u002Fcode checks, and 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. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet. Update the `review` HTML alignment page so it renders the complete working-packet substance as structured HTML review UI: purpose-built sections, tables, matrices, gates, cards, and tier-appropriate charts or diagrams that preserve every packet section, finding, caveat, and decision detail without summary loss. Raw Markdown packet text may appear only as a supplemental source view after the rendered review UI; do not make a `Full Preliminary Packet` or `Full Working Packet` raw Markdown dump, giant `\u003Cpre>\u003Ccode>` block, link-only view, or source-only view the primary review surface. Include the evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and artifact 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 for artifact approval 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\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- `research\u002Fyoutube\u002Fchannel-audit-\u003Cslug>.md`\n- `research\u002Fyoutube\u002Fdata\u002F\u003Cslug>\u002Fvideos-*.jsonl`\n- Optional `research\u002Fyoutube\u002Fpeer-benchmark-\u003Cslug>.md`\n- Optional peer raw metadata under `research\u002Fyoutube\u002Fdata\u002F\u003Cpeer-slug>\u002F`\n\n## Process\n\n1. Require a channel slug, handle, or channel audit path.\n2. Ensure raw upload metadata exists. If not, run `$youtube-channel-audit \u003Cchannel> [--count N]`.\n3. Parse publish dates, views, views\u002Fday, content roles, and video archetypes from raw metadata.\n4. Compute upload intervals, streaks, longest gaps, rolling 30\u002F60\u002F90-day publish counts, and current streak status.\n5. Compare pre-gap and post-gap performance while controlling for topic, video age, and outlier videos where the evidence allows it.\n6. Compare cadence against stage-matched peers when peer metadata exists.\n7. Decide whether the data points to frequency, topic selection, packaging, or production quality as the more likely bottleneck.\n8. Write `research\u002Fyoutube\u002Fcadence-diagnosis-\u003Cslug>.md`.\n\nCreate the `research\u002Fyoutube\u002F` directory if it does not exist.\n\n## Report Sections\n\n- Evidence coverage: videos analyzed, date range, peer coverage, and missing fields.\n- Upload timeline: chronological table with intervals, gaps, topics, roles, and views\u002Fday.\n- Cadence metrics: median interval, longest gaps, streaks, rolling publish counts, and current streak.\n- Gap analysis: pre-gap baseline, post-gap performance, outlier handling, and confidence level.\n- Peer cadence benchmark: publish frequency and consistency compared with comparable channels.\n- Bottleneck diagnosis: cadence vs topic vs packaging vs production constraints.\n- Practical cadence recommendation: minimum viable cadence, stretch cadence, batching options, and warning signs.\n- Strategic programming implication.\n\n## Constraints\n\n- Do not claim causation when the evidence only supports correlation.\n- Always name confounders such as topic mix, video age, search seasonality, and packaging changes.\n- Use exact dates and intervals.\n- Keep recommendations realistic for solo or small-team production unless evidence shows otherwise.\n- Route the resulting rhythm into `$content-programming`.\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## Next-Step Routing\n\nAfter writing the artifact, recommend the next contextual creator-media skill in the final response as `Recommended next skill: \u003Ccommand>`.\n\nDefault recommendation: `$creator-positioning`.\n\nIf the default successor already exists and is current, recommend the first missing or stale downstream creator-media artifact in this order:\n\n`$youtube-channel-audit` -> `$youtube-video-audit` -> `$youtube-vid-research` -> `$youtube-concept-research` -> `$youtube-competitive-research` -> `$youtube-title-thumbnail-audit` -> `$youtube-description-optimizer` -> `$youtube-portfolio` -> `$youtube-peer-benchmark` -> `$youtube-search-positioning` -> `$youtube-cadence-diagnosis` -> `$creator-positioning` -> `$content-programming` -> `$series-spec` -> `$product-led-media-map` -> `$creator-metrics-review`\n\nIf the sequence is ambiguous, multiple upstream artifacts are stale, or the recommendation depends on channel-level strategy vs programming-level changes, recommend `$creator-metrics-review` when metrics evidence exists, otherwise recommend the default successor and explain the missing artifact.\n\n## Alignment Page\n\nFollow the shared alignment-page convention via the packaged convention resolver; output path is `alignment\u002Fyoutube-cadence-diagnosis-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n\n","## Pack Availability Guard\n\nBefore telling the user to run a skill from another project-local pack, check `.agents\u002Fproject.json.enabled_packs`. If the target pack is not enabled, recommend `npx skillpacks install \u003Cpack>` instead of the target skill. Only the currently running skill and skills verified available in the active session or project-local install state are directly recommendable. For unavailable pack skills, recommend `npx skillpacks install \u003Cpack-or-skill>`; for unavailable base skills, recommend `npx skillpacks init` before the skill.\n\n# YouTube Cadence Diagnosis\n\nInvoke as `$youtube-cadence-diagnosis`.\n\n## Report-First Approval Gate\n\nDefault to scope-first approval: before synthesized research, inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions in a `review` alignment page plus a concise conversation summary.\n\nDo not perform synthesized research, rank candidates, make recommendations, or write working packets or canonical deliverables until final compiled YAML approves the research scope. Minimal pre-approval discovery may identify available files, source categories, and open questions; label it as scope evidence, not findings.\n\nAfter approved research-scope YAML, perform the research and write only the non-canonical working packet defined in the staged workflow. Then update the `review` alignment page with findings and stop again for feedback-only YAML or final compiled YAML artifact approval before creating or updating canonical research, spec, or task files.\n\nDo 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 - Scope discovery and approval.** Inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions. Build the `review` HTML alignment page before synthesized research. The page must render the proposed scope, available source categories, known context, assumptions\u002Fconfidence, proposed working-packet and canonical output paths, and research-scope approval gates. Stop for final compiled YAML approval of the research scope. Do not perform synthesized research, rank candidates, make recommendations, or write working packets, canonical research, spec, or task files in Stage 1.\n2. **Stage 2 - Research and artifact review.** Only after approved research-scope YAML with no unresolved `needs-clarification`, unresolved `down` feedback, or other unresolved negative feedback, perform the synthesized research, run required source\u002Fcode checks, and 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. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet. Update the `review` HTML alignment page so it renders the complete working-packet substance as structured HTML review UI: purpose-built sections, tables, matrices, gates, cards, and tier-appropriate charts or diagrams that preserve every packet section, finding, caveat, and decision detail without summary loss. Raw Markdown packet text may appear only as a supplemental source view after the rendered review UI; do not make a `Full Preliminary Packet` or `Full Working Packet` raw Markdown dump, giant `\u003Cpre>\u003Ccode>` block, link-only view, or source-only view the primary review surface. Include the evidence matrix, assumptions\u002Fconfidence register, source coverage gaps, proposed canonical file changes, and artifact 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 for artifact approval 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\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- `research\u002Fyoutube\u002Fchannel-audit-\u003Cslug>.md`\n- `research\u002Fyoutube\u002Fdata\u002F\u003Cslug>\u002Fvideos-*.jsonl`\n- Optional `research\u002Fyoutube\u002Fpeer-benchmark-\u003Cslug>.md`\n- Optional peer raw metadata under `research\u002Fyoutube\u002Fdata\u002F\u003Cpeer-slug>\u002F`\n\n## Process\n\n1. Require a channel slug, handle, or channel audit path.\n2. Ensure raw upload metadata exists. If not, run `$youtube-channel-audit \u003Cchannel> [--count N]`.\n3. Parse publish dates, views, views\u002Fday, content roles, and video archetypes from raw metadata.\n4. Compute upload intervals, streaks, longest gaps, rolling 30\u002F60\u002F90-day publish counts, and current streak status.\n5. Compare pre-gap and post-gap performance while controlling for topic, video age, and outlier videos where the evidence allows it.\n6. Compare cadence against stage-matched peers when peer metadata exists.\n7. Decide whether the data points to frequency, topic selection, packaging, or production quality as the more likely bottleneck.\n8. Write `research\u002Fyoutube\u002Fcadence-diagnosis-\u003Cslug>.md`.\n\nCreate the `research\u002Fyoutube\u002F` directory if it does not exist.\n\n## Report Sections\n\n- Evidence coverage: videos analyzed, date range, peer coverage, and missing fields.\n- Upload timeline: chronological table with intervals, gaps, topics, roles, and views\u002Fday.\n- Cadence metrics: median interval, longest gaps, streaks, rolling publish counts, and current streak.\n- Gap analysis: pre-gap baseline, post-gap performance, outlier handling, and confidence level.\n- Peer cadence benchmark: publish frequency and consistency compared with comparable channels.\n- Bottleneck diagnosis: cadence vs topic vs packaging vs production constraints.\n- Practical cadence recommendation: minimum viable cadence, stretch cadence, batching options, and warning signs.\n- Strategic programming implication.\n\n## Constraints\n\n- Do not claim causation when the evidence only supports correlation.\n- Always name confounders such as topic mix, video age, search seasonality, and packaging changes.\n- Use exact dates and intervals.\n- Keep recommendations realistic for solo or small-team production unless evidence shows otherwise.\n- Route the resulting rhythm into `$content-programming`.\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## Next-Step Routing\n\nAfter writing the artifact, recommend the next contextual creator-media skill in the final response as `Recommended next skill: \u003Ccommand>`.\n\nDefault recommendation: `$creator-positioning`.\n\nIf the default successor already exists and is current, recommend the first missing or stale downstream creator-media artifact in this order:\n\n`$youtube-channel-audit` -> `$youtube-video-audit` -> `$youtube-vid-research` -> `$youtube-concept-research` -> `$youtube-competitive-research` -> `$youtube-title-thumbnail-audit` -> `$youtube-description-optimizer` -> `$youtube-portfolio` -> `$youtube-peer-benchmark` -> `$youtube-search-positioning` -> `$youtube-cadence-diagnosis` -> `$creator-positioning` -> `$content-programming` -> `$series-spec` -> `$product-led-media-map` -> `$creator-metrics-review`\n\nIf the sequence is ambiguous, multiple upstream artifacts are stale, or the recommendation depends on channel-level strategy vs programming-level changes, recommend `$creator-metrics-review` when metrics evidence exists, otherwise recommend the default successor and explain the missing artifact.\n\n## Alignment Page\n\nFollow the shared alignment-page convention via the packaged convention resolver; output path is `alignment\u002Fyoutube-cadence-diagnosis-{topic}.html`.\n\n## Default Shipping Contract\n\nFollow the shared shipping contract convention in CLAUDE.md.\n\n",{"name":5,"type":42,"version":48,"description":7,"visual_tier":31,"argument-hint":49,"context_intake":50,"required_conventions":51},"v0.6","\u003Cchannel slug or handle> [--peer \u003Cchannel>...] [--count N]","artifact_only",[52],"alignment-page","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-cadence-diagnosis",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":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-cadence-diagnosis",{"tool":69,"command":70},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-cadence-diagnosis",{"tool":72,"command":73},"pnpm","pnpm dlx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-cadence-diagnosis","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-cadence-diagnosis\u002FSKILL.md",true,[77,83],{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"ALIGNMENT-PAGE.md","REFERENCE","参考文档",54207,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-cadence-diagnosis\u002FALIGNMENT-PAGE.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"CHANGELOG.md",1281,"https:\u002F\u002Fgithub.com\u002FGeorgeQLe\u002Fagentic-skills\u002Fblob\u002Fmaster\u002Fpacks\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-cadence-diagnosis\u002FCHANGELOG.md",[88,99,109,121,134,145],{"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":43},"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",[],[95,96,97,37,39,98],"source checkout allowed","checkout","fixture","valid",{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":43},"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",[],[106,107,108,98,97,39],"deck install 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