[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G080SFKS3A1FHEFS1485JH":3,"skill-same:01M6G080SFKS3A1FHEFS1485JH":64},{"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":33,"linkOnly":34,"markdownContent":35,"markdownBody":36,"frontMatter":37,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":43,"repositoryHtmlUrl":44,"repositoryHomepageUrl":45,"ownerHtmlUrl":46,"ownerBlogUrl":47,"ownerDescription":48,"updatedAt":49,"install":50,"resources":63},"01M6G080SFKS3A1FHEFS1485JH","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\u002Farchive\u002Fv0.1\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32],"youtube","diagnosis","cadence","youtube cadence diagnosis","performance","research","diagnose","v0","channel","evidence","publishing","peer","gap","post","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: v0.1\nargument-hint: \"\u003Cchannel slug or handle> [--peer \u003Cchannel>...] [--count N]\"\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 `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# YouTube Cadence Diagnosis\n\nInvoke as `$youtube-cadence-diagnosis`.\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\nQuantify publishing consistency, gap costs, and realistic cadence choices before turning strategy into a programming plan.\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## Workflow\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-Skill 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\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-cadence-diagnosis-{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 `$pack install \u003Cpack>` instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.\n\n# YouTube Cadence Diagnosis\n\nInvoke as `$youtube-cadence-diagnosis`.\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\nQuantify publishing consistency, gap costs, and realistic cadence choices before turning strategy into a programming plan.\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## Workflow\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-Skill 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\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-cadence-diagnosis-{topic}.html`.\n",{"name":5,"type":24,"version":38,"description":7,"argument-hint":39},"v0.1","\u003Cchannel slug or handle> [--peer \u003Cchannel>...] [--count N]","master","96e2912af886dd1606b1b97df707715aef062b02","packs\u002Fyoutube-ops\u002Fcodex\u002Fyoutube-cadence-diagnosis\u002Farchive\u002Fv0.1",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":51,"prompt":61,"zipAvailable":62},[52,55,58],{"tool":53,"command":54},"npx","npx skills add GeorgeQLe\u002Fagentic-skills --skill youtube-cadence-diagnosis",{"tool":56,"command":57},"bunx","bunx skills add GeorgeQLe\u002Fagentic-skills --skill 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