[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ME6NPFZ85ZDA4R0P2T2ZGA":3,"skill-same:01M6ME6NPFZ85ZDA4R0P2T2ZGA":63},{"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":34,"linkOnly":35,"markdownContent":36,"markdownBody":37,"frontMatter":38,"refName":39,"commitSha":40,"skillDirectory":41,"forksCount":42,"repositoryHtmlUrl":43,"repositoryHomepageUrl":44,"ownerHtmlUrl":45,"ownerBlogUrl":46,"ownerDescription":47,"updatedAt":48,"install":49,"resources":62},"01M6ME6NPFZ85ZDA4R0P2T2ZGA","compare-shows",null,"Use Arcmira to compare two YouTube channels or podcasts on YouTube: size, latest episode, topics, overlap and shared sponsors. For rival research.","hashgraph-online\u002Fawesome-codex-plugins","hashgraph-online","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160371962?v=4","01M6CNB6NRJVNNGN14TR01Q6D3","HOL (Hashgraph Online)","01M6JT1HSKKG9V68KQAQGBA7XP",1559,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Farcmira\u002Fmcp\u002Fskills\u002Fcompare-shows\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"compare","compare shows","shared","youtube","size","about","latest","cover","arcmira","for","use","channels","research","topics","youtube channels","2026-11-10 10:12:30",false,"---\nname: compare-shows\ndescription: \"Use Arcmira to compare two YouTube channels or podcasts on YouTube: size, latest episode, topics, overlap and shared sponsors. For rival research.\"\n---\n\n# Compare two shows\n\n`status` sizes each show, `episodes` gives the latest, `occurrences` with both channel ids ranks what each covers and returns `shared` for what both mention, and `sponsors` of each, joined on entity id, gives shared sponsors.\n\nRun each program with `arcmira_execute_read`; `arcmira_describe` has the method reference.\n\n## When to use\n\nUse Arcmira when the user asks:\n\n- compare two shows, or a show against a competitor\n- what two podcasts both talk about, or who they both advertise\n- a digest of what one or two shows covered this week or month\n\n## Pick the entity the user meant\n\nUsers give names; filters take ids only (ent_..., UC..., 11-character video ids), and a name where an id belongs throws `id_required`.\n\n1. Resolve the exact name the user said, with their own words about it as `context` (a bare \"Theo\" has none).\n2. `best` and `suggested` give the id. A `suggested` pick is an assumption: the answer names it, with `suggested.evidence` as the reason.\n3. `ask`: several entities fit, and `ask.options` goes back to the user. No answer at all: the name is not in the index.\n\nFor this task:\n\n- Resolve each show with `{ type: \"channel\" }` and use `youtube_channel_id`. Users shorten show names (\"All In\", \"MTS\"); resolve suggests a show by its initials or closest spelling, so say when a show was assumed. When nothing comes back, retry the full or hyphenated name before saying the show is not in the index.\n- Pass both UC ids in one `occurrences` call and read `shared`.\n\n## Worked program\n\nPass each block to `arcmira_execute_read` as one program (a block marked arcmira_execute_write goes to that tool), with the name swapped for the user's. It opens with the pick: set `CONTEXT` to the user's own words about the name. When several entities fit it returns `ask` and runs nothing else. Show those options to the user, then run it again with `ID` set to the pick. Build date windows from `arcmira.daysAgo(n)` and `arcmira.today()`.\n\n### Two shows, last 90 days\n\n```javascript\nconst SHOWS = [\"TBPN\", \"All-In Podcast\"], IDS = [null, null];   \u002F\u002F after an ask, put the picked option's channel_id in IDS and run again\nconst ids = [], names = [], assumed = [];\nfor (const [i, n] of SHOWS.entries()) {\n  if (IDS[i]) { ids.push(IDS[i]); names.push(n); assumed.push(null); continue; }\n  const r = await arcmira.resolve(n, { type: \"channel\" });\n  const e = r.best ?? r.suggested;\n  if (!e) return { unresolved: n, ask: r.ask && { question: r.ask.question, options: r.ask.options.map(o => ({ ...o, channel_id: r.candidates.find(c => c.id === o.id)?.youtube_channel_id ?? null })) } };\n  ids.push(e.youtube_channel_id);\n  names.push(e.name);\n  assumed.push(r.suggested ? r.suggested.evidence : null);\n}\nconst after = arcmira.daysAgo(90);\nconst [s0, s1, e0, e1, occ, sp0, sp1] = await Promise.all([\n  arcmira.status({ channelId: ids[0] }), arcmira.status({ channelId: ids[1] }),\n  arcmira.episodes(ids[0], { limit: 1 }), arcmira.episodes(ids[1], { limit: 1 }),\n  arcmira.occurrences({ channelIds: ids, types: [\"organization\", \"product\"], after, limit: 40 }),\n  arcmira.sponsors(ids[0]), arcmira.sponsors(ids[1]),\n]);\nconst inOther = new Map(sp1.sponsors.map(x => [x.entity.id, x.ad_reads]));\nreturn {\n  window: occ.window,\n  shows: ids.map((id, i) => ({ name: names[i], channel_id: id, assumed: Boolean(assumed[i]), why: assumed[i], videos_indexed: [s0, s1][i].channel.searchable_videos, indexed_through: [s0, s1][i].channel.indexed_through, latest: [e0, e1][i].episodes[0]?.title ?? null,\n    top: occ.rows.filter(x => x.channel_id === id).slice(0, 5).map(x => [x.name, x.count]) })),\n  both_discussed: occ.shared.slice(0, 5).map(x => ({ name: x.name, id: x.entity_id, episodes_by_show: x.by_channel.map(c => [c.channel_name, c.count]) })),\n  shared_sponsors: sp0.sponsors.filter(x => inOther.has(x.entity.id)).map(x => ({ name: x.entity.name, id: x.entity.id, ad_reads: [x.ad_reads, inOther.get(x.entity.id)] })),\n};\n```\n\n## A good answer\n\n- Names both shows as resolved, with their channel ids.\n- A side-by-side: videos indexed and `indexed_through` for each, the latest episode, and each show's top subjects with episode counts.\n- What both covered, from `shared`, with episodes per show, and the shared sponsors with ad reads per show, for a stated window.\n\n## Traps\n\n- With two or more `channelIds`, `occurrences` puts the overlap in `shared`; `rows` alone never shows it.\n- Never count `episodes` to size a show; `status({ channelId }).channel.searchable_videos` is the count.\n- An empty `shared` in a short window is an answer (no overlap in the window), not an error; widen the window only if the user asked for a longer one.\n\nDocs: https:\u002F\u002Farcmira.com\u002Fdocs\u002Fmcp-server\n\n## After the answer\n\nMonitors can follow what a research turn found, and each alert uses 25 credits from the account's plan, then its on-demand budget. The `company-watch` skill sets one up.\n\nIf anything was wrong, slow, or missing for the user, or they want a source or capability Arcmira lacks, send one arcmira_feedback.\n","# Compare two shows\n\n`status` sizes each show, `episodes` gives the latest, `occurrences` with both channel ids ranks what each covers and returns `shared` for what both mention, and `sponsors` of each, joined on entity id, gives shared sponsors.\n\nRun each program with `arcmira_execute_read`; `arcmira_describe` has the method reference.\n\n## When to use\n\nUse Arcmira when the user asks:\n\n- compare two shows, or a show against a competitor\n- what two podcasts both talk about, or who they both advertise\n- a digest of what one or two shows covered this week or month\n\n## Pick the entity the user meant\n\nUsers give names; filters take ids only (ent_..., UC..., 11-character video ids), and a name where an id belongs throws `id_required`.\n\n1. Resolve the exact name the user said, with their own words about it as `context` (a bare \"Theo\" has none).\n2. `best` and `suggested` give the id. A `suggested` pick is an assumption: the answer names it, with `suggested.evidence` as the reason.\n3. `ask`: several entities fit, and `ask.options` goes back to the user. No answer at all: the name is not in the index.\n\nFor this task:\n\n- Resolve each show with `{ type: \"channel\" }` and use `youtube_channel_id`. Users shorten show names (\"All In\", \"MTS\"); resolve suggests a show by its initials or closest spelling, so say when a show was assumed. When nothing comes back, retry the full or hyphenated name before saying the show is not in the index.\n- Pass both UC ids in one `occurrences` call and read `shared`.\n\n## Worked program\n\nPass each block to `arcmira_execute_read` as one program (a block marked arcmira_execute_write goes to that tool), with the name swapped for the user's. It opens with the pick: set `CONTEXT` to the user's own words about the name. When several entities fit it returns `ask` and runs nothing else. Show those options to the user, then run it again with `ID` set to the pick. Build date windows from `arcmira.daysAgo(n)` and `arcmira.today()`.\n\n### Two shows, last 90 days\n\n```javascript\nconst SHOWS = [\"TBPN\", \"All-In Podcast\"], IDS = [null, null];   \u002F\u002F after an ask, put the picked option's channel_id in IDS and run again\nconst ids = [], names = [], assumed = [];\nfor (const [i, n] of SHOWS.entries()) {\n  if (IDS[i]) { ids.push(IDS[i]); names.push(n); assumed.push(null); continue; }\n  const r = await arcmira.resolve(n, { type: \"channel\" });\n  const e = r.best ?? r.suggested;\n  if (!e) return { unresolved: n, ask: r.ask && { question: r.ask.question, options: r.ask.options.map(o => ({ ...o, channel_id: r.candidates.find(c => c.id === o.id)?.youtube_channel_id ?? null })) } };\n  ids.push(e.youtube_channel_id);\n  names.push(e.name);\n  assumed.push(r.suggested ? r.suggested.evidence : null);\n}\nconst after = arcmira.daysAgo(90);\nconst [s0, s1, e0, e1, occ, sp0, sp1] = await Promise.all([\n  arcmira.status({ channelId: ids[0] }), arcmira.status({ channelId: ids[1] }),\n  arcmira.episodes(ids[0], { limit: 1 }), arcmira.episodes(ids[1], { limit: 1 }),\n  arcmira.occurrences({ channelIds: ids, types: [\"organization\", \"product\"], after, limit: 40 }),\n  arcmira.sponsors(ids[0]), arcmira.sponsors(ids[1]),\n]);\nconst inOther = new Map(sp1.sponsors.map(x => [x.entity.id, x.ad_reads]));\nreturn {\n  window: occ.window,\n  shows: ids.map((id, i) => ({ name: names[i], channel_id: id, assumed: Boolean(assumed[i]), why: assumed[i], videos_indexed: [s0, s1][i].channel.searchable_videos, indexed_through: [s0, s1][i].channel.indexed_through, latest: [e0, e1][i].episodes[0]?.title ?? null,\n    top: occ.rows.filter(x => x.channel_id === id).slice(0, 5).map(x => [x.name, x.count]) })),\n  both_discussed: occ.shared.slice(0, 5).map(x => ({ name: x.name, id: x.entity_id, episodes_by_show: x.by_channel.map(c => [c.channel_name, c.count]) })),\n  shared_sponsors: sp0.sponsors.filter(x => inOther.has(x.entity.id)).map(x => ({ name: x.entity.name, id: x.entity.id, ad_reads: [x.ad_reads, inOther.get(x.entity.id)] })),\n};\n```\n\n## A good answer\n\n- Names both shows as resolved, with their channel ids.\n- A side-by-side: videos indexed and `indexed_through` for each, the latest episode, and each show's top subjects with episode counts.\n- What both covered, from `shared`, with episodes per show, and the shared sponsors with ad reads per show, for a stated window.\n\n## Traps\n\n- With two or more `channelIds`, `occurrences` puts the overlap in `shared`; `rows` alone never shows it.\n- Never count `episodes` to size a show; `status({ channelId }).channel.searchable_videos` is the count.\n- An empty `shared` in a short window is an answer (no overlap in the window), not an error; widen the window only if the user asked for a longer one.\n\nDocs: https:\u002F\u002Farcmira.com\u002Fdocs\u002Fmcp-server\n\n## After the answer\n\nMonitors can follow what a research turn found, and each alert uses 25 credits from the account's plan, then its on-demand budget. The `company-watch` skill sets one up.\n\nIf anything was wrong, slow, or missing for the user, or they want a source or capability Arcmira lacks, send one arcmira_feedback.\n",{"name":5,"description":7},"main","f620abaff09061f8c8b1f1559dca3fdd031a32e5","plugins\u002Farcmira\u002Fmcp\u002Fskills\u002Fcompare-shows",474,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins","https:\u002F\u002Fhol.org\u002Fplugins\u002Fbest-codex-plugins","https:\u002F\u002Fgithub.com\u002Fhashgraph-online","https:\u002F\u002Fhol.org","Open-source standards and developer tools for interoperable AI agents: discovery, identity, communication, payments, privacy and security.","2026-11-11 14:40:14",{"source":8,"skillName":5,"commands":50,"prompt":60,"zipAvailable":61},[51,54,57],{"tool":52,"command":53},"npx","npx skills add hashgraph-online\u002Fawesome-codex-plugins --skill compare-shows",{"tool":55,"command":56},"bunx","bunx skills add hashgraph-online\u002Fawesome-codex-plugins --skill compare-shows",{"tool":58,"command":59},"pnpm","pnpm dlx skills add hashgraph-online\u002Fawesome-codex-plugins --skill compare-shows","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Farcmira\u002Fmcp\u002Fskills\u002Fcompare-shows\u002FSKILL.md",true,[],[64,72,79,86,113,138],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":71},"01M746ZWACVKMZ1BJXJZHYJSSX","migrate-to-e2e","Moves an existing Playwright, Cypress, Selenium, Appium, Detox, Maestro, or TesterArmy suite to e2e one slice at a time, with the old suite running beside the new one until each ported test is proven. Keeps a MIGRATION.md progress file so any later session resumes where the last stopped. Optionally plants a defect to show both suites catch it. Use for \u002Fmigrate-to-e2e, \"migrate our tests to e2e\", \"port these Maestro flows\", \"move our TesterArmy tests\", or when a project has an e2e config and an older suite still running.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fmigrate-to-e2e\u002FSKILL.md",[],[],"2026-11-11 15:11:14",{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":76,"categories":77,"keywords":78,"publishedAt":71},"01M746ZPTAX1Q0FBKAB1CYND7E","e2e","Writes, runs, and debugs end-to-end tests for web and mobile apps with e2e, the agentic test runner, which mixes agent.act goals with exact locator assertions on a Playwright browser or an iOS or Android device. Also drives a project's running app live over the e2e MCP server to look at a screen, check a UI change, take a screenshot or record a video, and try a locator; and runs bug bashes, parallel e2e explore runs with each bug proven by a repro test. Use when a project depends on e2e or has an e2e.config.ts, when asked for end-to-end, browser, mobile, or agentic UI tests, to check a change in the running app, to QA or bug bash an app or branch, or when an e2e run fails.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fe2e\u002FSKILL.md",[],[],{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":71},"01M746ZJN784HVHMDP9MQGCSGG","create-verification-skill","Generate a project-local verify-\u003Capp> skill on top of e2e, so any coding agent can launch the app, check it is worth driving, exercise a feature the way a user does, keep evidence, and bug bash it. Writes the skill, a feature map with one explore charter per feature, and proves it once. Use for \u002Fcreate-verification-skill, \"make a verification skill for this repo\", or when a project has no scripted way to prove UI behavior.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fcreate-verification-skill\u002FSKILL.md",[],[],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":34},"01M716A6ETNB9B1SQ3GXZC75VR","deja-search","deja-vu memory — search the user's past AI coding sessions with the deja CLI. Holds what they already settled and never wrote into the repo (naming rules, banned or already-tried tools, required checks before merge, preferred values, who owns what). Use before your first edit in a task, before you call a change done or ready to merge, before you recommend a tool, library, design or reviewer, before re-debugging an error that may already be solved, when they say 'didn't we fix this before', 'what did we decide about X' or 'I already have that', and before telling them something on this machine does not exist.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-search\u002FSKILL.md",[],[93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112],"search","deja search","never","error","ready","memory","re","decide","fix","design","debugging","when","you","done","reviewer","io","change","cli","merge","past",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":34},"01M716A3J2W5SENSE9VGMXB375","deja-reflect","End-of-session reflection and memory curation with deja-vu. Review what was decided, what commands broke and what repaired them, and record durable project rules or decisions with deja remember so the next session starts with them.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-reflect\u002FSKILL.md",[],[120,121,122,108,123,124,125,126,127,128,129,130,131,132,98,133,134,135,136,137],"deja reflect","reflect","review","with","record","github","next","https","node","Rules","decisions","brew","remember","project rules","project","session","end","reflection",{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":155,"publishedAt":34},"01M715T3RR4BAYSR57HPPTJ0PF","revid","Make, edit, export and post AI videos with Revid (revid.ai) through the Revid MCP server. Use whenever the user wants a short-form or long-form video made (from an idea, a script, a URL, an article, a PDF, a tweet, a product page, their own clips, or a song), wants to find what is going viral on TikTok, YouTube, Instagram or X before making something, wants to edit or re-export an existing Revid project, generate a standalone AI image or clip, make a series episode, or publish and schedule a finished video to connected social accounts. Covers setup (hosted MCP with OAuth, or an API key), the 36 tools, credits, polling and the rules for publishing. Routes to the more specific revid-* skills when one fits.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftmakersas\u002Frevid-skills\u002Fskills\u002Frevid\u002FSKILL.md",[144,149,152],{"categoryNo":145,"categoryName":146,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":150,"categoryName":151,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":153,"categoryName":154,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000010","后端与接口",[140,156,157,158,159,160,161,134,162,99,163,164,165,166,104,167,168,169,170,171],"URL","Video","short-form","standalone","PDF","viral","tiktok","short","social","MCP","song","image","mcp server","schedule","api","publish"]