Compares two podcasts or YouTube shows side by side: size, latest episode, what each talks about, what both cover, and shared sponsors. Uses arcmira.
`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.
This medium 736-word instruction set is purpose-built for testing & qa work in AI coding agents. Paste directly into your CLAUDE.md or AI agent settings.
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.
Run each program with arcmira_execute_read; arcmira_describe has the method reference.
Users give names; filters take ids only (ent_..., UC..., 11-character video ids), and a name where an id belongs throws id_required.
context (a bare "Theo" has none).best and suggested give the id. A suggested pick is an assumption: the answer names it, with suggested.evidence as the reason.ask: several entities fit, and ask.options goes back to the user. No answer at all: the name is not in the index.{ 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.occurrences call and read shared.Pass 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().
const SHOWS = ["TBPN", "All-In Podcast"], IDS = [null, null]; // after an ask, put the picked option's channel_id in IDS and run again
const ids = [], names = [], assumed = [];
for (const [i, n] of SHOWS.entries()) {
if (IDS[i]) { ids.push(IDS[i]); names.push(n); assumed.push(null); continue; }
const r = await arcmira.resolve(n, { type: "channel" });
const e = r.best ?? r.suggested;
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 })) } };
ids.push(e.youtube_channel_id);
names.push(e.name);
assumed.push(r.suggested ? r.suggested.evidence : null);
}
const after = arcmira.daysAgo(90);
const [s0, s1, e0, e1, occ, sp0, sp1] = await Promise.all([
arcmira.status({ channelId: ids[0] }), arcmira.status({ channelId: ids[1] }),
arcmira.episodes(ids[0], { limit: 1 }), arcmira.episodes(ids[1], { limit: 1 }),
arcmira.occurrences({ channelIds: ids, types: ["organization", "product"], after, limit: 40 }),
arcmira.sponsors(ids[0]), arcmira.sponsors(ids[1]),
]);
const inOther = new Map(sp1.sponsors.map(x => [x.entity.id, x.ad_reads]));
return {
window: occ.window,
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,
top: occ.rows.filter(x => x.channel_id === id).slice(0, 5).map(x => [x.name, x.count]) })),
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]) })),
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)] })),
};indexed_through for each, the latest episode, and each show's top subjects with episode counts.shared, with episodes per show, and the shared sponsors with ad reads per show, for a stated window.channelIds, occurrences puts the overlap in shared; rows alone never shows it.episodes to size a show; status({ channelId }).channel.searchable_videos is the count.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.Monitors 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.
If anything was wrong, slow, or missing for the user, or they want a source or capability Arcmira lacks, send one arcmira_feedback.
Compare Shows is a free testing & qa skill for AI coding agents. Compares two podcasts or YouTube shows side by side: size, latest episode, what each talks about, what both cover, and shared sponsors. Uses arcmira.. It provides a specialized system prompt that configures your agent with testing & qa expertise.
Copy the system prompt below and paste it into your CLAUDE.md file or Claude Code's custom instructions to activate Compare Shows.
Compare Shows is compatible with Claude Code, Cursor, GitHub Copilot, Windsurf, OpenClaw, Cline, and any AI agent that supports custom system prompts or .cursorrules files.
Yes, Compare Shows is completely free and open source. The full source is available on GitHub at https://github.com/arcmira/mcp/blob/master/plugins/arcmira/skills/compare-shows/SKILL.md. You only need a subscription to the AI agent you use it with.
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