🔧 Compare Shows

Compares two podcasts or YouTube shows side by side: size, latest episode, what each talks about, what both cover, and shared sponsors. Uses arcmira.

About Compare Shows

`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.

Key Capabilities

  • compare two shows, or a show against a competitor
  • what two podcasts both talk about, or who they both advertise
  • a digest of what one or two shows covered this week or month
  • Pass both UC ids in one `occurrences` call and read `shared`.
  • Names both shows as resolved, with their channel ids.

What This Skill Covers

  • When to use
  • Pick the entity the user meant
  • Worked program
  • A good answer
  • Traps
  • After the answer

How It Works

  1. Resolve the exact name the user said, with their own words about it as `context` (a bare "Theo" has none).
  2. `best` and `suggested` give the id. A `suggested` pick is an assumption: the answer names it, with `suggested.evidence` as the reason.
  3. `ask`: several entities fit, and `ask.options` goes back to the user. No answer at all: the name is not in the index.

Use Cases

  • Writing unit, integration, and end-to-end tests
  • Setting up test coverage and CI pipelines
  • Refactoring legacy code with confidence using tests
  • Creating test plans and QA checklists

Example Prompts

Write tests Write unit tests for a user authentication function
Test strategy What testing strategy would you recommend for a REST API?

System Prompt (736 words)

Compare two shows

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.

When to use

  • compare two shows, or a show against a competitor
  • what two podcasts both talk about, or who they both advertise
  • a digest of what one or two shows covered this week or month

Pick the entity the user meant

Users give names; filters take ids only (ent_..., UC..., 11-character video ids), and a name where an id belongs throws id_required.

  • Resolve the exact name the user said, with their own words about it as 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.
For this task:
  • 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.
  • Pass both UC ids in one occurrences call and read shared.

Worked program

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().

Two shows, last 90 days

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)] })),
};

A good answer

  • Names both shows as resolved, with their channel ids.
  • A side-by-side: videos indexed and indexed_through for each, the latest episode, and each show's top subjects with episode counts.
  • What both covered, from shared, with episodes per show, and the shared sponsors with ad reads per show, for a stated window.

Traps

  • With two or more channelIds, occurrences puts the overlap in shared; rows alone never shows it.
  • Never count episodes to size a show; status({ channelId }).channel.searchable_videos is the count.
  • 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.
Docs: https://arcmira.com/docs/mcp-server

After the answer

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.

Frequently Asked Questions

What is Compare Shows?

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.

How do I use Compare Shows with Claude Code?

Copy the system prompt below and paste it into your CLAUDE.md file or Claude Code's custom instructions to activate Compare Shows.

Which AI coding agents work with 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.

Is Compare Shows free to use?

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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