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arcmira/compare-shows

arcmira

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.

v0.10.4LATEST
NewUpdated Oct 5, 2026

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.

Use it through the arcmira MCP server (arcmira_describe, then arcmira_execute_read with a program) or the arcmira CLI, whose commands have the same names. arcmira_describe carries the full method reference (CLI: arcmira <command> --help), and the arcmira skill the shared procedure.

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.

  1. Resolve the exact name the user said, and pass their own words about it as context when they gave any ("Sam, the My First Million co-host" is resolve("Sam", { context: "the My First Million co-host" })). Context is only words from the user's message, never your guess: a bare "Theo" is resolve("Theo"), and its ask goes back to the user.
  2. best: the name means that row. Use it and name it.
  3. suggested: no row is certain but one stands out. Use it and tell the user you assumed it, quoting suggested.evidence ("Sam Altman, assuming the most mentioned Sam: 4,399 appearances, 11x the next").
  4. ask: several rows fit and none stands out. Return ask.options for the user to pick and stop, or check every option id against the data in one program (occurrences or momentum with all the ids) and answer per row, naming each.
  5. None of the three: the name is not in the Arcmira index. Say so and ask for another spelling or a link; never answer for a different entity without saying so.
  6. Say which entity the answer is about (name, type, id) in the answer. Never switch entities silently.
  7. Before asserting a mention, read its description or passage and say which sense of the name it is (Mercury the bank, not the element). Drop rows about another sense.

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. When the result carries assumed: true, tell the user which entity was assumed and why (why). Build date windows from arcmira.daysAgo(n) and arcmira.today().

Two shows, last 30 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(30);
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.

When a plan or usage limit blocks a capability, briefly name the limit and any required tier reported by the API. Link to https://arcmira.com/pricing as "Plan access details" for information; do not upgrade a plan. Requested Premium work uses credits from the account's plan, then its on-demand budget, without another confirmation. Preserve error codes and reported quota or reset facts. If the user requested Premium, keep quality: "premium". Do not retry with captions, suggest third-party transcripts, or present them as equivalent. Only change the requested quality if the user asks.

Search as_of is the newest publication date among the returned passages, not the date the whole index was updated. For channel freshness, call arcmira.status({ channelId }) and report channel.search_indexed_through for transcript search. A result date or an empty query does not establish missing recent episodes.

Keep outside evidence separate from Arcmira results. Docs: https://arcmira.com/docs/mcp-server

After the answer

When the answer named companies, people, shows or topics worth following, offer once to save them to a monitor so updates arrive on their own. On a yes, follow the company-watch skill: it lists the user's monitors first and asks how they want updates.

If anything was wrong, slow, or missing for the user, send one arcmira_feedback.

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Overall Score

88/100

Grade

A

Excellent

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

90

Quality

88

Clarity

86

Completeness

84

Summary

This skill compares two podcasts or YouTube shows side by side using the Arcmira API, providing metrics like size, latest episodes, topics covered, overlapping content, and shared sponsors. It handles entity resolution, manages ambiguous name matching, and provides detailed instructions for calling Arcmira's read methods through either MCP server or CLI.

Detected Capabilities

Network access (Arcmira API calls)Entity resolution (resolve names to Arcmira IDs)Data aggregation and filtering (occurrences, sponsors, episodes)Time window filtering (date ranges with daysAgo utility)JSON data transformation and outputOptional follow-up integration (company-watch skill monitoring)

Trigger Keywords

Phrases that agents use to match this skill to user intent.

compare podcastsshow analysispodcast audienceshared sponsorschannel comparisontopic overlaparcmira lookup

Risk Signals

INFO

External API dependency on arcmira.com

Compatibility field, throughout skill instructions
INFO

Network requests to Arcmira API (read-only data retrieval)

Worked program and method calls (arcmira.status, arcmira.episodes, arcmira.occurrences, arcmira.sponsors)
INFO

Reference to external link for pricing and plan details

Section 'When a plan or usage limit blocks a capability'

Referenced Domains

External domains referenced in skill content, detected by static analysis.

arcmira.comwww.apache.org

Use Cases

  • Compare two podcasts or YouTube shows head-to-head on audience size, recent episodes, and subject matter
  • Analyze shared sponsors between two shows to understand advertising partnerships
  • Find what topics two shows both cover over a specified time window
  • Research a show's key topics and episode counts without manual effort
  • Discover if two podcasts have overlapping audiences or content themes

Quality Notes

  • Excellent entity resolution guidance: detailed steps for handling ambiguous names, with concrete examples ('Sam, the My First Million co-host')
  • Clear separation of concerns: resolve → pick → execute → answer phases are well-defined
  • Strong trap section addresses common mistakes (using episodes() to size a show, misinterpreting shared overlaps)
  • Comprehensive worked program example with comments and conditional logic for handling ask scenarios
  • Good output specification: agent knows exactly what 'done' looks like (names, channel ids, side-by-side comparison, overlap data, sponsors)
  • Error handling defined: missing entities, unresolved names, ambiguous matches, and quota limits all addressed
  • Documentation of data sources and API field meanings helps agent understand what each method returns
  • Nice post-answer guidance: offering to save monitored entities to company-watch skill for ongoing updates
  • Includes feedback mechanism (arcmira_feedback) for quality issues
  • Context preservation: skill emphasizes using user's own words for resolution (not agent guesses)
  • Edge case coverage: empty shared lists are explicitly flagged as valid answers, not errors
  • Field-level documentation: status fields (searchable_videos, indexed_through), episode window handling, and date interpretation all clarified
Model: claude-haiku-4-5-20251001Analyzed: Oct 5, 2026

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