Tool ID:
particle_get_podcastRun this action
Use the TypeScript SDK for one call. Usectx.tools.execute(...) inside a Play for durable calls, scheduled calls, or CSV processing.
import { Deepline } from 'deepline';
const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
'particle_get_podcast',
{
"id": "id_123"
},
);
console.log(result.toolResponse.raw);
CLI
deepline tools execute particle_get_podcast --input '{
"id": "id_123"
}' --json
Example response
The SDK returns this shape atresult.toolResponse.raw. The example values illustrate the response.
{
"data": {
"explicit": true,
"id": "id_123",
"title": "VP of Engineering"
}
}
deepline describe particle_get_podcast --json for the latest machine-readable contract.
Input reference
Returns a single podcast by slug (e.g., ‘all-in’) or ID. Slugs are human-readable identifiers included in every podcast response.| Name | Type | Required | Default | Details |
|---|---|---|---|---|
payload.id | string | Yes | — | Podcast slug (e.g., ‘all-in’, ‘lex-fridman-podcast’), internal ID, or numeric iTunes ID |
payload.topic_limit | integer | No | 10 | Maximum number of aggregated topics to return (0 for none, max 1000) Format: int64. Minimum: 0. Maximum: 1000. |
payload.include | array | No | — | Optional response sections. related attaches the five most related podcasts (lean form). recommended_guests the five guests the show could book next. recommended_sponsors (premium-grade, requires a plan with premium endpoints) the five advertisers active on shows like this one that do not buy it yet. Each has a paged endpoint for the full list: /related, /recommendations/guests, /recommendations/sponsors. coverage attaches how much of the show’s history we know of and have transcribed, including See the live schema for the complete constraint. |
Output reference
Standard tool result payload.| Name | Type | Required | Default | Details |
|---|---|---|---|---|
result.data | object | Yes | — | Provider response payload. |
result.data.bias | string | No | — | Political bias rating for the podcast: EXTREME_LEFT, LEANS_LEFT, LEFT, CENTER, RIGHT, LEANS_RIGHT, or EXTREME_RIGHT. Empty when the podcast is not substantively political or has not been evaluated yet. Fetch GET /v1/podcasts/{id}/bias for the full analysis including reasoning and evidence. |
result.data.coverage | object | No | — | — |
result.data.coverage.back_catalogue | object | No | — | — |
result.data.coverage.back_catalogue.complete | boolean | Yes | — | true when the discovery sources listed the podcast’s whole history. false when PodcastIndex capped its listing at 1,000 episodes, so older episodes may exist that neither it nor the podcast’s own feed lists. |
result.data.coverage.back_catalogue.feed_item_count | integer | No | — | Items the podcast’s own feed listed. Absent when the feed could not be read. Format: int64. |
result.data.coverage.back_catalogue.imported_at | string | Yes | — | When the back catalogue was last imported. Format: date-time. |
result.data.coverage.back_catalogue.podcastindex_episode_count | integer | Yes | — | Episodes PodcastIndex listed, at most 1,000. Format: int64. |
result.data.coverage.counted_at | string | No | — | When these counts were computed. They refresh hourly, so an episode ingested, transcribed or requested since is not reflected yet. Each episode’s own transcript_status is always current. Format: date-time. |
result.data.coverage.discovered_episode_count | integer | Yes | — | Every episode we know of, transcribed or not: the episodes we have ingested plus the podcast’s back catalogue. The transcript_statuses counts sum to it. Format: int64. |
result.data.coverage.newest_episode_published_at | string | No | — | Publication date of the newest discovered episode. Format: date-time. |
result.data.coverage.oldest_episode_published_at | string | No | — | Publication date of the oldest discovered episode. Format: date-time. |
result.data.coverage.transcript_statuses | array | null | Yes | — | Discovered episodes by transcript_status, one entry per status. Unlike episode_count on the podcast, which counts ingested episodes, these include the back catalogue. |
result.data.coverage.transcript_statuses[].count | integer | Yes | — | Discovered episodes with this status. Format: int64. |
result.data.coverage.transcript_statuses[].transcript_status | "transcribed" | "processing" | "queued" | "requestable" | "unavailable" | Yes | — | The status counted. See Episode.transcript_status. Allowed: transcribed, processing, queued, requestable, unavailable. |
result.data.coverage.years | array | null | Yes | — | Discovered and transcribed episodes per publication year, newest year first. Episodes without a publication date are counted in the totals only. |
result.data.coverage.years[].discovered | integer | Yes | — | Episodes published that year that we know of. Format: int64. |
result.data.coverage.years[].transcribed | integer | Yes | — | Of those, episodes with a transcript. Format: int64. |
result.data.coverage.years[].year | integer | Yes | — | Publication year (UTC). Format: int64. |
result.data.description | string | No | — | Podcast description |
result.data.episode_count | integer | No | — | Total number of episodes Format: int64. |
result.data.explicit | boolean | Yes | — | Whether the podcast contains explicit content |
result.data.format | object | No | — | — |
result.data.format.avg_episode_minutes | integer | No | — | Average episode length in minutes. Omitted when no episode durations are known. Format: int64. |
result.data.format.episodes_per_week | number | No | — | Publishing cadence over the trailing 90 days, in episodes per week (e.g. 5.0 for a weekday daily, 0.5 for a fortnightly show). Omitted until the show has been tracked long enough to measure reliably. Format: double. |
result.data.format.guest_frequency | string | No | — | How often episodes feature a guest: never, rare, occasional, regular, or always. Derived from the share of analyzed episodes with at least one guest speaker. Omitted when too few episodes have been analyzed to judge. Filter the catalog with the guest_frequency query parameter on GET /v1/podcasts. |
result.data.format.has_ads | boolean | No | — | Whether episodes carry advertiser reads. Omitted when too few episodes have been analyzed to judge. The full advertising profile (sponsors, read types, ad load) is served by GET /v1/podcasts/{id}/advertising. |
result.data.format.has_video | boolean | Yes | — | Whether any episode has a discovered video version (e.g. a YouTube release). |
result.data.format.publishing_status | string | No | — | Whether the show is still releasing episodes: active (published within the last 90 days) or dormant. Omitted when no publish dates are known. |
result.data.format.signals | array | null | No | — | Production formats detected from the show’s speaker-role mix: interview, panel, call_in, and/or solo_narrated. A show can carry several (a panel show with call-in segments). Omitted when too few episodes have been analyzed to judge. |
result.data.id | string | Yes | — | Unique identifier |
result.data.image_url | string | No | — | Cover image URL |
result.data.language | string | No | — | ISO 639-1 language code |
result.data.match_quality | "exact" | "partial" | "fuzzy" | "description" | "speculative" | No | — | How confidently this result matches your q search, strongest first. exact: this is the show with that name. partial: the name matches your search strongly (your search may have included extra words). fuzzy: the name is similar but not the same — it may be the show you meant with a typo, or a different show with a near-identical name. verify before relying on it. description: your search text appears in the show’s description rather than its name. speculative: a loose suggestion, listed last. See the live schema for the complete constraint. |
result.data.political_context | string | No | — | Political framework the bias rating is calibrated against: US, UK, EU, CANADA, AUSTRALIA, INDIA, OTHER. Omitted when the latest analysis returned NOT_POLITICAL or when no analysis has been run yet. |
result.data.popularity | number | No | — | Global popularity percentile in (0,1], a cume_dist ranking over all currently-charting podcasts (Apple Podcasts charts). Higher is more popular. The most popular podcast is 1.0. Always global — never scoped to a topic_id or other filter. Omitted when the podcast is not currently charting. Pair with the popularity_threshold query parameter on GET /v1/podcasts to filter the catalog by this value. Format: double. |
result.data.publisher | object | No | — | — |
result.data.publisher.id | string | Yes | — | Publisher ID |
result.data.publisher.name | string | Yes | — | Publisher name |
result.data.publisher.slug | string | No | — | Human-readable slug identifier (e.g., ‘goalhanger’, ‘iheartpodcasts’). When present, accepted in place of the ID anywhere a publisher reference is taken in the API. Occasionally absent on publishers whose name doesn’t slugify (e.g., scripts not representable in ASCII URL slugs). |
result.data.recommended_guests | array | null | No | — | The five guests the show could plausibly book next (lean form, no via). Present only on GET /v1/podcasts/{id} with include=recommended_guests. The paged list is GET /v1/podcasts/{id}/recommendations/guests. |
result.data.recommended_guests[].band | "strong" | "moderate" | "weak" | Yes | — | Coarse class of the score. Allowed: strong, moderate, weak. |
result.data.recommended_guests[].person | object | Yes | — | — |
result.data.recommended_guests[].person.description | string | No | — | Short description (e.g. current role), when known. |
result.data.recommended_guests[].person.id | string | Yes | — | Encoded Person identifier |
result.data.recommended_guests[].person.image_url | string | No | — | Canonical headshot URL when one is known for the Person |
result.data.recommended_guests[].person.name | string | Yes | — | Display name |
result.data.recommended_guests[].person.slug | string | No | — | Stable human-readable handle (e.g. ‘satya-nadella’). Recommended canonical identifier on every Particle Pro person surface. |
result.data.recommended_guests[].score | number | Yes | — | Strength of the recommendation in (0,1): how related the shows that booked this person are, counted once per publisher and damped for how widely the person already circulates. Recurring on any one show does not raise it, and circuit regulars who appear everywhere are excluded. Format: double. |
result.data.recommended_guests[].shared_show_count | integer | Yes | — | How many of the show’s related shows have booked this person. Format: int64. |
This output schema is too large for an inline display. Read the complete live contract with
deepline describe particle_get_podcast --json.Deepline cost
- Pricing model:
fixed(per call). - Estimated Deepline credits:
0per pricing unit. - Provider-native pricing may still exist outside Deepline credit billing.