> ## Documentation Index > Fetch the complete documentation index at: https://docs.particle.pro/llms.txt > Use this file to discover all available pages before exploring further. # Coverage > What is in the catalog, how fresh it is, what every episode carries, and the calls that tell you exactly what is available for a show, an episode, or a language before you build on it. Particle transcribes the podcast catalog end to end and keeps it current. This page gives the scope in numbers, how quickly a new episode becomes searchable, what each analysis layer covers, and the calls that show what is available for the shows you care about. ## The catalog in numbers The catalog grows every day, so its numbers live in the API rather than on this page. `GET /v1/podcasts/stats` needs no API key, is cached for a minute, and returns the podcast total and the episodes added in the last day and week: ```bash theme={"dark"} curl https://api.particle.pro/v1/podcasts/stats ``` ```json theme={"dark"} { "podcasts": { "totals": [ { "classification": "transcribed", "count": 138231 } ] }, "episodes": { "added": [ { "window": "24h", "count": 20535 }, { "window": "7d", "count": 174656 } ] } } ``` What the catalog contains, and where each count comes from: | | Live source | | ------------------------------------------------------------- | --------------------------------------------------------------------------------- | | Podcasts, every one transcribed | `podcasts.totals` in the stats response | | Episodes, and how many arrived in the last day and week | `episodes.added` in the stats response; `GET /v1/podcasts/episodes` for the list | | Segments: the topical sections of every transcribed episode | `segment_count` on an episode; `GET /v1/podcasts/episodes/{id}/segments` | | Clips: engagement-scored highlights, each with playable audio | `clip_count` on an episode; `GET /v1/podcasts/clips` to browse | | Knowledge graph: people, companies, and other entities | `GET /v1/entities/search`; each hit carries `mentions.podcast_episodes` | | History | Episodes back to 2017; a show's back catalogue is ingested when the show is added | ## How fresh Feeds are polled on a schedule derived from each show's release cadence and popularity: popular and frequent shows at least every 30 minutes, tightening to every few minutes around an expected release, and every show at least every two days. Once an episode is discovered it moves through four milestones that the feed and the stream expose: | Milestone | What is available | | ---------------- | --------------------------------------------------------------------------- | | `discovered` | The episode record: title, description, audio, published time, platform ids | | `transcribed` | The diarized transcript, speakers, and entity mentions | | `segmented` | Topical segments with titles and summaries, and the episode's topics | | `fully_ingested` | Highlight clips, ads, and everything else derived from the transcript | Transcription and enrichment take minutes to hours after discovery. [`GET /v1/podcasts/episodes/feed`](/podcasts/feed) (every plan) and [`GET /v1/podcasts/episodes/stream`](/podcasts/stream) (Enterprise) deliver episodes as they cross the milestone you choose, in ingestion order, with a cursor you can resume from. ## What every episode carries | Layer | Coverage | Where | | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------- | | Transcript | Every transcribed episode: diarized dialogue with a speaker and role per line, word-level timestamps, SRT | [Transcripts](/podcasts/transcripts) | | Speakers | Hosts, guests, panelists, and correspondents; an identified speaker links to a knowledge-graph person as `speaker.entity` | [Guests](/podcasts/guests) | | Segments | Every transcribed episode: intro, topic discussions, interviews, ads, outro. Episodes segmented since line ranges were recorded carry `start_line` and `end_line`, which together cover every transcript line; older episodes omit them | [Segments and clips](/podcasts/segments-and-clips) | | Entities and mentions | People, companies, organizations, and places named in the dialogue, linked to the knowledge graph | [Mentions](/podcasts/mentions) | | Topics | Per-episode topics from the taxonomy | [Topics](/knowledge-graph/topics) | | Clips | AI-extracted highlights with an `engagement_score` from 0 to 100 (above 70 is a strong clip) and a direct MP3 | [Segments and clips](/podcasts/segments-and-clips) | | Ads | Sponsor, product, offer, read type, and placement for every detected ad read | [Advertising](/podcasts/advertising) | ## What every show carries | Layer | Coverage | Where | | -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------- | | Rankings | Apple and Spotify chart positions by country and category, captured daily, with history and movers | [Rankings](/podcasts/rankings) | | Ratings | Listener star ratings and reviews with per-platform summaries and a narrative sentiment summary | [Ratings](/podcasts/ratings) | | Format | Guest frequency, interview, panel, call-in, or solo format, episode length, and cadence | [Format](/podcasts/format) | | Related shows | The shows most like this one, ranked and explained by content, topics, shared guests, network, and sponsors | [Related](/podcasts/related) | | Bias and suitability | Political-bias and GARM brand-suitability profiles for analyzed shows and publishers, each stamped with `evaluated_at`; analysis is expanding across the catalog, most popular shows first, and the [publisher suitability](/podcasts/publisher-suitability) page states its current reach | [Suitability](/podcasts/suitability), [Publisher bias](/podcasts/publishers-bias) | ## Check coverage before you build * **A show.** [`GET /v1/podcasts/search?q=`](/podcasts/search) resolves a name, and the record carries `episode_count`, `language`, `popularity`, and `format`. Holding an Apple, Spotify, or YouTube id or an RSS URL? [`GET /v1/podcasts/lookup`](/podcasts/lookup) resolves up to 100 per call, deterministically. * **An episode.** [`GET /v1/podcasts/episodes/lookup`](/podcasts/lookup) resolves Apple and YouTube ids, RSS guids (the broadest identifier, carried by about nine in ten episodes), PodcastIndex ids, and hosting-platform ids from Megaphone, Omny, Acast, and Art19. Every episode record carries `has_transcript`; `segment_count` and `clip_count` appear once they are non-zero, so one list call tells you what is ready and a missing count means nothing yet. * **A person or company.** [`GET /v1/entities/search?q=`](/knowledge-graph/entities) resolves the name, and every result carries `mentions.podcast_episodes`, the number of episodes naming it, so one call tells you whether there is dialogue to read and roughly how much. [`GET /v1/podcasts/mentions/timeseries`](/recipes/track-a-company#3-chart-the-volume-over-time) shows how that volume is spread over time, and its first non-zero bucket is how far back the catalog names the subject. * **A language.** `language` on episode and search endpoints takes an ISO 639-1 code matched on the primary subtag, so `fr` covers `fr-CA`. * **Charts.** [`GET /v1/podcasts/rankings/sources`](/podcasts/rankings), `/countries`, and `/categories` enumerate every chart tracked. * **Entities and topics.** [`GET /v1/entities/types`](/knowledge-graph/entities) and [`GET /v1/topics`](/knowledge-graph/topics) enumerate the vocabularies behind `entity_type` and `topic_id`. ## How the data is made, and what to lean on * **Transcripts** come from speech recognition with speaker diarization; each speaker is matched to a person in the knowledge graph when the episode identifies them. A speaker with an `entity` is identified; a named speaker without one keeps the name used on air; a speaker the pipeline could not name carries a diarization label such as `speaker_0`. * **Mentions** come from entity linking over the transcript: a line is a mention when it names the entity or a known alias, and `mention_variants` lists the forms that matched. Mentions inside ad reads are excluded by default; pass `include_ads=true` to count them. * **Search** ranks segments by meaning (`semantic_search`), by exact tokens (`keyword_search`), or both, and flags the lines that drove each match. `relevance_score` orders results within one query; across queries, compare by rank rather than by value. * **Clips** are chosen for shareability and scored for engagement on one scale across the catalog, so `min_engagement=80` means the same thing on every show. * **Ads, bias, and suitability** are classified from the transcript and refreshed as new episodes land. ## Related * [Concepts](/concepts) for identifiers, pagination, and errors * [Feed](/podcasts/feed) and [Stream](/podcasts/stream) for following new episodes * [Lookup](/podcasts/lookup) for resolving platform ids