Particle Podcast Resolve
particle_podcast_resolveFind a podcast by free-text title, exact slug, iTunes ID, or RSS feed URL. Returns slug, title, episode count, bias, and the top recurring speakers (with entity slugs). Use the slug as the agent-facing handle to feed into other podcast tools (particle_podcast_find_mentions, particle_podcast_list_episodes, particle_podcast_get_sponsors).
Free-text matching is forgiving — typos, missing or extra words, and pasted episode titles all work. Results are ordered best-match-first; text matches carry a match_quality field, and an empty list means the catalog has no plausible candidate.
With all identifiers omitted, returns the most recently updated podcasts — useful for browsing the catalog when you don't have a name in mind. Narrow free-text browsing with topic_slug (topic concentration, descendants included), suitability_tier, or min_popularity (global popularity percentile over charting podcasts).
Optional hydrations attach extra data to each result in the same call:
include: ["external_links"]: third-party platform presences (directories, social profiles, video channels, publisher websites) with resolved URLs and audience metrics.include: ["suitability"]: per-category brand-suitability breakdown (12 categories with prevalence, treatment, derived risk level, reasoning, and evidence excerpts) — premium-grade data, requires a plan with premium endpoints. The high-levelsuitability_tierenum (SAFE / LIMITED / SENSITIVE / UNSAFE) is rendered on every result without opt-in.include: ["ratings_summary"]: listener-review aggregate (average stars, count, per-platform breakdown).include: ["bias"]: full political-bias analysis (the high-level bias enum is always rendered without opt-in).include: ["rankings"]: current chart positions across sources/countries/categories — premium-grade data, requires a plan with premium endpoints. For movers and history useparticle_podcast_get_rankings.include: ["format"]: the show's format profile — how often episodes feature guests, detected production formats (interview, panel, call_in, solo_narrated), ad and video presence, episode-length distribution, publishing cadence, and the publish-day pattern.include: ["guest_expertise"]: the show's guest mix — shares of its analyzed guest appearances by established, senior and in-field guests and promotional appearances, and the occupations and fields it books most.recent_episodes: N: inline this many of each result's most recent episodes (slug, title, published_at, duration) — skip the follow-upparticle_podcast_list_episodescall when you only need the most recent tail.
Find shows by who they book with guest_occupation or guest_field (resolve the words to codes with particle_expertise_resolve first) and the share floors min_established_guest_share, min_in_field_guest_share and max_promotional_guest_share: guest_field="banking-finance-and-investment" with min_established_guest_share=0.5 finds shows that book established finance experts. For the shows that booked an occupation's or field's guests most in a recent window, use particle_expertise_get with include: ["top_podcasts"].
Tool call template
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "particle_podcast_resolve"
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | Exact slug match for a known handle (e.g. 'all-in'). | |
| limit | No | Maximum candidates to return (1-25, default 5). | |
| query | No | Free-text search across podcast titles and descriptions (case-insensitive partial match). Omit to fall back to the most recently updated podcasts. | |
| include | No | Optional non-parameterized hydrations to attach to each result. 'external_links' adds third-party platform presences (directories, social profiles, video channels, publisher websites). 'suitability' adds the per-category brand-suitability breakdown (premium-grade data — requires a plan with premium endpoints). 'ratings_summary' adds the listener-review aggregate. 'bias' adds the full political-bias analysis. 'rankings' adds current chart positions (premium-grade data — requires a plan with premium endpoints). 'format' adds the format profile (guest frequency, interview/panel/call-in/solo formats, ads, video, episode length, cadence, publish days). 'related' adds the five most related shows (slug, score, band) — for the full ranked list with the basis behind each pair call particle_podcast_list_related. 'recommended_guests' adds the five guests the show could book next — people who have guested on its related shows but never on it (person slug, score, band, and the related shows that booked them); the booking pipeline. 'recommended_sponsors' adds the five advertisers the show could pitch — sponsors that run on its related shows but not on it (sponsor, linked company, score, band, ads and most recent ad across those shows, and which shows); the prospecting list (premium-grade data — requires a plan with premium endpoints). 'coverage' adds how much of the show's history we know of and have transcribed: discovered episodes by transcript status and by year, and whether its back catalogue (older episodes discovered in its feed but not transcribed) has been imported and is complete. 'guest_expertise' adds the show's guest mix: the shares of its analyzed guest appearances by established, senior or in-field guests and promotional appearances, and the occupations and fields it books most (codes the guest_ filters accept). 'speaker_statement_characteristics' adds how the show's lines are said over the last 365 days: each sentiment, certainty, specificity and temporal_orientation label's share of its scored lines, and for each pole label the share of profiled shows with a lower share (e.g. more forward-looking than 82% of shows) — how the show talks, not what it covers. The high-level suitability_tier and bias enums are always rendered without opt-in. Off by default; opt in only when needed. | |
| rss_url | No | Canonical RSS feed URL. Resolves directly to the matching podcast. | |
| itunes_id | No | Numeric Apple Podcasts / iTunes ID (e.g. '1502871393'). Resolves directly to the matching podcast. | |
| topic_slug | No | Filter candidates by topic (slug from particle_topic_browse, e.g. 'technology/artificial-intelligence'). Matches podcasts where the topic — or any of its descendants — accounts for a meaningful share of episodes, ranked by concentration. | |
| guest_field | No | Only shows whose analyzed guests include someone listed under this ANZSRC 2020 field of research: a code, slug or title from particle_expertise_resolve. | |
| min_popularity | No | Restrict candidates to podcasts whose global popularity percentile is at least this value (0-1]. Popularity is a cume_dist ranking over currently-charting podcasts; non-charting podcasts are excluded when set. Omit or 0 to disable. | |
| recent_episodes | No | Inline this many of each result's most recent episodes (slug, title, published_at, duration). 0 (default) means none — call particle_podcast_list_episodes if you need more than the inline tail. Capped at 25. | |
| guest_occupation | No | Only shows whose analyzed guests include someone listed under this occupation: a SOC 2018 or ISCO-08 code, slug or title from particle_expertise_resolve. | |
| suitability_tier | No | Filter candidates by brand-suitability tier. Podcasts without a suitability analysis are excluded when set. | |
| min_in_field_guest_share | No | Only shows where at least this share (0-1) of analyzed guest appearances are guests speaking within their own field. | |
| max_promotional_guest_share | No | Only shows where at most this share (0-1) of analyzed guest appearances are promotional; 0 keeps only shows with none. | |
| min_established_guest_share | No | Only shows where at least this share (0-1) of analyzed guest appearances are by guests of established standing. |