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particle_podcast_get_guest

Read-only

A guest's podcast-appearance profile: lifetime stats (appearances, distinct podcasts, first/last appearance) plus their most frequent podcasts. Guests are people — the same slug works with particle_person_get for the biographical profile.

Request optional sections via include: 'appearances' for the most recent episode appearances (episode and podcast slugs included for follow-up calls), 'podcasts' for the per-podcast rollup, 'suitability' for brand-suitability exposure across the podcasts they appear on, 'recommended_podcasts' for the five shows they could plausibly appear on next — shows related to the ones they have guested on, minus those, with the venues behind each pick (the pitch list; branch on each row's band).

Returns not_found for people who exist but have never appeared on a podcast — use particle_person_get for those.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
includeNoOptional response sections: 'appearances' (most recent episode appearances with episode/podcast slugs), 'podcasts' (per-podcast rollup of where they appear), 'suitability' (brand-suitability exposure across the podcasts they appear on), 'recommended_podcasts' (the five shows they could plausibly appear on next — shows related to the ones they have guested on, minus those, each with the venues that led there; the pitch list). Default response is the profile + lifetime stats.
guest_slugYesPerson slug (e.g. 'sam-altman') from particle_podcast_list_guests, particle_person_resolve, or particle_entity_resolve.
output_formatNoOutput serialization. 'markdown' (default) returns the LLM-facing rendering. 'json' returns the structured payload as JSON text — use only for programmatic chaining where exact field extraction matters; the JSON shape is larger and noisier for an LLM to read.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint: true, and the description adds meaningful behavior beyond that: the not_found case for non-guests, the default response profile plus optional include sections, and the recommended_podcasts pitch-list behavior. It does not contradict the annotation and gives the agent enough to anticipate the response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then organized by optional sections and finally the error-routing note. Every sentence adds distinct information; the length is justified by the number of include options and the not_found behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only getter with three parameters and no output schema, the description covers all essential context: default response, optional sections, slug source, behavior for no appearances, and the sibling fallback. No critical operational detail seems missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description enriches parameter meaning: it explains that episode/podcast slugs in 'appearances' enable follow-up calls, and it clarifies the recommended_podcasts pitch-list structure with 'branch on each row's band'. It also gives slug provenance via list_guests/person_resolve/entity_resolve.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb-resource pairing: it fetches a guest's podcast-appearance profile and enumerates the contained stats (lifetime appearances, distinct podcasts, first/last appearance, frequent podcasts). It explicitly distinguishes itself from particle_person_get by noting that the same slug returns the biographical profile, so an agent can tell them apart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit selection guidance: use particle_person_get for biographical profiles and for people who exist but have never appeared on a podcast (not_found), implying particle_podcast_get_guest is for podcast-appearance data. It also names follow-up call possibilities from the include sections, which helps an agent decide when to request appearances.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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