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particle_company_get

Read-only

Return a bundled profile for one company: identifiers (slug, ticker, domain, CIK, QID, linked entity), name, and description.

Request optional sections via include: 'people' for current leadership and notable people (person slugs feed particle_person_get), 'products' for the three-level product hierarchy, 'competitors' for the competitor list, 'external_links' for the company's LinkedIn, social profiles, domain, Wikidata QID, SEC CIK and tickers. The default response is lean — include only what you need.

For sponsor/advertising analytics on this company, use particle_company_get_podcast_ad_presence instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
includeNoOptional response sections: 'people' (current leadership and notable people), 'products' (three-level product hierarchy), 'competitors' (competitor list), 'podcast_recommendations' (the ten podcasts the company could advertise on next, with the shows it already buys that led there; premium), 'external_links' (LinkedIn, social profiles, domain, Wikidata QID, SEC CIK and tickers). Default response is lean — request only what you need.
company_slugYesCompany identifier — accepts slug (e.g. 'nvidia'), domain (e.g. 'nvidia.com'), or canonical ID. If you already know the domain you can call this tool directly without first running particle_company_resolve.
product_statusNoComma-separated lifecycle filter for include=products (e.g. 'active' or 'active,announced'). Allowed values: active, announced, discontinued, rumored. Defaults to 'active'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / include / description
      Previous value: -"Optional response sections: 'people' (current leadership and notable people), 'products' (three-level product hierarchy), 'competitors' (competitor list), 'podcast_recommendations' (the ten podcasts the company could advertise on next, with the shows it already buys that led there; premium). Default response is lean — request only what you need."New value: +"Optional response sections: 'people' (current leadership and notable people), 'products' (three-level product hierarchy), 'competitors' (competitor list), 'podcast_recommendations' (the ten podcasts the company could advertise on next, with the shows it already buys that led there; premium), 'external_links' (LinkedIn, social profiles, domain, Wikidata QID, SEC CIK and tickers). Default response is lean — request only what you need."
    • changedInput schema / properties / include / items / enum
      Previous value: -[
-  "people",
-  "products",
-  "competitors",
-  "podcast_recommendations"
-]New value: +[
+  "people",
+  "products",
+  "competitors",
+  "podcast_recommendations",
+  "external_links"
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, so the description must carry the rest — and it does add real behavioral context: the default response is lean, a section is flagged as premium (`podcast_recommendations`), and `people` slugs feed `particle_person_get`. It stops short of covering pagination, rate limits, or error behavior, so not a 5.

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

Conciseness4/5

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

Three sentences, front-loaded with the core purpose before the optional sections and the alternative-tool note. The include enumeration largely duplicates the schema, which is mild redundancy, but nothing is wasted or buried.

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?

There is no output schema, so the description carries the burden of describing the return payload — and it does, itemizing the identifiers, name, and description, plus what each optional section yields. Combined with the routing guidance, an agent has everything needed to call it correctly.

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 description coverage is already 100%, setting a baseline of 3, but the description adds value the schema does not: it explains the cross-tool linkage (person slugs feed `particle_person_get`) and reinforces the lean-by-default include semantics. `product_status` filtering is left to the schema, which fully documents it.

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?

States a specific verb and resource ('Return a bundled profile for one company') and enumerates exactly what the bundle contains (identifiers, name, description). It also routes away from a near-neighbor by naming `particle_company_get_podcast_ad_presence` for sponsor analytics, so the agent can distinguish it without opening a schema.

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?

Gives explicit when-to-use guidance for each optional section via `include`, states the default is lean and to request only what is needed, notes you can skip `particle_company_resolve` when the domain is known, and names an alternative tool for a different use case. When/when-not/alternative are all covered.

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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