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datasets_sec_companies_search

Search the SEC companies dataset. Searches SEC-reporting companies stored in a search index — normalized filing history, financial-statement rollups (latest annual/quarterly revenue, net income, total assets) and trailing-90-day insider…

Instructions

Search the SEC companies dataset. Searches SEC-reporting companies stored in a search index — normalized filing history, financial-statement rollups (latest annual/quarterly revenue, net income, total assets) and trailing-90-day insider (Form 3/4/5) activity. Sort enum: relevance, name_asc, revenue_desc, net_income_desc, filing_recent_desc, insider_activity_desc. entity_type, sic, sic_description, exchange, and state_of_incorporation are open filters over the exact values EDGAR reports for each filer (not a fixed enum) — discover real values via the matching facet. Billing: this search costs 1 credit per record returned, with a minimum of 2 (an empty result costs 2, a full page of 100 costs 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over the company name, or an exact ticker match, max 256 characters
cikNoExact CIK filter, numeric or zero-padded, e.g. 320193 or 0000320193
sicNoExact SIC industry-code filter, e.g. 3571, max 32 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, name_asc, revenue_desc, net_income_desc, filing_recent_desc, insider_activity_desc
tickerNoExact ticker filter (case-insensitive), e.g. AAPL, max 32 characters
exchangeNoExact exchange filter as reported by EDGAR, e.g. Nasdaq, NYSE, max 64 characters
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
form_filedNoExact form-type filter; keeps only companies that have ever filed this form, e.g. 10-K, 8-K
entity_typeNoExact entity-type filter as reported by EDGAR (e.g. operating), max 64 characters
max_revenueNoMaximum latest-annual revenue in USD (normalized), 0 or greater
min_revenueNoMinimum latest-annual revenue in USD (normalized from the filer's reporting currency at reference rates), 0 or greater
has_financialsNoWhen true, keep only companies that have XBRL financial statements
min_net_incomeNoMinimum latest-annual net income in USD (normalized; negative allowed)
sic_descriptionNoExact SIC description filter, e.g. Electronic Computers, max 128 characters
min_total_assetsNoMinimum latest-annual total assets in USD (normalized), 0 or greater
reporting_currencyNoExact reporting-currency filter, ISO-4217 code, e.g. USD, JPY, EUR
state_of_incorporationNoExact state/country-of-incorporation filter as reported by EDGAR, e.g. DE, CA, max 32 characters
min_insider_txn_count_90dNoMinimum insider (Form 3/4/5) transaction count in the trailing 90 days, 0 or greater

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
      +  "relevance",
      +  "name_asc",
      +  "revenue_desc",
      +  "net_income_desc",
      +  "filing_recent_desc",
      +  "insider_activity_desc"
      +]
  2. Addedv1.6.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral load and does so well on cost: 1 credit per record, minimum 2, an empty result costs 2 and a full page costs 100. It also notes that financial figures are normalized and that insider activity is a trailing-90-day window. Auth, rate limits, and return shape are still unaddressed.

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?

Front-loaded with the one-line purpose, then sorted in logical blocks (data scope, sort, open filters, billing). Dense but every sentence carries information; the billing sentence is slightly long but earns its place.

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

Completeness4/5

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

For a 19-parameter, no-output-schema, unannotated search tool, the description covers dataset scope, filter semantics, sorting, and billing cost. What remains missing is a hint at the returned record shape and page-based pagination behavior, which the schema only partly implies.

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 baseline is 3, but the description adds real meaning beyond the schema: it enumerates the sort enum values, clarifies that entity_type/sic/sic_description/exchange/state_of_incorporation are open filters over exact EDGAR values rather than fixed enums, and points to the facet endpoint for discovering valid values.

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

Purpose4/5

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

States a specific verb and resource ('Search the SEC companies dataset') and enumerates the data covered: normalized filing history, financial-statement rollups, and trailing-90-day insider activity. It distinguishes itself from the facets sibling by pointing there for value discovery, but the boundary against other sec_companies_* siblings (insider, financials, item) is left implicit.

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

Usage Guidelines3/5

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

The description implies usage through its filter notes (open filters, discover via the matching facet) but never states when to pick this tool over the sibling search/item/facets tools, nor any exclusions. Usage is inferred rather than stated.

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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