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SEC Fundamentals API

by com.multyplylabs
OverviewDiscussionsAdmin

Market-Wide Insight

market_insight
Read-onlyIdempotent

Curated analysis computed live across all US public companies, chosen by name: top_companies (rank by a metric, optionally within an industry), movers (largest change in a metric between fy_from and fy_to), sector_landscape (margin medians per industry), metric_trend (yearly sum, median or mean of a metric), capital_returns (buybacks vs dividends by size bucket) or filing_velocity (monthly filing counts for a form type). Each parameter's description says which analyses read it; the response reports the fiscal year(s) used. Use screen_companies for your own criteria and standard_score for F-Score, Z-Score and similar scores. Cost: $0.15 per call; unpaid calls return a payment-required error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fyNoFiscal year for top_companies, sector_landscape and capital_returns, and the default end year for movers and metric_trend; omit for the current fiscal year.
aggNometric_trend only: sum (the default), median or mean.
formNofiling_velocity only: form type to count, e.g. 8-K (the default).
nameYesAnalysis to run: top_companies, movers, sector_landscape, metric_trend, capital_returns or filing_velocity.
fy_toNoEnd year for movers and metric_trend (default fy).
limitNoMaximum rows for top_companies and movers, 1-200 (default 25).
metricNoMetric for top_companies, movers and metric_trend, e.g. revenue (the default), gross_margin, research_development.
monthsNofiling_velocity only: months of history, default 18, up to 120.
fy_fromNoStart year for movers (default fy - 2) and metric_trend (default 2015).
industryNotop_companies only: 2-digit SIC industry group, e.g. 73; omit for every industry.
min_revenueNoMinimum annual revenue in USD for movers (default 1e9) and sector_landscape (default 1e8).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed11 schema fields changed
    • addedInput schema / properties / agg / description
      Added value: +"metric_trend only: sum (the default), median or mean."
    • addedInput schema / properties / form / description
      Added value: +"filing_velocity only: form type to count, e.g. 8-K (the default)."
    • addedInput schema / properties / fy / description
      Added value: +"Fiscal year for top_companies, sector_landscape and capital_returns, and the default end year for movers and metric_trend; omit for the current fiscal year."
    • addedInput schema / properties / fy_from / description
      Added value: +"Start year for movers (default fy - 2) and metric_trend (default 2015)."
    • addedInput schema / properties / fy_to / description
      Added value: +"End year for movers and metric_trend (default fy)."
    • addedInput schema / properties / industry / description
      Added value: +"top_companies only: 2-digit SIC industry group, e.g. 73; omit for every industry."
    • addedInput schema / properties / limit / description
      Added value: +"Maximum rows for top_companies and movers, 1-200 (default 25)."
    • addedInput schema / properties / metric / description
      Added value: +"Metric for top_companies, movers and metric_trend, e.g. revenue (the default), gross_margin, research_development."
    • addedInput schema / properties / min_revenue / description
      Added value: +"Minimum annual revenue in USD for movers (default 1e9) and sector_landscape (default 1e8)."
    • addedInput schema / properties / months / description
      Added value: +"filing_velocity only: months of history, default 18, up to 120."
    • addedInput schema / properties / name / description
      Added value: +"Analysis to run: top_companies, movers, sector_landscape, metric_trend, capital_returns or filing_velocity."
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the description's job is lighter. It adds useful non-annotation behavior: analyses are computed live, the response reports the fiscal year(s) used, calls cost $0.15, and unpaid calls return a payment-required error.

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 the analysis list, then routing and cost. Three sentences cover a complex 11-parameter tool without redundancy or filler.

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?

Given the full input schema, output schema, and safety annotations, the description covers what the tool does, which mode to choose, which alternatives to use, what the response reports, and the cost/error condition. An agent has enough to select and invoke 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 coverage is 100%, so the baseline is 3. The description adds value by defining each named analysis in terms of the parameters that drive it (metric, industry, fy_from/fy_to, form, months, agg), which helps an agent select the right parameter combination per mode.

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 names the tool's resource ('all US public companies'), states the operation ('computed live'), and enumerates six selectable analyses by name, so an agent immediately knows what market_insight returns. It also distinguishes this tool from screen_companies and standard_score, which are the closest sibling alternatives.

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 explicitly routes to alternatives: 'Use screen_companies for your own criteria and standard_score for F-Score, Z-Score and similar scores.' It also clarifies the paid nature and failure mode, which is important before invocation.

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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