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sec_frames

Retrieve every filer's reported value for one XBRL concept and reporting period, providing cross-company comparisons from credential-free public SEC EDGAR frames.

Instructions

Cross-company values for one XBRL concept and period. Returns every filer's reported value for one XBRL concept in one reporting period (an EDGAR "frame"). Credential-free public SEC data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitNoUnit of measure, default USD
limitNoMax companies, default 200, max 2000
periodYesReporting frame, e.g. CY2024, CY2024Q1, CY2024Q4I
conceptYesXBRL concept tag, e.g. Assets, Revenues
taxonomyNoXBRL taxonomy, default us-gaap

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / taxonomy / enum
      Added value: +[
+  "dei",
+  "ifrs-full",
+  "srt",
+  "us-gaap"
+]
  2. Addedv1.5.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the disclosure burden; it does add 'Credential-free public SEC data' and explains the frame concept. However, it says 'Returns every filer's reported value' while the schema's limit parameter defaults to 200 and caps at 2000, and it does not mention truncation, pagination, or default taxonomy behavior.

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 two sentences, front-loads the core purpose, and contains no filler. Every clause contributes either the query scope, the return scope, or the access requirement.

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

Completeness3/5

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

For a simple five-parameter read tool this is mostly sufficient: required parameters are clear and defaults are in the schema. However, there is no output schema and the description's 'every filer' claim conflicts with the limit parameter, so an agent could under-specify limit when completeness matters.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3; the description adds only contextual meaning for concept and period ('XBRL concept tag', 'reporting frame'). It does not add value for unit, limit, or taxonomy beyond what the schema already states.

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 a specific verb and resource: retrieving cross-company values for one XBRL concept and reporting period (an EDGAR frame). This clearly differentiates it from sibling SEC tools like sec_financials or sec_company_submissions by emphasizing aggregate, frame-based queries rather than company-specific filings.

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 phrase 'Cross-company values' implies this is for frame-level aggregation across filers rather than individual company queries, but the description never explicitly states when to choose this over siblings or when not to use it. There are no exclusions or alternative tool names mentioned.

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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