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Glama

US Economic, SEC EDGAR & On-Chain Data (x402)

by net.agentfund

SEC Company Financials (XBRL)

edgar_financials
Read-onlyIdempotent

Key financials for a U.S. public company, pulled from SEC XBRL company facts.

Returns revenue, net income, diluted EPS, total assets, total liabilities, shareholders' equity and cash, each with the most recent ANNUAL and QUARTERLY figure, the period covered, and the form it came from.

Handles two things that trip up naive XBRL queries: filers migrated from the "Revenues" tag to "RevenueFromContractWithCustomerExcludingAssessedTax" under ASC 606, so each concept tries several tags in order; and the SEC repeats facts across filings with differing period lengths, so observations are classified as annual or quarterly by their actual duration rather than by trusting the fiscal-period label.

When to use: fundamentals for valuation or screening, checking latest reported revenue or EPS, pulling balance-sheet lines.

When NOT to use: you need full statements line by line, segment detail, non-GAAP measures, or analyst estimates.

Args:

  • ticker (string, required): a ticker such as "AAPL", or a bare CIK such as "320193".

Returns structuredContent: { "cik": "0000320193", "entity": "Apple Inc.", "ticker": "AAPL", "concepts": { "revenue": { "label": "Revenue", "tag": "RevenueFromContractWithCustomerExcludingAssessedTax", "annual": { "end": "2025-09-27", "start": "2024-09-29", "value": 416000000000, "unit": "USD", "fiscalYear": 2025, "fiscalPeriod": "FY", "form": "10-K" }, "quarterly": { "end": "2026-06-27", "value": 94000000000, "unit": "USD", "form": "10-Q" } }, "netIncome": {}, "epsDiluted": {}, "assets": {} }, "source": "https://www.sec.gov/edgar" }

A concept the filer does not report comes back with tag null and both periods null, rather than a fabricated zero.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesTicker symbol (e.g. "AAPL") or a bare SEC CIK (e.g. "320193").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already establish read-only and idempotent behavior. The description goes further, explaining tag-fallback logic for ASC 606, classification by actual duration rather than fiscal-period labels, and returning null instead of fabricated zeros. No contradiction with annotations.

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?

The description is long but well-structured, starting with the core purpose, then return details, technical nuances, and usage guidance. The extra length is justified by the complexity of XBRL handling and a concrete return example, though it is not as concise as simpler tool descriptions.

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?

With no output schema, the description provides a detailed structuredContent example covering all concepts and period objects, plus behavior for missing concepts. Combined with strong annotations and a single-parameter schema, the agent has everything needed to invoke the tool and interpret results.

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?

The input schema already provides a full description of the ticker parameter with examples of both ticker and CIK formats, and the description merely restates this. With 100% schema coverage, the baseline of 3 applies; the description adds no new semantic detail.

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 clearly states it returns key financials from SEC XBRL company facts, listing specific metrics (revenue, net income, EPS, etc.). It distinguishes itself from sibling SEC tools by focusing on financial figures versus filings, holdings, or insider transactions.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance for valuation/screening and exclusions like segment detail or analyst estimates. This gives the agent actionable direction for selecting this tool against alternatives.

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

All US Economic, SEC EDGAR & On-Chain Data (x402) toolsInspect
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TDQS

A4.5/5.0
Disambiguation5/5

Every tool targets a distinct resource and action. The macro_* tools each cover one economic indicator, the edgar_* tools cover different SEC filing types, and the onchain_* tools are split by chain scope (single vs multi), asset type, and operation. Even the two data-cleaning tools are clearly distinct (JSON repair vs table parsing). No two tools appear to do the same thing.

Naming Consistency4/5

Names follow a mostly consistent snake_case pattern with domain prefixes: macro_*, edgar_*, onchain_*. The exceptions are bls_cpi (could be macro_cpi) and the utility tools structured_json_repair and tabular_to_json, which break the prefix pattern but are still descriptive and predictable. Overall, the convention is clear with minor deviations.

Tool Count3/5

21 tools is in the 'heavy' range (16-25). However, the server spans three distinct domains (US economic data, SEC EDGAR, on-chain data), and each tool serves a unique purpose within its domain. While it feels dense, the breadth is justified by the server's stated multi-domain scope.

Completeness4/5

The tool surface covers the major needs in each domain: key macro indicators, common EDGAR filings and searches, and core on-chain reads. Minor gaps exist (e.g., no PPI, no historical on-chain balances, no company CIK lookup), but agents can work around these with existing tools or by combining them.

Resources