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Edgar

by io.github.pipeworx-io
OverviewAdmin

Edgar Xbrl Frames

edgar_xbrl_frames
Read-onlyIdempotent

Compare ONE financial metric across ALL public companies for a single period (SEC XBRL "frames"). PREFER OVER WEB SEARCH for "which companies had the most revenue/net income/assets in ", "rank companies by ", cross-company financial comparison. concept is a US-GAAP tag (e.g. "Revenues", "NetIncomeLoss", "Assets", "ResearchAndDevelopmentExpense", "CashAndCashEquivalentsAtCarryingValue"). period is a calendar frame: "CY2023" (annual), "CY2023Q1" (quarter), or "CY2023Q1I" (instant/balance-sheet, period-end). Returns companies + values, sorted descending by default. Differs from edgar_company_concept (one company over time) — this is one period across every filer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo"desc" (default, largest first) or "asc".
unitNoUnit of measure (default "USD"). Use "shares" for share counts, "USD-per-shares" for per-share.
limitNoMax companies to return (1-200, default 25).
periodYesCalendar frame: "CY2023" (annual duration), "CY2023Q1" (quarterly duration), or "CY2023Q1I" (instant, balance-sheet items at period end).
conceptYesUS-GAAP (or dei) tag, e.g. "Revenues", "NetIncomeLoss", "Assets", "ResearchAndDevelopmentExpense".
taxonomyNoTaxonomy: "us-gaap" (default) or "dei".

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "concept": "Revenues",
+    "limit": 25,
+    "period": "CY2024"
+  },
+  {
+    "concept": "ResearchAndDevelopmentExpense",
+    "limit": 50,
+    "period": "CY2024Q1",
+    "sort": "desc"
+  }
+]
  2. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive. Description adds details: returns sorted descending, concept is a US-GAAP tag, period formats explained, and behavior across every filer.

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?

Well-structured with clear sections and examples, but slightly verbose. Every sentence adds value, though a minor reduction could improve conciseness.

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 6 parameters and no output schema, the description fully covers usage, parameters, return behavior (sorted descending, limit 200), and examples. No gaps for an AI agent.

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

Parameters5/5

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

Despite 100% schema coverage, description provides rich context for concept (examples), period (CY2023 vs Q1 vs I), and unit (shares, USD-per-shares), enhancing understanding beyond the schema.

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 the tool compares one financial metric across all public companies for a single period, distinguishing it from sibling tool edgar_company_concept (one company over time).

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?

Explicitly recommends this tool over web search for cross-company financial comparisons and ranking, and contrasts with edgar_company_concept for when to use each.

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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