Edgar

Edgar Company Concept

edgar_company_concept

Read-onlyIdempotent

AUTHORITATIVE historical financials for any US public company. Source: SEC XBRL filings (the official numbers companies file, not third-party scrapes). Pass a ticker or CIK plus a friendly metric name — Revenue, NetIncomeLoss, Cash, LongTermDebt, EarningsPerShareDiluted — and the tool resolves the right XBRL tag for that filer (post-ASC-606 companies use RevenueFromContractWithCustomerExcludingAssessedTax instead of "Revenues", etc.). Returns both ANNUAL (10-K) and QUARTERLY (10-Q) values by default, each labeled with fiscal_period (FY/Q1/Q2/Q3/Q4) and form, newest first, PLUS a latest field holding the single freshest data point. Q4 rows are DERIVED (FY minus Q1-Q3, marked derived:true) because SEC filers never report a standalone Q4 fact — so "revenue Q4 2024" questions are answerable directly from values; match the requested fiscal_year AND fiscal_period rather than defaulting to latest. Use latest for point-in-time metrics like cash, runway, and debt — it is the newest 10-Q when one is more recent than the last 10-K, so a stale annual figure never masks a newer quarter. Use for "what was AAPL's revenue in 2024", "NVDA's latest cash position", "show me long-term debt trend", anything where you need the SEC-filed number rather than an estimate.

Input Schema

TableJSON Schema

Name	Required	Description
`cik`	Yes	Ticker (e.g., "AAPL") or CIK number (e.g., "320193"). Tickers are auto-resolved.
`period`	No	Which reporting periods to return: "all" (default — annual 10-K + quarterly 10-Q), "annual" (10-K/20-F/40-F only), or "quarterly" (10-Q only). Point-in-time metrics (cash/runway/debt) usually want the default so the freshest quarter is included; use "annual" for clean year-over-year trends.
`concept`	Yes	Metric name. Common: "Revenue" / "Revenues", "NetIncomeLoss", "Cash", "Assets", "Liabilities", "StockholdersEquity", "EarningsPerShareDiluted", "LongTermDebt".

Output Schema

TableJSON Schema

Name	Required	Description
`cik`	Yes	Company CIK number
`label`	Yes	Human-readable concept label
`concept`	Yes	US-GAAP concept tag name
`description`	Yes	Detailed concept description
`company_name`	Yes	Official company name
`annual_values`	Yes	Annual values sorted by fiscal year descending

Schema Changelog

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

Changed1 schema field changedJul 24, 2026

addedInput schema / properties / period

Added value: +{
+  "description": "Which reporting periods to return: \"all\" (default — annual 10-K + quarterly 10-Q), \"annual\" (10-K/20-F/40-F only), or \"quarterly\" (10-Q only). Point-in-time metrics (cash/runway/debt) usually want the default so the freshest quarter is included; use \"annual\" for clean year-over-year trends.",
+  "enum": [
+    "all",
+    "annual",
+    "quarterly"
+  ],
+  "type": "string"
+}

Changed2 schema fields changedMay 14, 2026

changedInput schema / properties / cik / description

Previous value: -"Company CIK number (e.g., \"320193\" for Apple)"New value: +"Ticker (e.g., \"AAPL\") or CIK number (e.g., \"320193\"). Tickers are auto-resolved."

changedInput schema / properties / concept / description

Previous value: -"US-GAAP concept name (e.g., \"Revenue\", \"NetIncomeLoss\", \"Assets\", \"Liabilities\", \"StockholdersEquity\", \"EarningsPerShareDiluted\")"New value: +"Metric name. Common: \"Revenue\" / \"Revenues\", \"NetIncomeLoss\", \"Cash\", \"Assets\", \"Liabilities\", \"StockholdersEquity\", \"EarningsPerShareDiluted\", \"LongTermDebt\"."

Changed1 schema field changedMay 8, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "annual_values": {
+      "description": "Annual values sorted by fiscal year descending",
+      "items": {
+        "properties": {
+          "filed": {
+            "description": "Date filing was submitted",
+            "type": "string"
+          },
+          "fiscal_year": {
+            "description": "Fiscal year",
+            "type": "number"
+          },
+          "period_end": {
+            "description": "Period end date in YYYY-MM-DD format",
+            "type": "string"
+          },
+          "unit": {
+            "description": "Unit of measurement (e.g., USD, shares)",
+            "type": "string"
+          },
+          "value": {
+            "description": "Reported value",
+            "type": "number"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "cik": {
+      "description": "Company CIK number",
+      "type": "string"
+    },
+    "company_name": {
+      "description": "Official company name",
+      "type": "string"
+    },
+    "concept": {
+      "description": "US-GAAP concept tag name",
+      "type": "string"
+    },
+    "description": {
+      "description": "Detailed concept description",
+      "type": "string"
+    },
+    "label": {
+      "description": "Human-readable concept label",
+      "type": "string"
+    }
+  },
+  "required": [
+    "cik",
+    "company_name",
+    "concept",
+    "label",
+    "description",
+    "annual_values"
+  ],
+  "type": "object"
+}

Changed1 schema field changedMay 6, 2026

addedInput schema / examples

Added value: +[
+  {
+    "cik": "320193",
+    "concept": "Revenue"
+  },
+  {
+    "cik": "1652044",
+    "concept": "NetIncomeLoss"
+  }
+]

First observedApr 22, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the annotations (readOnly, idempotent), the description discloses critical behavioral traits: Q4 rows are derived (FY minus Q1-Q3, marked derived:true), the tool resolves the appropriate XBRL tag per filer, and the `latest` field semantics (newest 10-Q when more recent than last 10-K). These details are not evident from annotations or schema and significantly affect how results should be interpreted.

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 dense but well-structured, with each sentence adding critical information: source authority, input flexibility, return format, derived Q4 caveat, latest field usage, and explicit use cases. No filler or repetition. The key details are front-loaded with the tool's purpose, and the formatting (caps for emphasis, backticks for fields) aids scannability.

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 complexity of financial data (fiscal periods, derived values, tag resolution), the description covers all necessary context for an agent to use the tool correctly. It explains the default return behavior, the `latest` field, and how to match historical periods. With an output schema also present, the description is complete without needing to repeat return structures.

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?

The schema already provides 100% coverage for parameters, including the ticker/CIK distinction and metric examples. The description adds valuable semantic context by explaining that the concept parameter is a friendly name that the tool maps to the correct XBRL tag (e.g., post-ASC-606 differences) and lists common metric examples. This enriches the schema's basic descriptions.

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 immediately states the tool's core function: 'AUTHORITATIVE historical financials for any US public company.' It specifies the source (SEC XBRL filings) and the accepted inputs (ticker or CIK plus metric name), and clearly scopes the output to annual and quarterly values. This is a specific verb+resource+scope that distinguishes it from vague or generic tools, even without naming sibling tools.

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?

The description provides explicit usage guidance with concrete examples: 'Use for "what was AAPL's revenue in 2024", "NVDA's latest cash position", "show me long-term debt trend"'. It also differentiates when to use `latest` versus `values` (point-in-time metrics vs. historical matching) and explains the derived Q4 behavior. This is clear when-to-use advice that goes beyond simple context.

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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