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Calera-Labs

FINSEC — Certified SEC Memory MCP Server

by Calera-Labs

Compute Certified SEC CAGR

compute_sec_cagr
Read-only

Calculate exact compound annual growth rate (CAGR) from certified SEC filing facts for any company metric across fiscal periods, using deterministic math to prevent confabulation.

Instructions

Exact compound annual growth rate (CAGR) calculation over verified SEC filing facts. Deterministic mathematical execution with zero language model confabulation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricYesEDGAR metric to compound, e.g. revenue, free cash flow, net income
companyYesCompany ticker or name, e.g. AAPL
end_periodYesEnd fiscal period, e.g. FY2023
low_tokensNoOptional. When true, returns compact JSON schema.
start_periodYesStart fiscal period, e.g. FY2020

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
stNoCompact status indicator (OK | REFUSE)
perNoCompact period string
valNoCompact numeric value
hashNoCryptographic filing audit hash
cellsNoValuation pack verified cells dictionary
valueNoVerified financial metric numeric value or computed arithmetic result
periodNoFiscal reporting period
reasonNoExplanation when SAFE_REFUSAL is returned
statusNoVerification status: VERIFIED_SUCCESS | SAFE_REFUSAL | COMPLETE | OK
companyNoCompany name or ticker symbol
conceptNoUS-GAAP / XBRL financial concept
operandsNoUnderlying verified metric operands with accessions
formattedNoFormatted monetary or percentage string
provenanceNoSEC EDGAR filing provenance details

Schema Changelog

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

  1. Changed16 schema fields changedv0.1.1
    • addedOutput schema / properties / cells
      Added value: +{
      +  "description": "Valuation pack verified cells dictionary",
      +  "type": "object"
      +}
    • addedOutput schema / properties / company
      Added value: +{
      +  "description": "Company name or ticker symbol",
      +  "type": "string"
      +}
    • addedOutput schema / properties / concept
      Added value: +{
      +  "description": "US-GAAP / XBRL financial concept",
      +  "type": "string"
      +}
    • removedOutput schema / properties / content
      Removed value: -{
      -  "description": "List of MCP output blocks containing verified SEC fact payload or SAFE_REFUSAL",
      -  "items": {
      -    "properties": {
      -      "text": {
      -        "description": "Serialized verified SEC fact response with cryptographic filing provenance",
      -        "type": "string"
      -      },
      -      "type": {
      -        "description": "MIME content type (text)",
      -        "type": "string"
      -      }
      -    },
      -    "required": [
      -      "type",
      -      "text"
      -    ],
      -    "type": "object"
      -  },
      -  "type": "array"
      -}
    • addedOutput schema / properties / formatted
      Added value: +{
      +  "description": "Formatted monetary or percentage string",
      +  "type": "string"
      +}
    • addedOutput schema / properties / hash
      Added value: +{
      +  "description": "Cryptographic filing audit hash"
      +}
    • addedOutput schema / properties / operands
      Added value: +{
      +  "description": "Underlying verified metric operands with accessions",
      +  "type": "array"
      +}
    • addedOutput schema / properties / per
      Added value: +{
      +  "description": "Compact period string",
      +  "type": "string"
      +}
    • addedOutput schema / properties / period
      Added value: +{
      +  "description": "Fiscal reporting period",
      +  "type": "string"
      +}
    • addedOutput schema / properties / provenance
      Added value: +{
      +  "description": "SEC EDGAR filing provenance details",
      +  "type": "object"
      +}
    • addedOutput schema / properties / reason
      Added value: +{
      +  "description": "Explanation when SAFE_REFUSAL is returned",
      +  "type": "string"
      +}
    • addedOutput schema / properties / st
      Added value: +{
      +  "description": "Compact status indicator (OK | REFUSE)",
      +  "type": "string"
      +}
    • addedOutput schema / properties / status
      Added value: +{
      +  "description": "Verification status: VERIFIED_SUCCESS | SAFE_REFUSAL | COMPLETE | OK",
      +  "type": "string"
      +}
    • addedOutput schema / properties / val
      Added value: +{
      +  "description": "Compact numeric value"
      +}
    • addedOutput schema / properties / value
      Added value: +{
      +  "description": "Verified financial metric numeric value or computed arithmetic result"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "content"
      -]New value: +[]
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

While readOnlyHint already indicates a safe read operation, the description adds valuable behavioral traits: it is 'deterministic mathematical execution with zero language model confabulation,' which reassures users about output reliability. This goes beyond the annotation by promising exactness and no hallucination, which is highly relevant for financial data.

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 exceptionally concise: two sentences with no filler. The first sentence front-loads the core purpose, and the second adds a key guarantee. Every word earns its place, making it efficient for an agent to parse.

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

Completeness4/5

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

With an output schema present and full schema coverage, the description does not need to explain return values or parameter formats. It covers the essential context: it uses SEC data and is deterministic. However, it omits any discussion of data availability, error handling, or use-case boundaries, which slightly detracts from completeness in a complex financial domain.

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 provides 100% coverage for all five parameters, each with descriptive text. The description itself does not elaborate on parameters, but the schema already handles that. Per calibration, a baseline of 3 is appropriate when schema coverage is high and the description adds no extra parameter insight.

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's function: computing an exact compound annual growth rate (CAGR) from verified SEC filing facts. It uses a specific verb ('calculation') and identifies the resource ('SEC filing facts'), and the deterministic language distinguishes it from query-only 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 Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or contrasts with sibling tools like query_sec_metric_exact or query_financial_sec. The context of CAGR computation is implied but not explicitly framed as the recommended option for such calculations.

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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