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Calera FINSEC — Certified SEC Memory

by io.github.CaseyYahbara

Exact SEC Metric Recall

query_sec_metric_exact
Read-only

Exact EDGAR metric recall for company+metric+period. Server-side verified fact with provenance; SAFE_REFUSAL when missing. No LLM math.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricYesEDGAR metric, e.g. net income, free cash flow, total revenue, operating cash flow
periodYesFiscal period, e.g. FY2023
companyYesCompany ticker or name, e.g. AAPL
low_tokensNoOptional. When true, returns compact JSON schema.

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 changed
    • 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 observed

TDQS

A4.3/5.0
Behavior4/5

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

The annotation already declares readOnlyHint=true, so the agent knows this is a safe read operation. The description adds valuably beyond that by revealing 'Server-side verified fact with provenance' (meaning results are authoritative and cite sources) and 'SAFE_REFUSAL when missing' (meaning the tool will explicitly decline rather than hallucinate), which is critical behavioral context for a retrieval tool. It also states 'No LLM math,' warning against the tool being used for computation. The only gap is not explaining the format or pagination of the response, but the output schema likely covers that.

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 a single sentence plus two short phrases: 'Exact EDGAR metric recall for company+metric+period. Server-side verified fact with provenance; SAFE_REFUSAL when missing. No LLM math.' Every part earns its place—purpose, data source/quality, error handling, and behavioral constraint. It is front-loaded and dense with useful information.

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 tool's complexity (4 parameters, 3 required), the presence of an output schema to explain return values, and the annotation readOnlyHint=true, the description is complete. It covers the core purpose, the data's verified nature, refusal behavior, and a key limitation (no math). There are no apparent gaps for an agent to make a mistake in invoking this tool.

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 has 100% description coverage, with clear descriptions for all four parameters. The description does not add additional meaning beyond the schema descriptions themselves, but it does tie them together contextually by stating the inputs are 'company+metric+period' and noting the optional 'low_tokens' parameter (though not explicitly named). Since schema coverage is complete, a baseline score of 3 is appropriate.

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 purpose: 'Exact EDGAR metric recall for company+metric+period.' It specifies a verb ('recall'), a resource ('EDGAR metric'), and the required inputs (company, metric, period). This distinguishes it from siblings like 'compute_sec_cagr' (which uses arithmetic) and 'query_sec_sector_peers' (which targets peers).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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

The description explicitly notes 'Server-side verified fact with provenance; SAFE_REFUSAL when missing. No LLM math.' This tells the agent when the tool will return a verifiable result versus refuse (SAFE_REFUSAL), and that it should not be used for mathematical derivations or guessing. It lacks explicit guidance on when to prefer alternatives like 'compute_sec_cagr' for growth rates or 'query_financial_sec' for broader searches, but the sibling names and the 'No LLM math' hint provide adequate contextual clues.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes: CAGR calculation, general algebraic solving, metric querying, sector peer retrieval, and valuation inputs. However, `query_financial_sec` and `query_sec_metric_exact` overlap significantly in returning verified SEC facts, potentially causing confusion about which to use for a given retrieval need.

Naming Consistency3/5

Tool names use mixed prefixes: `query_` for three tools, but `compute_`, `lattice_arith_`, `valuation_`, and `vln_` for others. No single verb-noun pattern is maintained across the set, though names are still readable and descriptive.

Tool Count5/5

Seven tools is a well-scoped number for a specialized financial data server. Each tool serves a clear function without redundancy, and the count is neither too thin nor too heavy for the domain of certified SEC metrics and arithmetic.

Completeness5/5

The tool surface covers the full lifecycle of querying certified SEC data, performing deterministic calculations, retrieving sector peers, and obtaining valuation inputs. An overview tool helps agents understand capabilities. No obvious gaps are present for the stated purpose.

Resources