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Calera FINSEC — Certified SEC Memory

VLN Capabilities Overview

vln_capabilities_overview
Read-only

Returns a complete structured overview of all certified EDGAR valuation packs, deterministic financial arithmetic operations, SEC calculations, and product scope boundaries on finsec.caleralabs.com.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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

TDQS

A3.6/5.0
Behavior3/5

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

The description adds that the overview is 'complete' and 'structured', and lists the domains covered. However, it does not disclose behavioral traits such as caching behavior, authentication requirements, or response size. Since annotations already provide readOnlyHint=true, the bar is lower, and the description provides adequate addition without contradiction.

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, front-loaded sentence that efficiently conveys the tool's purpose without wasted words. It starts with the action verb 'Returns' and lists the key content areas, making it easy 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?

Given the tool's complexity (returning a structured overview of multiple domains), the description is reasonably complete. It lists the covered areas and the existence of an output schema covers return structure. However, it does not address how the 'low_tokens' parameter modifies the response, which is a minor gap.

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?

Schema description coverage is 100%, with the single optional boolean parameter 'low_tokens' having its own schema definition. The description does not mention this parameter or explain how it affects the output. Therefore, it adds no additional meaning beyond the schema, resulting in the baseline score of 3.

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 returns a 'complete structured overview' of certified EDGAR valuation packs, deterministic financial arithmetic operations, SEC calculations, and product scope boundaries. This specific verb+resource breakdown distinguishes it from sibling tools like compute_sec_cagr or query_financial_sec, which are focused on specific computations or queries.

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 its siblings. It does not suggest using it for discovery before calling specific tools, nor does it mention any prerequisites or exclusions. The usage context is only implied by the tool's role as an overview, but this is not explicitly stated.

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.