Skip to main content
Glama

Domain 31 Lattice Arithmetic

lattice_arith_evaluate
Read-only

Compute CAGR, ratio, multiply, divide, YoY series, or product chain using verified SEC EDGAR financial data. Returns the arithmetic result, parity check, and full cell provenance for audit-ready analysis.

Instructions

VLN Domain 31 native arithmetic (cagr|ratio|multiply|divide|yoy_series|product_chain) over verified FINSEC EDGAR cells. Returns arith_method, parity_ok, series[], and cell provenance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opYescagr | ratio | multiply | divide | yoy_series | product_chain
metricNoEDGAR metric, e.g. free cash flow, revenue
companyNoTicker or name when fetching EDGAR cells
factorsNoOptional comma-separated positive factors for product_chain, e.g. 0.79,0.30,1.07,4.5
periodsNoOptional comma-separated fiscal periods for yoy_series/product_chain, e.g. FY2020,FY2021,FY2022
end_periodNoEnd / denominator period, e.g. FY2023
low_tokensNoOptional. When true, returns compact JSON schema.
start_periodNoStart / numerator period, e.g. FY2020

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesList of MCP output blocks containing verified SEC fact payload or SAFE_REFUSAL
Behavior3/5

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

The description states the return structure ('arith_method, parity_ok, series[], and cell provenance'), which adds some behavioral context beyond the readOnlyHint annotation. However, it does not disclose potential error states, authentication needs, or behavior when cells are missing. Since the annotation already marks it as read-only, the description provides moderate additional value but lacks depth.

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 extremely concise: two sentences with no wasted words. The first sentence defines the purpose and operations, the second lists the return values. It is front-loaded and efficient.

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

Completeness3/5

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

With 8 parameters, a full schema, and an output schema (not shown but noted), the description is adequate but incomplete. It does not mention prerequisites (e.g., whether EDGAR cells must already be fetched), nor does it explain how this tool relates to siblings. The return outline is helpful but not comprehensive. Overall, it meets basic needs but has gaps.

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 coverage is 100%, so the schema already describes all parameters. The description lists the return fields but does not add extra meaning or constraints for parameters (e.g., how 'op' affects other fields or valid factor ranges). With full schema coverage, the baseline is 3, and the description does not elevate this.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool performs native arithmetic (cagr, ratio, multiply, divide, yoy_series, product_chain) on verified FINSEC EDGAR cells. It specifies the verb (evaluate arithmetic) and the resource (EDGAR cells). However, it does not explicitly differentiate from the sibling tool 'compute_sec_cagr', which may be a more specific CAGR function, leaving some ambiguity about when to use this versus that.

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 or when not to use this tool compared to its siblings. For example, it does not clarify when to prefer this over 'compute_sec_cagr' or 'query_financial_sec'. There are no explicit usage contexts, prerequisites, or exclusions, which is a significant gap given the presence of related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Calera-Labs/finsec-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server