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UHQ-Actual
by UHQ-Actual

List DOL LCA Disclosure Fields

lca_disclosure_fields

Retrieve field names from DOL LCA disclosure XLSX files using filters for fiscal year, quarter, employer, and more.

Instructions

Read field names from a DOL LCA disclosure XLSX file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoWorksite or employer city substring filter.
stateNoTwo-letter worksite or employer state filter.
dateToNoInclusive upper date bound in YYYY-MM-DD form.
quarterNoFiscal quarter, 1 through 4.
socCodeNoSOC code prefix filter.
dateFromNoInclusive lower date bound in YYYY-MM-DD form.
jobTitleNoJob title substring filter.
dateFieldNoDOL date field to filter on, default DECISION_DATE.
localFileNoOptional path to an already-downloaded official LCA disclosure XLSX file.
naicsCodeNoNAICS code prefix filter.
visaClassNoVisa class, such as H-1B, H-1B1, or E-3.
caseStatusNoCase status, such as CERTIFIED or DENIED.
fiscalYearNoFederal fiscal year, such as 2026.
maxResultsNoMaximum rows to return.
searchModeNoEmployer match mode.
employerNameNoEmployer name filter.
minAnnualWageNoMinimum annualized offered wage.
Behavior2/5

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

With no annotations, the description must fully convey behavior. It only says 'Read field names,' omitting details about data sources, filtering effects, output format, or side effects. The 17 optional parameters suggest complex behavior not explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence with no fluff. However, it could incorporate more context without significant bloat, given the tool's complexity.

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

Completeness2/5

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

Given 17 optional parameters, no output schema, and no annotations, the description is inadequate. It fails to explain the relationship between parameters and the returned field names, nor the source of the XLSX file.

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 each parameter. The description adds no additional meaning beyond reading field names, failing to explain how parameters affect the output (e.g., do filters limit fields or rows?). Baseline 3 is appropriate.

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 the tool reads field names from a DOL LCA disclosure XLSX file, specifying the verb and resource. However, it does not distinguish it from sibling tools like foreign_labor_fields or whd_enforcement_fields, which also list field names for different datasets.

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?

No guidance is provided on when to use this tool versus alternatives such as lca_disclosure_files or lca_search. The description lacks context about prerequisites or typical use cases.

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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