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cliwant

mcp-sam-gov

by cliwant

sam_search_wage_determinations

Read-only

Search Service Contract Act (SCA) or Davis-Bacon (DBA) wage determinations by locality. Filter by state, county, or WD number/title to find governing wage rates.

Instructions

Find the Service Contract Act (SCA) or Davis-Bacon (DBA) wage determination(s) governing a locality (keyless SAM SGS). Filter by coverage (sca|dba), state (2-letter, server-side), county (client-side), or WD number/title. Returns the structured WD list; follow with sam_get_wage_rates to read the rate table. NOTE: query matches WD number/title only, NOT occupation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo0-based page index (default 0).
limitNoPage size (default 20, max 50).
queryNoMatches the WD NUMBER/TITLE only — NOT occupation/job title (q=guard returns 0).
stateNo2-letter USPS state code (e.g. 'VA'), applied SERVER-SIDE. A full name is applied client-side instead.
countyNoCounty name (substring match), applied CLIENT-SIDE over the fetched page only (the API has no county filter).
coverageYesWhich wage-determination law: 'sca' (Service Contract Act — services) or 'dba' (Davis-Bacon Act — construction). 'dba' is normalized to the API's 'dbra' index.
activeOnlyNoOnly currently-active WDs (default true).
standardOnlyNoOnly standard (non-non-standard) WDs (default true).
Behavior5/5

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

The description goes beyond the 'readOnlyHint' and 'openWorldHint' annotations by detailing behavior: filters are applied server-side (state) or client-side (county) due to API limitations, and coverage 'dba' is normalized to 'dbra'. It explains the pagination defaults and the open-world nature of results.

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 concise (4 sentences) with a front-loaded purpose sentence, followed by filter details and a crucial note. Every sentence adds value, no redundancy.

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 8 parameters and no output schema, the description covers all parameters, explains API limitations, and provides usage sequence (follow with sam_get_wage_rates). It is complete for an effective search tool, addressing potential confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3. The description adds significant value by explaining the client-side vs server-side behavior for state and county, the normalization of 'dba' to 'dbra', and reinforcing that 'query' only matches WD number/title. This clarifies parameter usage beyond the schema.

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 states it 'Find the Service Contract Act (SCA) or Davis-Bacon (DBA) wage determination(s) governing a locality (keyless SAM SGS).' It clearly defines the core action (searching wage determinations) and the specific resources (SCA/DBA). It distinguishes itself from the sibling tool 'sam_get_wage_rates' by noting the follow-up step.

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 provides clear context on when to use the tool (to find wage determinations by locality) and includes a critical note that 'query matches WD number/title only, NOT occupation', preventing misuse. It also directs to use 'sam_get_wage_rates' to read the rate table. However, it does not explicitly state when not to use this tool over alternative search methods, but the sibling list includes many unrelated tools.

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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