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cliwant

mcp-sam-gov

by cliwant

fac_search_audits

Read-only

Search entity Single Audit summaries from the Federal Audit Clearinghouse. Filter by UEI, state, audit year, and federal award amounts to identify audit risk.

Instructions

Search entity Single Audit summaries from the Federal Audit Clearinghouse (keyless via the api.data.gov DEMO_KEY; api.fac.gov PostgREST general table) — the SUBCONTRACTOR / teaming AUDIT-RISK vetting entry point (2 CFR 200 Subpart F / Single Audit Act; every entity expending ≥$750K/yr in federal awards). Structured filters (all optional, AND-combined): auditeeUei (12-char SAM UEI — the PRIMARY join key to SAM/USAspending/EDGAR, → auditee_uei), auditeeState (2-letter → auditee_state), auditYear (int → audit_year), totalExpendedMin/totalExpendedMax (USD → total_amount_expended gte/lte). limit (≤100, def 25), offset. Returns { audits:[{ report_id, auditee_uei, audit_year, auditee_name, auditee_ein, auditee_state, auditee_city, total_amount_expended, fac_accepted_date }] } + honest _meta. Feed a row's report_id (or the UEI) to fac_get_findings for the audit-RISK flags. ★PII: a HARDCODED select-allowlist surfaces ONLY entity + audit-summary fields and DELIBERATELY EXCLUDES the auditee's personal-contact columns (email/phone/certifying-official name) — the vetting subject is the ENTITY; there is NO caller select/column param. HONESTY: totalAvailable is the EXACT Content-Range total (a response header under Prefer:count=exact; a '*'/absent/non-numeric denominator ⇒ totalAvailable:null + a page-fullness hedge, NEVER 0); total_amount_expended is null-never-0 (a missing amount is null, never 0); a bad column ⇒ PostgREST 400 ⇒ invalid_input (filtersDropped is ALWAYS empty); a genuine [] ⇒ honest empty; 400/403/5xx/timeout/HTML/non-array THROW (206 = success, never a fake empty). NOT a debarment/exclusion/fitness determination — an audit finding is the auditor's opinion; cross-check SAM exclusions + OFAC. Keyless-first via DEMO_KEY (~10 req/hr shared ceiling; set DATA_GOV_API_KEY for production — never logged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows per page, 1..100, default 25.
offsetNo0-based row offset for pagination (default 0).
auditYearNoFilter by audit year (int, → audit_year=eq.). e.g. 2024.
auditeeUeiNoFilter by 12-char SAM UEI (^[A-Z0-9]{12}$; → auditee_uei=eq. — the PRIMARY join key to SAM/USAspending/EDGAR). e.g. 'ZQGGHJH74DW7'.
auditeeStateNoFilter by 2-letter US state code (uppercase; → auditee_state=eq.). e.g. 'CA'.
totalExpendedMaxNoMaximum total federal awards expended (USD, → total_amount_expended=lte.).
totalExpendedMinNoMinimum total federal awards expended (USD, → total_amount_expended=gte.).
Behavior5/5

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

Annotations declare readOnlyHint and openWorldHint. Description adds substantial behavioral details: PII exclusion, honest handling of totalAvailable and total_amount_expended, error behaviors (e.g., 206 success, non-array throw), and rate limits. Far exceeds annotation-only information.

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?

Description is dense and well-structured with clear sections (PII, HONESTY, etc.), but slightly verbose due to extensive edge-case details. Front-loaded purpose is good.

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?

Complete coverage for a parameter-rich tool with no output schema. Describes return format, pagination, error behavior, and integration with fac_get_findings. All necessary context for agent invocation.

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?

Schema coverage is 100% with descriptions. Description adds value by explaining auditeeUei as primary join key, state code casing, min/max for totalExpended, and default/bound for limit. Slight improvement over schema alone.

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?

Clearly states it searches entity Single Audit summaries from the Federal Audit Clearinghouse for audit-risk vetting. Provides source details and distinguishes from sibling tool fac_get_findings by mentioning how to feed report_id.

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?

Explicitly identifies as entry point for subcontractor/teaming risk vetting under 2 CFR 200. Clarifies it is not a debarment/exclusion determination and directs cross-checking with SAM/OFAC. Notes keyless usage and production key. Does not explicitly list alternatives, but context is sufficient.

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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