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by io.github.pipeworx-io
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Fac Audit Findings

fac_audit_findings
Read-onlyIdempotent

Audit findings recorded against single audits — the compliance exceptions, material weaknesses, significant deficiencies, questioned costs and repeat findings that auditors reported. Query by report_id, or by recipient name/UEI to sweep every audit that recipient filed. Answers "has this grant recipient had audit findings, and were they material or repeated".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ueiNoRecipient UEI; resolves that recipient's audits, then their findings. Alias: auditee_uei.
limitNoMax finding rows to return, 1-200 (default 50).
report_idNoFAC report id to pull findings for. Aliases: id, audit_id.
audit_yearNoRestrict the resolved audits to one audit year (used with auditee_name or uei).
auditee_nameNoRecipient name substring; the tool resolves matching audits first, then their findings. Aliases: query, q, name.
include_textNoAlso attach the narrative finding text when FAC exposes it (default false — the text rows are long).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "limit": 5,
-    "uei": "MPUMNJU3G315"
-  }
-]New value: +[
+  {
+    "limit": 25,
+    "report_id": "2024-08-GSAFAC-0000063952"
+  }
+]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds value by clarifying the output (types of findings) and the include_text parameter behavior. No contradictions with annotations.

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?

Two sentences: first defines findings, second gives usage guidance. Every word serves a purpose; no redundancy. Front-loaded with the core purpose.

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?

No output schema exists, so description must cover return values. It lists finding types but does not detail response structure (e.g., fields, pagination). Adequate but could be more complete for a 6-parameter tool without output schema.

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%, so baseline is 3. The description does not add significant new semantics beyond what the schema already provides, merely rephrasing parameter purposes in a narrative.

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 explicitly states the tool retrieves audit findings for single audits, listing specific types (compliance exceptions, material weaknesses, etc.) and the question it answers. It differentiates from sibling FAC tools by focusing on findings and mentioning query methods.

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 guidance: query by report_id or sweep by recipient name/UEI. It answers a specific question ('has this grant recipient had audit findings...'). Alternatives are implied through siblings, though no explicit when-not-to-use.

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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