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CivicDataForge Government Evidence

HHS-OIG LEIE Exclusion Screening

civicdataforge--leie-exclusion-screening

Use to find review candidates in the HHS-OIG LEIE by name, valid NPI, state, specialty, or exclusion type. Do not treat a candidate match as identity adjudication or use this tool for facility licensing. Starts the bound Apify Actor with the caller's APIFY_TOKEN, may consume Apify usage, waits up to 60 seconds, and returns at most 1,000 source-linked rows without changing the source list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoscreen checks people/entities and returns evidence records; filter pulls source LEIE records with provenance.screen
stateNoTwo-letter state code, for example TX.
enrichNpiNoLook up matched LEIE NPIs or a caller-supplied NPI in the official CMS registry and return explainable correlation signals. NPI status is not licensure or eligibility.
samApiKeyNoCaller-supplied SAM.gov public API key. Required only when includeSam is enabled; never returned in output.
specialtyNoSubstring match on specialty, such as NURSING, PHARMACY, or HOME HEALTH.
includeSamNoOpt in to the official GSA SAM.gov Exclusions API. Requires your own public SAM.gov API key.
maxRecordsNoCaps LEIE records returned in filter mode.
screenListNoFor screen mode. Each item: { "name": "JOHN SMITH" or "ACME HOME HEALTH", "npi": "1234567893" (optional valid test NPI), "state": "NC" (optional), "ref": "your-id" (optional) }. Name-only matches are normalized exact-name candidates, constrained by state when supplied, and require human review.
exclusionTypeNoOIG exclusion authority code, such as 1128a1 or 1128b5.
maxNpiLookupsNoCaps NPPES calls per run. Remaining rows still receive LEIE results and show that enrichment was skipped.
maxSamQueriesNoCaps SAM.gov calls per run to respect the official API's role-dependent rate limits.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations (readOnlyHint=false, destructiveHint=false) are enriched by the description: it discloses that the tool starts an Apify Actor, may consume Apify usage, waits up to 60 seconds, and returns a bounded result set while 'without changing the source list.' This directly addresses side effects and non‑destructive behavior beyond what the flags alone imply.

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, no filler. The purpose is front‑loaded, then constraints and side effects. Every token earns its place, and it avoids restating obvious parameter details already in the schema.

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

Completeness4/5

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

For a complex tool with 11 parameters and two modes, the description covers the essential operational context (side effects, limits, non‑destructiveness) but does not explain the distinction between screen and filter modes or the shape of the returned records. However, the schema descriptions handle those aspects thoroughly, so the description is adequate for an experienced agent.

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%, and each parameter already has a rich, explanatory description (e.g., mode, enrichNpi notes, samApiKey secrecy). The tool description only summarizes the parameter space ('by name, valid NPI, state, specialty, or exclusion type') without adding detail, so it stays at the baseline 3 for a fully‑documented 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 a specific verb ('find review candidates') and a concrete resource ('HHS-OIG LEIE'), and lists the search dimensions (name, NPI, state, specialty, exclusion type). This clearly distinguishes it from sibling tools that query other registries (EPA, restaurant inspections, etc.) without needing to open any schemas.

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?

It explicitly says when to use the tool ('Use to find review candidates') and gives exclusions: 'Do not treat a candidate match as identity adjudication or use this tool for facility licensing.' It does not name an alternative sibling, but the sibling set is clearly domain‑distinct, so usage context is sufficient. Operational guidance (waits up to 60s, returns ≤1,000 rows) reinforces expected usage.

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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TDQS

A3.9/5.0
Disambiguation3/5

Most domain tools are well-scoped with explicit cross-references (e.g., FL DBPR vs. STR registry, Texas vs. multistate childcare). However, the evidence-gateway overlaps with EPA, U.S. property, and other specialized tools by describing similar intake categories, creating ambiguity about when to use the router versus the domain-specific tool.

Naming Consistency3/5

The specialized tools consistently use the civicdataforge-- prefix with descriptive noun phrases, while the generic actor tools use imperative verb_noun style. The naming is readable and predictable within each subgroup, but the mixed conventions and the awkward doubled prefix in civicdataforge--civicdataforge-evidence-gateway prevent full consistency.

Tool Count4/5

Fourteen tools is reasonable for a broad government-evidence server covering many data domains plus an async run lifecycle. The count is not excessive, though the gateway and several overlapping domain-specific tools add some redundancy.

Completeness4/5

The tool set covers a wide range of evidence domains and provides complete async workflow coverage: launch queries, check run status, fetch dataset items, read KVS records, and abort runs. Minor gaps remain, such as no explicit way to enumerate supported jurisdictions or sources, and the gateway's broad categories are underspecified.

Resources