Georgia Prisoners' Speak Public Data

Get facility staff roster

get_facility_staff_roster

Read-onlyIdempotent

Staff headcount and list for one GDC facility, from a GDC-produced roster.

Answers "how many staff work at X", "how many officers work there", "list the
staff at X". `slug` is the facility slug, e.g. 'dooly-state-prison' (use
list_facilities to find it).

`title` optionally filters by job title. GDC abbreviates heavily: correctional
officers appear as "Correctional Ofc", clerical staff as "Admin Support" or
"Admin Assistant". Try both the plain word and the abbreviation.

ALWAYS report the `observed` date alongside any figure from this tool. A roster
is a single-day observation, not a statement about who works there today.

A zero for a role is a finding about the roster rather than missing data: the
roster holds no nursing, physician or dental titles anywhere in GDC, which is
consistent with medical staffing being contracted rather than directly employed.
Do not assert that reason as established fact.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes
`limit`	No
`title`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 6, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already signal a safe, read-only, idempotent operation, and the description adds substantial behavioral context: the roster is a point-in-time observation, zero values are meaningful findings rather than missing data, and the medical-staffing interpretation should not be asserted as fact. No contradiction with the readOnly/idempotent 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?

The description is long but every sentence earns its place: front-loaded purpose, concrete examples, useful abbreviation guidance, and critical interpretation caveats. It is well structured and contains no filler or repetition.

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?

Despite having no output schema and minimal input schema, the description gives the agent enough to invoke the tool correctly and interpret results: what the data source is, what questions it answers, how to find the slug, how titles are abbreviated, and how to handle dates and zero counts. The only slight gap is the limit parameter behavior, but the overall context is complete for correct use.

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 0% schema description coverage, the description compensates well by explaining slug with an example and clarifying title-filter behavior including GDC abbreviations. It omits any explanation of the limit parameter, though limit is optional and has a default, so this is a minor rather than critical gap.

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 clearly states the tool returns a staff headcount and list for one GDC facility from a GDC-produced roster, and gives concrete example questions it answers. It distinguishes itself from broader tools by emphasizing the single-facility scope and the roster source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly tells the agent to use list_facilities to find the slug, explains how the title filter works with abbreviations, and instructs the agent to always report the observed date. It also warns that the roster is a single-day observation, not a statement about current staffing, which is clear when-not guidance.

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

A4.1/5.0

Disambiguation5/5

Each tool names a distinct resource or action: contraband incidents vs summaries, a single facility vs facility list vs staff roster, and site-wide search vs quote search. The few close pairs are complementary rather than duplicative, and descriptions explicitly indicate when to use each.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (get_*, list_*, search_*). The one outlier, get_gps_guide, still fits the get_<resource> convention, so there is no real style clash.

Tool Count4/5

At 18 tools the server is heavier than a minimal CRUD surface, but it covers a broad public-data domain with a distinct endpoint per dataset or site function. The count feels slightly over the typical sweet spot rather than bloated or redundant.

Completeness4/5

The major GPS data domains are represented: facilities, population, mortality, contraband, parole, length of stay, settlements, and legal text. A few potentially relevant datasets (e.g., a structured budget tool) are not exposed directly, but search_site plus get_page cover most of those gaps.

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