Georgia Prisoners' Speak Public Data

List intelligence

list_intelligence

Read-onlyIdempotent

List GPS intelligence briefings — per-facility and per-issue analyses.

`kind` filters to 'facility' or 'issue'; `contains` filters on the slug.
Read any of them in full with get_page(), e.g.
get_page('intelligence/facility/dooly-state-prison').

Facility briefings are enumerated from the public index. Issue briefings have no
published index, so a maintained list of known slugs is returned and may be
incomplete — `issues_note` says so in the payload.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	No
`contains`	No

Schema Changelog

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

First observedSep 6, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower, but the description still adds substantial behavioral context: facility briefings come from a public index, issue briefings have no published index and may be incomplete, and the payload carries an `issues_note` flag. This completeness caveat meaningfully calibrates agent expectations. The incompleteness note slightly tempers openWorldHint=false, but the description is transparent about the limitation rather than contradictory, so no contradiction is flagged.

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?

Four sentences, each with a distinct job: purpose, parameter semantics, read-onward routing, and completeness caveat. The purpose and filter semantics are front-loaded before the caveat, and every sentence earns its place with no filler.

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?

There is no output schema, so the description must convey return-shape expectations; it does mention the `issues_note` payload field and the incompleteness risk for issue briefings. It does not describe the structure of the returned list items (whether entries expose slugs, titles, dates) or pagination behavior, but for a two-optional-parameter list tool whose safety profile is fully annotated, those gaps are minor.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must carry the full burden for both parameters. It does so completely: `kind` filters to 'facility' or 'issue' (naming the allowed values) and `contains` filters on the slug. This fully compensates for the empty schema documentation.

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 first sentence states a specific verb (list), a resource (GPS intelligence briefings), and scope (per-facility and per-issue analyses). It distinguishes itself from the sibling get_* tools, especially get_page, by framing itself as the enumeration step versus the read-in-full 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 explicitly names get_page as the alternative for reading a briefing and gives a concrete chaining example, get_page('intelligence/facility/dooly-state-prison'), which routes the agent from list to read. It lacks explicit when-not-to-use or exclusion conditions, e.g., 'if you already know the slug, call get_page directly,' so it falls just short of full routing 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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