get_facilityOne facility's full public record plus its most recent state health inspection, if GPS has one.
`slug` is the facility's gps.press slug, e.g. 'macon-state-prison'. Use
list_facilities to find it.| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral nuance via the conditional 'if GPS has one,' indicating the inspection data may not always be present. This goes beyond what annotations alone convey, though it could mention behavior for unknown slugs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long with no wasted words. The core purpose is front-loaded, and the parameter guidance is concise and directly actionable. The example and cross-reference to list_facilities earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter read tool, the description covers what is returned (full public record and most recent inspection), the parameter semantics, and how to discover the parameter value. With annotations covering safety and idempotency, there are no major gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines 'slug' as a string with no description. The tool description compensates fully by explaining that slug is the facility's gps.press slug, giving a concrete example ('macon-state-prison'), and directing users to list_facilities to find valid values. This is exactly the kind of semantic enrichment the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get') and resource ('one facility's full public record plus its most recent state health inspection'). It distinguishes itself from sibling tools like get_facility_staff_roster or get_population_snapshot by focusing on the full record plus inspection, not a specialized subset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete usage context: fetch a single facility's comprehensive record and its latest inspection. It also advises using list_facilities to find the slug, which is helpful. It does not explicitly enumerate when not to use the tool versus each sibling, but the scope is clear enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.