get_system_statisticsHeadline statistics for the Georgia prison system: population, mortality, demographics, facility counts, releases and health measures, with the update date and data source GPS assembled them from.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful transparency by stating that the output includes the update date and the data source that 'GPS assembled them from', giving the agent context about data provenance and freshness that the annotations do not provide.
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 a single sentence that front-loads the core purpose and uses a compact list for the data categories. It avoids redundant restatements of the tool name. The only minor issue is the slightly awkward phrasing 'GPS assembled them from', but it does not waste words.
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?
Given the tool has no parameters, no output schema, and annotations that cover safety and idempotency, the description supplies the essential missing context: what data categories are included and that update date and data source are part of the result. This is sufficient for an agent to understand what the tool returns without over-explaining.
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 tool has no parameters, so there is no parameter ambiguity to resolve. The description compensates by outlining the returned content categories, which helps the agent understand what to expect even though the schema is empty.
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 states a specific resource ('Georgia prison system') and a clear verb ('get') tied to 'headline statistics', then enumerates the covered categories: population, mortality, demographics, facility counts, releases, and health measures. It is distinct enough from sibling tools like get_population_snapshot or get_mortality_data by framing itself as a system-wide aggregate, though it does not explicitly name those alternatives.
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 phrase 'headline statistics' implies this is the tool for a broad system-level overview, providing some usage context. However, it does not explicitly state when to use this tool versus more specialized sibling tools such as get_population_snapshot or get_mortality_data, so the agent must infer the intended 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.