get_enforcement_statsGet summary statistics of enforcement actions. Group by jurisdiction, violation type, risk level, or month to understand enforcement trends.
| Name | Required | Description | Default |
|---|---|---|---|
| date_to | No | End date filter (YYYY-MM-DD) | |
| group_by | Yes | Grouping dimension: "jurisdiction", "violation_type", "risk_level", or "month" | |
| date_from | No | Start date filter (YYYY-MM-DD) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, and the description does not contradict them. It adds that the operation returns summary statistics, but provides no additional behavioral detail such as whether individual actions are excluded or how aggregation is structured.
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?
Two short sentences, both informative: the first states the action and resource, the second explains allowed groupings and intended use. There is no filler or unnecessary repetition.
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 read-only aggregation tool with 100% schema coverage and one required parameter, the description is largely sufficient for an agent to select and call it correctly. It could be slightly stronger by naming what the returned statistics contain, since there is no output schema, but this is a minor gap.
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?
Schema description coverage is 100%, so every parameter (group_by, date_from, date_to) is already documented. The description repeats the group_by options and adds a purpose, but adds no new semantic detail beyond what the schema already provides.
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 uses a specific verb ('Get') and resource ('summary statistics of enforcement actions'), and clarifies that this is aggregate rather than detail-level data. This distinguishes it from siblings like get_enforcement_details and search_enforcement_actions, which concern individual actions.
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?
It states the general use case, 'understand enforcement trends,' and enumerates grouping dimensions, so an agent can infer when to call it. However, it does not explicitly contrast with sibling tools such as search_enforcement_actions or get_enforcement_details, nor state when not to use this tool.
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 targets a distinct resource or operation: enforcement has search/get/stats, courts have list/holidays, judges have search/detail-rules, and filing rules have a dedicated search. The only potential overlap is search_filing_rules vs get_judge_rules, but their descriptions clearly separate source-document rules from judge-specific rules.
All tool names follow a predictable verb_noun pattern using check_, get_, list_, and search_. The resource nouns are consistently placed after the verb, making the tool surface easy to navigate.
9 tools is well-scoped for a court-rules research server. Each tool covers a distinct facet of the domain without redundancy.
The server covers the main read/search workflows: courts, judges, judge rules, filing rules, holidays, and enforcement actions with search/detail/stats. The main gap is that check_compliance only generates a curl command rather than executing the compliance check, which may leave an agent unable to complete that workflow unless it can run external commands.