get_state_public_safety_profileState crime trends with national comparison, Judiciary committee memberships from the state's congressional delegation, and relevant policy area context for criminal justice legislation.
| Name | Required | Description | Default |
|---|---|---|---|
| stateCode | Yes | Two-letter state code (e.g., TX) | |
| yearsBack | No | Years of trend data (default 5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the main behavioral aspects. The description adds valuable context on what the tool returns (crime trends, committee memberships, policy context), which is beyond the annotations.
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 listing three categories of data, which is concise and clear. However, it could be slightly more structured by separating the categories or front-loading the core function.
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?
Without an output schema, the description should explain return format, but it only lists data types. The yearsBack parameter is not mentioned in the description, leaving a gap for the agent. The description is adequate but not complete.
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 baseline is 3. The description does not add additional meaning beyond the schema; it describes tool output but not parameters. The yearsBack parameter is not referenced in the description.
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 the tool provides 'State crime trends with national comparison, Judiciary committee memberships... and relevant policy area context for criminal justice legislation.' This is a specific verb+resource combination that distinguishes it from sibling tools like get_state_climate_profile or get_state_energy_profile.
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 implies usage for criminal justice legislation context but does not explicitly state when to use this tool versus alternatives like search_crime_statistics or other state profiles. No when-not-to-use or exclusions are mentioned.
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 has a clear, specific purpose with detailed descriptions that differentiate them. Prefix patterns like get_district_, search_, analyze_, get_, etc., help an agent easily identify the correct tool for a task.
All tool names use a consistent verb_noun or verb_noun_noun pattern with underscores. The naming convention is uniform across the entire set, with no mixing of styles or ambiguous verbs.
With 47 tools, the count is high but justified by the broad scope of civic data analysis. While some agents might find the sheer number overwhelming, the tools are organized into clear categories (district profiles, searches, analyses) that make navigation feasible.
The toolset covers an impressively wide range of domains: legislation, representatives, districts, voting, committees, campaign finance, lobbying, federal spending, regulations, environment, energy, healthcare, housing, disaster, banking, consumer complaints, crime, vehicles, and more. There are no obvious missing operations for a civic data platform.