Free sample of the multi-state carrier-distress dataset: headline counts plus a few recent liquidations and recent enforcement fines. Free -- the discovery bait for /v1/solvency and /v1/enforcement.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It reveals it's a free read operation returning sample data. However, it does not mention authentication requirements, rate limits, or what happens if called repeatedly. For a simple sample tool, this is acceptable but not thorough.
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 sentences, front-loaded with the key purpose ('Free sample of the multi-state carrier-distress dataset'). No filler words. Efficient.
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 tool with no parameters and no output schema, the description adequately explains the sample contents: headline counts, recent liquidations, enforcement fines. It also indicates it's free and a discovery bait. However, it could mention if the output is paginated or the format, but given no output schema, this is sufficient.
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 input schema has no parameters (schema description coverage 100% by default). With zero parameters, the description does not need to add parameter info. Baseline 4 is appropriate.
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 a free sample of a multi-state carrier-distress dataset, including headline counts and recent liquidations/enforcement fines. It distinguishes from siblings like get_solvency (full dataset) and get_enforcement_actions (full list) by being a sample.
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 indicates it's a free discovery bait for the full endpoints, suggesting it's meant for exploration before purchasing. However, it does not provide explicit guidance on when to use vs. alternatives like compare_carrier_states or an exhaustive list of when-not-to.
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 clearly distinct purpose, covering different data types (carriers, financials, catastrophes, hazard, etc.) and actions. Even closely related tools like compare_states and compare_carrier_states differ in scope (state comparison vs. carrier footprint), so no ambiguity exists.
The vast majority follow a verb_noun pattern with 'get_' for retrieval and 'list_' for enumeration. A few tools use 'compare_' and 'check_', which are semantically appropriate but introduce slight inconsistency. Overall, the pattern is predictable and readable.
With 40 tools, the count is well above the typical 3-15 range, making it feel heavy. While the domain justifies many endpoints, the presence of over 10 dedicated sample tools adds unnecessary bloat. Consolidation of sample tools could improve scoping.
The server covers a wide range of insurance data domains: eligibility, carriers, financials, catastrophe, hazard, litigation, premium, rates, syndicates, and enforcement. It includes discovery tools and sample data. As a read-only API, it is comprehensive, though a tool for policy-level detail might be a minor gap.
