Lists regulatory frameworks known to the catalog, their authority-basis prefixes, and the record-py gap analyses each triggers, helping clients map obligations to validations.
Regulatory frameworks known to the catalog, their authority_basis prefixes, and which record-py gap analyses each one triggers.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| frameworks | Yes | ||
| gap_analyses | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is fully covered. The description adds domain context by specifying the semantic content returned (authority_basis prefixes, gap-analysis triggers), but since an output schema exists and enumerates returns, that addition is modest rather than essential.
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?
A single compact sentence with no filler, front-loading the resource and then the payload contents. Every clause earns its place by naming distinct returned data.
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?
With an output schema present, return values need not be re-described, and zero parameters mean there is no argument behavior to explain. The description covers the remaining gap adequately, though a note on when to consult this catalog before other tools would make it fully self-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 tool takes zero parameters, so there is nothing to document and the baseline of 4 applies. The description does not need to explain any argument semantics.
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 names the resource (regulatory frameworks) and enumerates what the listing includes: authority_basis prefixes and the record-py gap analyses each framework triggers. It is a noun phrase rather than an explicit verb, but the listing intent is unmistakable. It is reasonably distinguishable from siblings like list_rules and get_rule, though it does not explicitly say it is the framework catalog versus the rules catalog.
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?
No when-to-use, when-not-to-use, or alternative is stated. An agent must infer from the name alone that this is the discovery step before calling list_rules or get_rule. Given the sibling set, a single clause about fetching frameworks first would have added real routing value.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.