list_regulationsList regulations in the registry and whether corpus JSON is loaded. Then search_regulation, search_regulations, or list_workflows for a named process.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Most rows to return (default 10 on searches, max 50) | |
| max_chars | No | Cap on the response size in characters (default 8000) |
Changes observed during successful MCP inspections.
Input schema / properties / limitAdded value: +{
+ "anyOf": [
+ {
+ "type": "integer"
+ },
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Most rows to return (default 10 on searches, max 50)",
+ "title": "Limit"
+}Input schema / properties / max_charsAdded value: +{
+ "anyOf": [
+ {
+ "type": "integer"
+ },
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Cap on the response size in characters (default 8000)",
+ "title": "Max Chars"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds a useful behavioral detail (the corpus JSON loaded status) that goes beyond annotations, though it doesn't mention pagination or response format. Given the annotation coverage, this is sufficient.
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 concise sentences: the first states the purpose and scope, the second provides routing guidance. Every word earns its place, and key information is front-loaded.
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 listing tool with two optional params, no output schema, and strong annotations, the description covers purpose, scope, and alternatives. It lacks details on output structure but that is not critical for a read-only list operation. Overall, it is adequately 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% for both limit and max_chars, so the schema already documents them. The description does not add any parameter-specific meaning beyond the schema, matching the baseline of 3.
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 lists regulations and reports whether corpus JSON is loaded, with a specific verb ('List') and resource ('regulations in the registry'). It also distinguishes itself from siblings by pointing to search_regulation, search_regulations, and list_workflows for named-process queries.
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?
Explicitly names alternative tools and the condition for using them ('for a named process'), giving clear guidance on when not to use this tool. This leaves no ambiguity for an agent selecting among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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