list_agenciesReturn the USAJOBS reference list of all federal agency sub-element codes and names; useful for resolving agency codes returned by the search tool.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| Code | No | List of agency codes |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {}
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Federal agency reference codes",
+ "properties": {
+ "Code": {
+ "description": "List of agency codes",
+ "items": {
+ "properties": {
+ "CodeName": {
+ "description": "Agency name",
+ "type": "string"
+ },
+ "CodeValue": {
+ "description": "Agency code",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable context by specifying the content type ('USAJOBS reference list of all federal agency sub-element codes and names') and its utility in decoding search results. No contradictions or missing critical behavioral details for a simple list tool.
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 with two clauses, front-loading the purpose and following with a usage hint. Every word earns its place; there is no wasted text.
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 zero parameters and an output schema present, the description provides all necessary context for invoking the tool correctly. It explains both what the tool returns and why it's useful, making it complete for the tool's simple nature.
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 zero parameters, so there are no parameter details to explain. The baseline for zero-param tools is 4. The description reinforces the full scope without any filtering, which is sufficient.
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 identifies the tool's function: 'Return the USAJOBS reference list of all federal agency sub-element codes and names.' It uses a specific verb and resource, and the scope ('all federal agency sub-element codes') distinguishes it from sibling list tools like list_occupational_series.
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 provides an explicit use case: 'useful for resolving agency codes returned by the search tool.' This clarifies when to use the tool, though it does not explicitly name alternatives or state when not to use it. The context is still clear and practical.
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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