get_caseGet a full SCOTUS case from Oyez by term and docket number — question presented, facts, conclusion, decision (winning party, vote split, decision type), which justices were in the majority vs. dissent, advocates, and whether oral-argument audio exists. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | SCOTUS term year, e.g. 2023. | |
| docket_number | Yes | Docket number, e.g. "22-448" (CFPB v. Community Financial Services). |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "docket_number": "22-448",
+ "term": 2023
+ },
+ {
+ "docket_number": "21-1086",
+ "term": 2022
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool is 'Keyless' (no authentication required) and lists the data fields returned. Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description aligns with these. No contradictions; adds value beyond 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 two sentences long, front-loaded with the tool's purpose and key details. Every sentence adds value: the first lists return fields, the second states authentication requirement. No wasted words.
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?
Given the tool's simplicity (2 params, no output schema), the description fully explains what is returned and how to use it. Annotations cover safety and behavior. No gaps remain for an agent to select and invoke correctly.
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%, with clear parameter descriptions and examples. The description reinforces that the tool uses 'term and docket number' but does not add new semantic details beyond the schema. Baseline score of 3 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 retrieves a full SCOTUS case from Oyez, listing specific components (question, facts, conclusion, decision details, justices, advocates, audio existence). It distinguishes from sibling tools like search_cases and cases_by_term, which serve different purposes (search vs. retrieve by exact identifiers).
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 specifies when to use this tool: when you have a specific term and docket number. It implicitly excludes use cases where you need to search by other criteria. However, it does not explicitly mention alternatives like search_cases or cases_by_term, leaving room for ambiguity.
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.