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haksanlulz

mcp-courtwatch

by haksanlulz

oral_arguments

Search oral argument audio by case, court, or topic to get argue date, judges, duration, and MP3 link—then hear how a case was actually argued.

Instructions

Search oral-argument audio recordings (CourtListener type=oa): case name, court, argue date, judges on the panel, duration, and an MP3 download link. Useful for hearing how an issue was actually argued. Works without a token.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (case name, party, or topic).
courtNoOptional court id filter (e.g. "scotus", "ca2"). Get ids from court_list.
limitNoMax results from this page (1-20, default 20).
cursorNoOpaque cursor from a previous response's next_cursor.
order_byNoSort order (default relevance; newest/oldest sort by argue date).
argued_afterNoOptional ISO date (YYYY-MM-DD); only arguments on/after.
argued_beforeNoOptional ISO date (YYYY-MM-DD); only arguments on/before.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It clarifies the operation is a search (read-only), specifies the result fields including the MP3 download link, and discloses that no authentication token is needed. It doesn't mention pagination or rate limits, but for a read-only search tool these are minor omissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences provide the essential information with zero filler. The primary action and resource are front-loaded, followed by a use case and the auth note, making it easy for an agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema or annotations, the description covers what is searched, what is returned, the intended use case, and authentication requirements. The 100% schema coverage handles parameter details, so nothing critical is missing for an agent to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter is already documented with its own description. The tool description does not add parameter-level syntax or clarification beyond restating the domain fields, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Search oral-argument audio recordings'), names the CourtListener type (oa), and enumerates the returned fields (case name, court, argue date, judges, duration, MP3 link). This clearly differentiates it from siblings like opinion_search, which focus on written opinions, and docket_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a concrete usage scenario—'hearing how an issue was actually argued'—and notes that it works without a token. It does not explicitly name alternatives or state when not to use it, but the sibling tool list and the framing provide enough context for an agent to route correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.