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Case docket entries

get_case_docket
Read-onlyIdempotent

List a public case's docket entries newest first, with document availability. Paginate with next_cursor. At most 50 per call. Entries the site does not publish are omitted and only counted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoEntries to return, 1-50. Defaults to 50.
cursorNoOpaque pagination token from a previous call's next_cursor. Omit for the first page.
case_urlYesFull Docket Nexus case URL, as accepted by get_case.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / case_url / description
      Added value: +"Full Docket Nexus case URL, as accepted by get_case."
    • addedInput schema / properties / cursor / description
      Added value: +"Opaque pagination token from a previous call's next_cursor. Omit for the first page."
    • addedInput schema / properties / limit / description
      Added value: +"Entries to return, 1-50. Defaults to 50."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

The description goes well beyond the annotations by disclosing ordering (newest first), pagination via next_cursor, the 50-item cap, document availability, and the fact that unpublished entries are omitted but counted. This gives an agent a realistic behavioral model before calling.

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?

Three short sentences, each carrying distinct information: what is listed, how pagination works, and how unpublished entries are handled. It is front-loaded with the most important purpose and has no filler.

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

Completeness4/5

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

The description covers purpose, ordering, pagination, limit, and filtering behavior. Since there is no output schema, it would be stronger if it briefly described the shape of a docket entry or how 'document availability' appears in results, but it is still sufficient for an agent to invoke the tool confidently.

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 coverage is 100%, so the baseline is 3. The description reinforces cursor usage and the 50-item limit, but these details are already present in the schema. It does not add meaningfully new semantics for case_url or the cursor format beyond what the schema provides.

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?

Description begins with a specific verb and resource: 'List a public case's docket entries newest first.' It adds order and document-availability scope, which clearly distinguishes this from siblings like get_case or get_document. The public-case qualifier also prevents confusion with private or internal tools.

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 clear context for use: retrieving docket entries for a public case. It also implies limitations ('public case') but does not explicitly name alternative tools or state when NOT to use this one. It lacks direct sibling differentiation, but the intended use case is obvious.

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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