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JustlyAI

DocketBird MCP Server

by JustlyAI

docketbird_search_documents

Read-onlyIdempotent

Search docket entries by title or description in a specific case to find filings labeled with a term.

Instructions

Find docket entries in ONE case whose title/description contains a term.

This matches docket-entry METADATA only (the title and description shown on
the docket sheet), not the text inside the filings. To search the full text
of filing bodies — across all courts or within one case — use
docketbird_fulltext_search instead.

When to use:
- User wants filings TITLED a certain way in a known case
  (e.g. docket entries labeled "motion to dismiss")
- Narrowing down a docket sheet before download

Note: the upstream /documents endpoint has no pagination, so the entire
docket is always fetched and matched in memory; very large dockets can hit
DocketBird's own ~29s gateway timeout (a 504).

Args:
    case_id: DocketBird case ID
    search_term: Term to match against docket-entry titles/descriptions
    page: Page number (starts at 1, default 1)
    page_size: Results per page (default 20, max 50)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
case_idYes
page_sizeNo
search_termYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations (readOnlyHint, etc.), it discloses the lack of pagination and potential 504 timeout for large dockets, and clarifies that it only searches metadata not full text.

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?

Well-organized with a clear first sentence, bulleted usage guidance, a notable caveat, and a parameter list. Every sentence adds value without redundancy.

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?

Given output schema exists, return values are covered. The description explains scope, limitations, and parameter details, fully addressing the tool's complexity.

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

Parameters5/5

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

Despite 0% schema description coverage, the Args section explains each parameter's purpose, defaults, and constraints (e.g., page_size max 50).

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 clearly states it finds docket entries in one case matching metadata (title/description), distinguishing itself from the sibling fulltext search tool.

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

Usage Guidelines5/5

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

Provides explicit when-to-use scenarios (e.g., filings titled a certain way in a known case) and when-not-to-use (full text search), naming the alternative tool.

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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