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Pacer Party Search

pacer_party_search
Read-onlyIdempotent

Find parties across US federal court cases by name — live PACER Case Locator (PCL) party search across all federal courts. Returns each matching party (name, role) with the associated case number, court, and case title. Requires your own PACER credentials (NextGen); PACER charges your account per search ($0.10/page, capped). Example: pacer_party_search({ party_name: "Nicholas Henderson", _apiKey: "myuser:mypass" })

Input Schema

NameRequiredDescriptionDefault
pageNoOptional 0-based result page (up to 54 matches per page). Default 0.
roleNoOptional party role code to filter by, e.g. "dft" (defendant) or "pla" (plaintiff).
_apiKeyYesYour PACER credentials as "username:password" (NextGen PACER account). PACER bills your account per search.
court_idNoOptional court ID to restrict the search, e.g. "ilndc".
party_nameYesParty name to search for, e.g. "Nicholas Henderson" or "Smith". Required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations (which already declare readOnly, idempotent, openWorld, non-destructive), the description adds the nonzero context an agent needs: it requires the caller's own NextGen PACER credentials and PACER bills the account per search ($0.10/page, capped). It also discloses the return shape (party name/role plus case number, court, case title), which matters since there is no output schema.

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

Conciseness4/5

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

The purpose and cost/auth caveats are front-loaded in three dense sentences, with the example last. It is slightly long due to the embedded example, but nothing is wasted.

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?

For a search tool with no output schema, the description covers what the agent needs: data source, scope, credential and billing requirements, and the fields returned. Nothing essential to correct invocation is missing.

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 (party_name, role, court_id, page, _apiKey) is already documented in the schema. The description supplies a usage example but adds no semantics beyond what the schema provides, so the baseline of 3 applies.

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

Purpose4/5

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

The description gives a specific verb and resource ("Find parties ... by name") and pins the data source ("live PACER Case Locator (PCL) party search across all federal courts"). This implicitly distinguishes it from the sibling pacer_case_search by scoping it to party lookups, but it never names that sibling to make the boundary explicit.

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?

It conveys clear usage context — searching for parties by name in federal cases, with a worked example showing the required credentials. However, it offers no explicit when-not guidance or routing to the sibling pacer_case_search for case-level lookups.

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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