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proofread-mcp

by Data-Alchemy-Labs
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TypeScript
Remote

Look up a list of citations in the register

resolve_citations
Read-onlyIdempotent

Resolve up to 500 case citations in one call, returning one line per citation with status: found, ambiguous, not in register, or cannot verify. Ideal for tables of authorities or citation lists.

Instructions

Look up up to 500 case citation strings in proofread.law's register in one call and get one line per citation, in input order: found (the case, court, date, link), ambiguous, not in the register (a register fact with a coverage qualifier, never proof that the case does not exist), cannot verify (Westlaw/Lexis identifier, or a volume the register cannot see yet), known citation, or no citation recognised. Use it for a table of authorities or any list of citations you already have; use check_citations for prose (it also checks names and quotations). Cannot: resolve Westlaw (WL) or Lexis identifiers, check statutes, regulations or secondary sources, or say whether a case is still good law. A red row means 'check this', never 'this case does not exist'; an orange row means the register has nothing to check against, which is not evidence either way. Each citation counts against the resolve quota (1,000 a month free), not the check quota. Without an API key the free tier applies per IP address; a key from sign_up (free tier) identifies the account, and a paid-plan key lifts the limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citesYesCitation strings, one per entry, up to 500.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and open-world, and the description goes further: it explains per-line outcome categories, red/orange row meanings, the open-world caveat, quota counting, and authentication behavior. There is no contradiction with the annotations.

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?

The purpose is front-loaded and every subsequent clause carries operational meaning: outcomes, caveats, usage split, quota, and auth. Despite its length, the description packs high-density guidance with no filler.

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 one-parameter lookup tool with a rich but unspecified output, the description covers the return shape, per-row semantics, error interpretation, limits, quota, and authentication. There is no output schema, so this level of detail is necessary and sufficient.

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

Parameters4/5

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

The schema already fully documents cites as up to 500 strings, so the baseline is 3. The description adds that these are case citation strings, clarifies that Westlaw or Lexis identifiers cannot be resolved, and ties each entry to a returned line in input order, giving the agent more usable constraints than the schema alone.

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 action ('Look up up to 500 case citation strings') and names the resource (proofread.law's register). It also distinguishes list lookup from check_citations, so an agent can select the right tool without opening the schema.

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?

It states exactly when to use the tool ('for a table of authorities or any list of citations you already have') and when to use check_citations instead. It also lists unsupported inputs and quota/API-key conditions, removing ambiguity about prerequisites.

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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