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Trace a quoted passage

search_quotes
Read-onlyIdempotent

Find every case that has quoted a phrase. Phrase-matched search over 4.3M distinct passages quoted by two or more opinions, ranked by how many cases quote them. Use it to (a) find the true source of half-remembered language BEFORE attributing it, and (b) locate the canonical wording of a rule. Returns the passage, its source case, and adoption counts. When no passage has the exact phrase it falls back to passages sharing its distinctive words (match_kind relaxed), and it adds the mined propositions later courts cite a case for (match_kind proposition). Same tool as find_authority. Routing: a proposition or quoted language -> find_authority (pasted verbatim); a doctrine name or fact pattern -> find_issues; a party name, statute number or keywords -> search_cases. Quotation marks mean pasted from a tool result (opinion text, passage, best_match). If you typed a quote from memory, run verify_quote and use best_match. Run check_brief on the finished draft and apply its corrections. Copy cite_as for the citation (first page, then pin). The first 3 rows carry star_page and cite_as.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quoteYesThe phrase to search for (three or more words; matched as a phrase, not keywords)
stateNoOptional two-letter state code: relaxed and proposition matches are limited to that state's courts (falls back to all courts when it has none); verbatim exact-phrase matches from any court are kept, that state's first

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only say read-only/idempotent, but the description adds substantial behavior: the relaxed fallback when no exact phrase exists, the proposition match kind, the ranked-by-adoption ordering, and the returned fields (passage, source case, adoption counts). It also notes first-3-rows carry star_page and cite_as.

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

Conciseness3/5

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

The core purpose and fallback behavior are front-loaded well, but the text is dense and blends in tangential cross-tool workflow (verify_quote, check_brief, 'copy cite_as', 'quotation marks mean pasted') that dilutes focus on this tool's own invocation.

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 read-only search with no output schema, the description supplies the return shape, the two fallback modes, ranking semantics, and routing, leaving nothing an agent needs in order to call it correctly or interpret results.

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 the schema already documents both the quote ('three or more words, matched as a phrase') and state parameters, including the verbatim-vs-relaxed state scoping. The description adds no syntax or format detail beyond that, so baseline 3 applies.

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?

States a specific verb and resource ('find every case that has quoted a phrase') with concrete scope (4.3M passages, ranked by adoption count). The routing rules explicitly distinguish it from find_authority, find_issues, and search_cases, so an agent can place it among its 16 siblings.

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?

Gives explicit when-to-use cases ((a) sourcing half-remembered language, (b) locating canonical rule wording) plus a full routing block mapping proposition/quoted-language, doctrine/fact-pattern, and party/statute inputs to three different sibling tools. It also names follow-ups (verify_quote, check_brief).

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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