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Find the case to cite for a proposition

find_authority
Read-onlyIdempotent

Find the case to cite for a proposition. Paste the proposition or the language you need authority for VERBATIM; do not convert it to keywords. The result names the source case to cite (source_case), the verbatim passage, and how many courts have adopted it (quoted_by_cases); match_kind says how it matched: exact_phrase (the passage contains your words), relaxed (it shares your distinctive words), proposition (a rule later courts cite that case for). A miss means no court has quoted or been cited for that wording; try find_issues for the doctrine, or search_cases with 3-4 distinctive words. 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
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
propositionYesThe proposition or quoted language, verbatim (three or more words; up to ~300 characters are used)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations cover safety (readOnly, idempotent, destructive=false, openWorld=false), and the description adds genuinely non-obvious behavior: the three match_kinds and what each means, that a miss implies no court quoted that wording, the state fallback rule, and which fields the first 3 rows carry. This is rich behavioral context beyond structured data.

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?

Front-loaded with the core instruction (paste verbatim), followed by routing and workflow guidance in tight sentences with no filler. It is dense and somewhat long, but nearly every sentence carries actionable information.

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?

There is no output schema, so the description must explain returns, and it does: source_case, the verbatim passage, quoted_by_cases, match_kind, star_page and cite_as. Combined with the routing and downstream steps, an agent has everything needed to call and act on this tool.

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?

Schema coverage is 100%, so baseline is 3, but the description adds real meaning the schema does not: paste VERBATIM rather than keywords, quotation marks signal pasted-from-tool text, and the state parameter's relaxed/proposition scoping versus kept verbatim matches.

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+resource ('Find the case to cite for a proposition') and immediately distinguishes itself from siblings by naming find_issues and search_cases as the alternatives for different inputs. An agent can identify this tool's niche without opening any 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?

Gives explicit routing rules: proposition/quoted language -> find_authority (verbatim), doctrine name or fact pattern -> find_issues, party name/statute/keywords -> search_cases. It also states when-not (a miss means no court quoted that wording) and gives a fallback plus a downstream workflow (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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