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Search case law

search_cases
Read-onlyIdempotent

Full-text search over 10.7M U.S. court opinions (all states + federal, via syfert.com). Call this to find case law on a topic, locate a case by name, or find cases citing a statute. 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. Each hit carries bluebook and url (snippet up to 240 chars); a hit whose snippet quotes an earlier case carries passage_origin, the case to cite for that language. A q that is one citation or an "X v. Y" caption naming one case decisively also returns that case as direct_hit above the results (find_case does only that lookup). Query syntax: boolean AND/OR/NOT, "exact phrases", proximity (term1 w/5 term2), wildcards (neglig*), and field filters inside q (name:, judge:, syllabus:). Statute-style numbers like 83.49 are matched as citations to that statute. total may be null: a court or date filter makes the exact count too expensive to compute, and total_pages + total_note then carry the scale. partial: true means the time budget was hit; see partial_note. tier names the caller's plan; _source names the backend that served the search: xeric = the dedicated index, cloud = the cloud index behind a short queue. When no opinion holds every word of a long query, the answer may carry relaxed=true with relaxed_note and relaxed_terms_kept / relaxed_terms_dropped: its rows (closest_match) hold only the kept words. A q that is an "X v. Y" caption also lists, first on page 1, the decisions whose caption carries both parties (abbreviations and agency acronyms read: "Stone v. INS", "ANR Pipeline Co. v. FERC"), marked matched_by caption; the ranked rows follow unchanged. semantic: true ranks opinions by MEANING instead of words (a paraphrased fact pattern finds cases that share none of its words; rows carry similarity, no snippet; state, court, date and status=published filters apply); a text search with no hits is retried that way automatically (semantic_fallback: true).

Input Schema

NameRequiredDescriptionDefault
qYesSearch query. Examples: "premises liability" AND negligence; name:miranda; 768.28 sovereign immunity
pageNoPage number, default 1
sortNoDefault relevance (authority-weighted).
courtNoCourt id filter, comma-separable, trailing * for prefix. E.g. fla* (all Florida), scotus, ca11, fladistctapp1. Also takes a group token covering a whole set of courts: us-circuits, us-districts, us-bankr, fl-fed-districts, fed-veterans, fed-military, fed-immigration, fed-taxtrade, tribal-navajonation, tribal-cherokee. Use find_court to resolve either. Takes precedence over state.
judgeNoJudge name filter
stateNoTwo-letter state code (fl, tx, ny, ca ... all 50 states + dc). Scopes the search to that state's OWN courts — supreme, appellate, circuit and county. Federal district and bankruptcy courts sitting in the state count as federal here, not as state courts, so they are excluded; add them with the court argument. Ignored if court is also given.
statusNopublished or unpublished
compactNotrue = shorter rows (bluebook, url, date_filed, cited_by, status if not published, treatment flag and red/yellow counts, snippet, holding, passage_origin); default false
date_toNoYYYY-MM-DD
per_pageNoResults per page, default 10, max 20
semanticNotrue = rank by meaning (whole-opinion embeddings) instead of matching words; q is then plain language, not boolean syntax. Default false.
date_fromNoYYYY-MM-DD

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / semantic
      Added value: +{
      +  "description": "true = rank by meaning (whole-opinion embeddings) instead of matching words; q is then plain language, not boolean syntax. Default false.",
      +  "type": "boolean"
      +}
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered, yet the description adds substantial behavioral detail beyond them: null totals under filters, total_pages/total_note, partial_note on timeout, tier/_source backend, relaxed=true with kept/dropped terms, and semantic_fallback on empty text searches. This is rich response-shape disclosure the annotations do not carry.

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-loads the purpose and routing before diving into response nuances, and nearly every sentence conveys non-obvious behavior for a 12-param tool. However, it is a single dense run-on paragraph whose length and inline notation (e.g. 'relaxed_terms_kept / relaxed_terms_dropped') make it harder to scan than it needs to be.

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?

With no output schema, 12 parameters, and complex query modes, the description fully compensates by explaining returned fields (bluebook, url, snippet, passage_origin, direct_hit, matched_by, similarity), pagination/total behavior, and fallback modes. Nothing an agent needs to call or interpret results is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description meaningfully enriches q with full query syntax (boolean, phrases, proximity, wildcards, name:/judge:/syllabus: filters) and explains semantic-mode ranking and its interaction with filters. It stops short of clarifying a few filters (e.g. how judge/status interact), so it edges above baseline rather than maxing out.

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?

Opens with a specific verb+resource+scale: 'Full-text search over 10.7M U.S. court opinions (all states + federal)'. It then explicitly distinguishes itself from siblings find_authority, find_issues, and find_case with a routing rule, so an agent can pick the right tool without opening other schemas.

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 routing: 'a proposition or quoted language -> find_authority; a doctrine name or fact pattern -> find_issues; a party name, statute number or keywords -> search_cases.' It also notes find_case performs only the single-caption lookup, giving clear when-to-use and when-not-to-use guidance.

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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