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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.

Input Schema

TableJSON 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
date_fromNoYYYY-MM-DD

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover readOnly/idempotent/non-destructive, yet the description adds substantial behavioral context beyond them: total may be null when court/date filters make counting expensive (total_pages/total_note compensate), partial:true means the time budget was hit, and relaxed=true rows hold only kept words. This is exactly the edge-case disclosure the annotations cannot provide.

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?

Dense but well-organized with labeled 'Routing:' and 'Query syntax:' segments and purpose front-loaded. Long for a single paragraph, but the detail is warranted by an 11-parameter tool with no output schema; a few clauses could still be tightened.

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, the description carries the full return-value burden and does so thoroughly (bluebook, url, snippet up to 240 chars, passage_origin, direct_hit, total/partial/relaxed fields, tier and _source backends). 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 description coverage is 100%, so the baseline is 3. The description goes beyond the schema by spelling out the query syntax (boolean AND/OR/NOT, exact phrases, proximity w/5, wildcards, name:/judge:/syllabus: field filters) and the statute-number-as-citation behavior, which the brief schema examples omit.

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 ('Full-text search over 10.7M U.S. court opinions') and immediately scopes it against siblings via explicit routing rules. An agent can distinguish it from find_authority, find_issues, and find_case 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 when-to-use branches: 'a proposition or quoted language -> find_authority; a doctrine name or fact pattern -> find_issues; a party name, statute number or keywords -> search_cases.' Also clarifies find_case's narrower role. Nothing is left to inference.

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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