Indiana Code

Search reviewed case transcriptions

case_transcription_search

Read-onlyIdempotent

Search reviewed historical reports and scanned-opinion derivatives, separate from primary opinion bodies. Historical editorial headnotes and the initial source notice and caption of a modern scan are excluded from search. Appended correction orders are searched as complete components, including their captions. Each result identifies its derivative type and retains source provenance, source notices and date limitations. These are not official verbatim judicial text or citator results; citation eligibility is not evaluated. case_get includes labeled components.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "case_transcription_search"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes
`offset`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 3, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, closed-world behavior, and the description adds real substance beyond them: which content is excluded from search, how appended correction orders are indexed, what provenance and date limitations accompany results, and the caveat that citation eligibility is not evaluated. Pagination and limit behavior remain undisclosed.

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?

Five compact sentences with no filler; scope and exclusions are front-loaded. Some clauses are dense and slightly repetitive ('retains source provenance, source notices'), but nothing is expendable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Behavioral scope is well covered and an output schema exists so return values needn't be explained. However, with 0% schema coverage the complete absence of parameter guidance (especially query form and pagination) leaves a real gap for a three-parameter search tool.

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

Parameters2/5

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

Schema description coverage is 0% and the description says nothing about query syntax, matching semantics, or the limit/offset parameters. With three bare parameters, the description should compensate but instead focuses entirely on content scope.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific scope: searching reviewed historical reports and scanned-opinion derivatives, explicitly separate from primary opinion bodies. It is distinguishable from a generic opinion search, though it never names the sibling case_search and leans on jargon ('scanned-opinion derivatives') that may require domain knowledge.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied through exclusions (not primary opinion bodies, not citator results) and a pointer to case_get for labeled components, but there is no explicit when-to-use or when-not versus case_search or case_get. The agent must infer selection from negative statements rather than direct routing.

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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