search_decisions

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

Annotations already cover safety (readOnly, openWorld, idempotent, non-destructive). The description adds context about the corpus size (9M+ opinions) and the output contract (citations, cite counts, IDs for get_decision_text), going beyond the structured data without contradiction. It does not discuss rate limits or auth, but the annotations lower the bar.

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

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

The description is four sentences, each earning its place: scope, accepted inputs, domain restriction tip, and output. It is front-loaded with the verb and resource, contains no fluff, and is appropriately sized for the tool's complexity.

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

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

Given the detailed schema covering all parameters and annotations covering behavior, the description completes the picture by explaining the query types, domain restriction, and return value relationship to get_decision_text. No output schema exists, so the explicit mention of return values is sufficient. This is complete for an agent to select and invoke the tool.

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

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

Schema coverage is 100% with detailed descriptions for all 9 parameters, so the baseline is 3. The description mentions query input types and the domain parameter, adding some semantic nuance beyond the schema, but not significantly. The schema already documents these well.

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

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

The description clearly states the tool's function with a specific verb and resource: 'Search U.S. court decisions (CourtListener, 9M+ opinions across federal and state courts).' It also lists accepted input types and mentions returning IDs for get_decision_text, which distinguishes it from sibling search tools like search_regulations.

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

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

It gives clear usage context by specifying what inputs work ('case name, reporter citation, docket number, or issue keywords') and how to restrict court level with 'Use domain to restrict the court tier.' However, it does not explicitly name alternatives or exclusion criteria, so it lacks full when-to-use vs. 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.