Search Judges

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

With no annotations, the description fully discloses matching behavior (case insensitive substring), result cap (50), and default behavior for empty q. It also mentions the resource cost (no AI credits). It does not describe the return format, but for a simple autocomplete tool, this is adequate.

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?

Three efficient sentences, front-loaded with purpose and usage, with no redundant or filler content. Every sentence adds value.

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?

For a simple tool with one parameter and no output schema, the description covers the core behavior, the default case, the cap, and the intended use case. It is complete enough for an agent to use correctly, though it omits the exact response shape (e.g., list of names).

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% for the single 'q' parameter, so the schema already explains the case-insensitive substring match. The description adds value by noting that an empty or omitted q returns the first 50 names, but this is behavioral context rather than parameter semantics. Baseline 3 is appropriate.

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 it is an autocomplete over the combined Supreme Court and High Court judge name list, with a specific verb ('Autocomplete') and resource. It distinguishes itself from sibling tools by explicitly tying it to getting exact spellings before using search_indian_court_cases.

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?

Explicitly states when to use ('to get the exact spelling of a judge name before passing it to search_indian_court_cases as judgeName'), names the alternative tool, and clarifies that no AI credits are consumed. This gives clear context for when to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.