Search measured benchmark claims

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

Annotations already establish read-only and closed-world behavior. The description adds genuinely useful behavioral details beyond that: case-insensitive matching, the requirement that every whitespace-separated term matches, and the specific summary fields returned.

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 tightly written sentences cover the resource, matching behavior, return contents, and the main alternative. Every sentence earns its place with no wasted words or repetition.

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 one-parameter search tool with no output schema, the description is thorough: it states the registry scope, search semantics, return fields, and the natural follow-up tool for deeper detail. Nothing essential is missing.

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% and the schema already documents the single query parameter with examples. The description adds extra meaning by explaining the matching rule ('every whitespace-separated term must match') and the scope of keywords across hardware, runtime, model, metric, and workload.

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 states a specific verb and resource: 'Keyword search over the AGmind claim registry of measured local-LLM benchmarks.' It also clearly distinguishes from get_claim by directing users to that tool for full records, and the keyword-search framing differentiates it from list_measured.

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?

The description gives clear context for when to use the tool and explicitly points to get_claim as the alternative for full records. However, it does not explicitly address when list_measured would be preferred over this keyword search.

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