dsl_search

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

No annotations are provided, so the description must carry the full burden. It fails to disclose whether the tool is read-only, requires authentication, or has performance implications. It only describes pagination via limit and offset.

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 concise and well-structured: it starts with the purpose, explains DSL briefly, gives examples, and defines parameters. Every sentence is informative and no words are wasted.

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 tool's complexity, the description covers the query syntax with examples and parameter details. An output schema exists, so return values are not needed. However, error handling or performance considerations are absent.

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?

The input schema has 0% description coverage, but the description includes an 'Args' section that explains each parameter, their defaults, and meaning (e.g., 'query: Atlas DSL query string'). This adds significant value beyond the schema.

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 purpose: 'Execute an Atlas DSL search query.' It explains that DSL supports structured queries with type filters, attribute conditions, and aggregations, and provides example queries. This distinguishes it from sibling tools like quick_search and search_entities.

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 says the tool is 'Useful for complex, precise queries,' implying when to use it. However, it does not explicitly exclude use cases or compare with alternatives, so some guidance is missing.

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