Elastic MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions what the tool supports (full-text search, filters, aggregations, sorting), it doesn't describe important behavioral aspects like authentication requirements, rate limits, error handling, performance characteristics, or what happens when queries fail. For a complex search tool with 7 parameters, this leaves significant gaps in understanding how the tool behaves.

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 extremely concise and well-structured in a single sentence that efficiently communicates the core functionality and supported features. Every word earns its place, with no redundant information or unnecessary elaboration. It's front-loaded with the primary purpose and follows with key capabilities.

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 complex search tool with 7 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (search results format), error conditions, authentication requirements, or performance considerations. The combination of complexity and lack of structured metadata means the description should provide more contextual information about how to use the tool effectively and what to expect from it.

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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds minimal value beyond the schema by mentioning that the tool supports features like aggregations and sorting, which correspond to the 'aggs' and 'sort' parameters. However, it doesn't provide additional semantic context about parameter interactions, dependencies, or usage patterns beyond what's in the schema descriptions.

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 as executing a search query using Elasticsearch Query DSL, specifying the technology and core functionality. It distinguishes itself from siblings by focusing on search operations, unlike tools for cluster management, user administration, or document retrieval. However, it doesn't explicitly differentiate from 'count' or 'msearch' which are also search-related tools.

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 provides no guidance on when to use this tool versus alternatives like 'count', 'msearch', or 'esql_query'. It mentions supported features (full-text search, filters, aggregations, sorting) but doesn't explain when these capabilities make this the appropriate choice over other search-related tools in the sibling list.

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