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. It mentions matching a query but does not cover critical aspects like whether this is a read-only operation, performance implications (e.g., rate limits), or what happens with invalid inputs. This leaves significant gaps in understanding the tool's behavior.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick comprehension.

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 complexity of a counting operation with query filtering, no annotations, and no output schema, the description is incomplete. It fails to explain return values (e.g., count format, error handling) or behavioral nuances, which are essential for effective tool use in this context.

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 100% description coverage, clearly documenting both parameters ('index' and 'query'). The description adds minimal value beyond the schema, as it only reiterates the query filtering concept without providing additional syntax, format details, or examples. Baseline score of 3 is appropriate given the schema does the heavy lifting.

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 verb ('count') and resource ('documents in an index'), specifying the action and target. However, it does not explicitly differentiate from sibling tools like 'search' or 'get_index_stats', which might also involve document queries or counts, leaving some ambiguity in distinguishing its unique role.

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, such as 'search' for retrieving documents or 'get_index_stats' for broader statistics. It lacks context on prerequisites, exclusions, or comparisons to sibling tools, offering minimal usage direction.

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