Run ES|QL query

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

No annotations exist, so the description carries the behavioral burden. It discloses the return format (columns/values table), gives a realistic example that shows aggregation behavior, and warns that leading-wildcard LIKE/RLIKE are rejected because they cannot use the index. It does not mention pagination, limits, authentication, or whether the query is constrained to read-only operations, but the core call behavior is transparent.

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: two sentences that front-load the core action and return format, then add practical usage guidance and a key pitfall. Every sentence earns its place with no filler or repetition of schema details.

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 tool with two parameters and no output schema, the description covers the essential operational context: what the tool does, what it returns, when it is preferred, and common text-matching pitfalls with an example. It could further clarify behavior of the optional filter or result limits, but an agent has enough to invoke it successfully.

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 schema already documents both parameters at 100% coverage, providing the baseline of 3. The description adds meaningful semantics for the query parameter with an example, shows how to express status filtering and aggregation, and clarifies text-matching syntax. The optional filter parameter is not elaborated in the description, but the schema covers it and the additional ES|QL guidance adds real value.

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: 'Run an ES|QL query' and explicitly defines the return shape as a 'columns/values table.' It also differentiates the tool from siblings like es_search and es_count by positioning it as the fastest way to aggregate, with a concrete ES|QL example.

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 usage context: use it for aggregation and ES|QL pipelines, and it provides specific guidance for text matching (MATCH/QSTR) and a warning against leading-wildcard LIKE/RLIKE. It does not explicitly name alternative sibling tools or state when to choose those over this tool, so it stops short of a full 5.

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