Find log lines and where they come from

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 reveals that the tool performs a single Elasticsearch request, aggregates across namespaces/containers, shows time distribution, and returns a sample of lines. This goes well beyond the title and schema, though it does not discuss limits, edge cases, or error behavior, so it is strong but not exhaustive.

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 two sentences with no filler. It front-loads the core purpose ('One-shot log search'), enumerates the output dimensions in a compact list, and closes with a concrete usage directive. Every sentence earns its place.

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?

The tool has 4 flat parameters and no output schema, but the description compensates by naming the key result groupings: match count, namespaces/containers, time distribution, and sample lines. Combined with the schema's parameter documentation, an agent has enough to call it effectively. It could have mentioned what happens when no matches are found, but that is a minor gap.

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 four parameters and their meanings. The description adds strategic context about the one-shot nature and the window's impact on query time, but it does not need to repeat parameter-level semantics, so baseline 3 is appropriate.

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 a specific verb and resource: one-shot log search that returns match count, source namespaces/containers, time distribution, and sample lines. It distinguishes itself from a generic search or discovery call by explicitly framing itself as an all-in-one alternative to discovery-plus-search.

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 explicit when-to-use guidance: prefer this as the FIRST call for 'where/when/how often is X happening,' and it explains why (answers all three questions in one round trip). It stops short of naming sibling tools explicitly or stating when NOT to use it, but the usage context is clear and actionable.

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