lc_execute_search_query

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

With no annotations provided, the description carries the full burden. It mentions paginated behavior and bounded polling, but fails to disclose important traits such as whether the search is asynchronous, if it blocks, rate limits, validity of query_id, or any side effects. The description is too sparse for a tool with this complexity.

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 sentence that is front-loaded with the main action and output. It is efficient with no wasted words, though it could benefit from additional detail without sacrificing conciseness.

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 has 5 parameters, no output schema, no annotations, and many sibling tools, the description is incomplete. It lacks parameter explanations, return value format, and usage context necessary for an agent to use the tool correctly.

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 5 parameters with 0% description coverage, yet the description provides no explanation of any parameter (e.g., what 'oid' represents, format of 'query', meaning of 'start' and 'end'). It fails to add any meaning beyond the schema, leaving the agent to guess.

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 it starts a paginated LCQL search and returns a query_id for bounded polling. The verb 'start' and resource 'LCQL search' are specific, and the mention of 'paginated' and 'bounded polling' distinguishes it from siblings like lc_execute_saved_query (which executes a saved query) and lc_poll_search_query (which polls results).

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 implies usage for starting paginated searches meant for bounded polling, but it does not explicitly state when to use this tool versus alternatives like lc_estimate_search_query or lc_execute_saved_query. It lacks explicit 'when to use' or 'when not to use' guidance.

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