batch_query

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

No annotations are provided, so the description carries the burden. It discloses parallel execution and returning all results together, but lacks behavioral details like error handling for individual queries, rate limits, or read-only nature. It adds some context beyond the schema but not comprehensive.

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, direct, and front-loaded. Every sentence adds value: first defines the core function, second gives use cases. No wasted words.

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's complexity (parallel queries, no output schema), the description adequately conveys purpose and input structure. It explains return behavior ('return all results together') but could specify result ordering or error aggregation. Still sufficient for selection.

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 coverage is 100% with parameter descriptions in the schema itself. The description echoes the schema by stating each query has instance, SQL, and time range, but doesn't add new semantic meaning or format details beyond what's already in the structured input definition.

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 executes multiple SQL log queries in parallel across instances and returns combined results. It uses specific verbs and resources ('execute multiple SQL log queries') and distinguishes itself from siblings like search_logs (single query) by emphasizing parallelism and batch capability.

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 explicit use cases: 'comparing data across instances or fetching related signals in a single round trip.' While it doesn't list exclusions or alternatives, the context makes it clear this is for multi-query scenarios, with siblings implying single-query alternatives.

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