graphql_query

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

Annotations indicate readOnlyHint=true, destructiveHint=false, and openWorldHint=false. The description adds critical behavioral context: safety limits (max 1000 results, 10s timeout), large table filtering requirements, syntax details (camelCase, UPPERCASE LIKE), and relationships, without contradicting annotations.

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 long but well-structured: purpose first, then detailed sections for LSMS and LERG. Every sentence adds value, with no redundancy or fluff.

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 two distinct APIs and numerous details (queries, filters, relationships, naming, limits), the description is comprehensive. It covers all necessary context for an AI 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 100% coverage with descriptions for all 3 parameters. The description adds significant meaning beyond the schema: detailed query examples, filter syntax, naming conventions, and specific use cases for each service.

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 GraphQL queries against two distinct APIs (LSMS or LERG), with a specific verb and resource. It warns against mixing syntax, distinguishing it from sibling tools like lerg_query which are more specialized.

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 extensive guidance on when to use each service, including key queries, filtering methods, safety limits, and relationships. It implicitly distinguishes from siblings by being the general-purpose GraphQL executor.

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