graphql_knowledge_query

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It adds one important operational detail ('Requires the GraphQL server to be running') but does not mention that queries are read-only/non-destructive, potential rate limits, or what happens if the server is unavailable. This is a moderate level of transparency for a query tool.

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. The first sentence efficiently lists the tool's core capabilities, and the second covers the operational prerequisite. Every word contributes meaning.

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 is complex due to the open-ended nature of GraphQL, and there is no output schema. The description gives a high-level overview and the schema covers parameters, but it does not clarify what the response format will be, error handling, or examples of typical queries beyond what the schema shows. This leaves some ambiguity for an agent deciding whether to invoke the tool.

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%, with each parameter already well-documented (query includes examples, endpoint has a default, variables are described). The description adds no parameter-specific meaning beyond what the schema provides, so the baseline score of 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 specifies a verb ('Query'), a resource ('GraphQL Knowledge Hub API'), and distinct use cases ('structured knowledge discovery, project graph traversal, pipeline exploration, cross-project relationship analysis'). It uniquely distinguishes this tool from all sibling tools, which are focused on notes/context rather than direct GraphQL access.

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 clear context for when to use the tool (for GraphQL-based knowledge discovery and graph traversal) and mentions a prerequisite (server must be running). However, it does not explicitly exclude alternatives or name competing tools. This is still sufficient because the sibling tools serve different purposes.

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