Jules MCP Server

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 effectively describes the tool as a list operation with pagination support, which implies it's read-only and non-destructive. However, it doesn't cover aspects like rate limits, authentication needs, error handling, or what 'Jules can work with' entails, leaving gaps in behavioral context.

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 front-loaded with the core purpose in the first sentence, followed by structured sections for 'Args' and 'Returns' that are concise and waste-free. Every sentence adds value, making it easy to scan and understand quickly.

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 low complexity (2 parameters, no nested objects) and the presence of an output schema (handling return values), the description is largely complete. It covers purpose, parameters, and returns adequately. However, it could benefit from more behavioral details (e.g., error cases or 'Jules' context) to fully compensate for the lack of annotations.

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 0%, so the description must compensate. It adds meaningful semantics by explaining 'page_size' as 'Number of sources to return' with a range and default, and 'page_token' as 'Token for pagination from previous response,' which clarifies usage beyond the bare schema. This adequately covers both parameters, though it could detail format constraints for the token.

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 verb ('List') and resource ('available GitHub repositories that Jules can work with'), making the purpose specific and actionable. It distinguishes this tool from siblings like 'get_source' (which retrieves a single source) and 'create_pull_request' (which performs a different action), establishing its unique role in the toolset.

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 by specifying 'available GitHub repositories that Jules can work with,' which helps identify when to use this tool. However, it lacks explicit guidance on when not to use it or direct alternatives (e.g., compared to 'get_source' for a single repository), missing full sibling differentiation.

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