atlassian-browser-mcp

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds valuable behavioral context beyond this: it specifies platform restrictions ('Server/Data Center only'), raises NotImplementedError for Jira Cloud, and outlines the return structure ('JSON string with queue metadata, issues, and pagination metadata'). This enhances transparency without contradicting annotations, though it could detail error handling or rate limits more.

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 well-structured and front-loaded, starting with the core purpose, followed by platform restrictions, parameter list, return details, and error handling. Each sentence serves a distinct purpose without redundancy, making it efficient and easy to parse for an AI agent.

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 (4 parameters, read-only operation) and the presence of annotations (readOnlyHint) and an output schema (implied by 'Returns' section), the description is complete. It covers purpose, platform constraints, parameters, returns, and errors, providing all necessary context for correct tool invocation without needing to explain return values in detail.

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 clear descriptions for all parameters (e.g., 'Service desk ID (e.g., '4')', 'Starting index for pagination (0-based)'). The description lists parameters but adds minimal extra meaning beyond the schema, such as clarifying pagination context. Given the high schema coverage, a baseline score of 3 is appropriate, as the description does not significantly enhance parameter understanding.

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's purpose: 'Get issues from a Jira Service Desk queue.' It specifies the verb ('Get') and resource ('issues from a Jira Service Desk queue'), but does not explicitly differentiate it from sibling tools like 'jira_get_service_desk_queues' or 'jira_get_sprint_issues', which handle related but distinct resources. This makes it clear but not fully sibling-distinct.

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 context for when to use this tool: 'Server/Data Center only. Not available on Jira Cloud.' It also implies usage for paginated retrieval of queue issues. However, it does not mention when not to use it or name specific alternatives among siblings, such as 'jira_get_service_desk_queues' for queue metadata or 'jira_search' for broader issue queries, leaving some guidance gaps.

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