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 the Cloud-only restriction, mentions NotImplementedError and ValueError exceptions, and notes in the limit parameter description that 'the function will still fetch all the data' despite limiting results. This enhances understanding of performance and error handling 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 well-structured and front-loaded: the first sentence states the core purpose, followed by organized sections for Args, Returns, and Raises. Each sentence adds value, such as clarifying exceptions and parameter defaults, with no wasted words. It efficiently communicates essential information.

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 (batch operation with multiple parameters), the description is complete: it covers purpose, parameters, return values, and exceptions. With annotations indicating read-only behavior and an output schema present (implied by 'Returns' section), no additional details on safety or output structure are needed. It adequately addresses all contextual aspects.

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 detailed descriptions for all parameters in the input schema. The description's 'Args' section lists parameters but adds minimal extra semantics beyond the schema (e.g., it repeats 'None for all fields' for fields, similar to schema). Given high schema coverage, the baseline is 3, as the description doesn't 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 changelogs for multiple Jira issues (Cloud only).' It specifies the verb ('Get'), resource ('changelogs'), scope ('multiple Jira issues'), and platform restriction ('Cloud only'), which distinguishes it from potential server-based alternatives. This is specific and comprehensive.

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 usage: it specifies 'Cloud only' and mentions NotImplementedError for Jira Server/Data Center, guiding when not to use it. However, it does not explicitly compare with sibling tools (e.g., jira_get_issue or other batch tools) or detail alternatives for single-issue changelogs, leaving some room for improvement in sibling differentiation.

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