Bitbucket 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. While it states the tool adds reviewers without removing existing ones (a useful behavioral detail), it lacks critical information about permissions required, whether the operation is reversible, error conditions, or rate limits. For a mutation tool with zero annotation coverage, this represents significant gaps in behavioral transparency.

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 appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are organized clearly under 'Args:' and 'Returns:' sections. While efficient, the 'Returns' section could be slightly more informative about the structure of the 'Updated reviewer list'.

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 (mutation operation with 4 parameters), no annotations, and the presence of an output schema (which handles return values), the description is moderately complete. It covers the purpose and parameters adequately but lacks important behavioral context about permissions, side effects, and error handling that would be expected for a mutation 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?

With 0% schema description coverage, the description compensates well by explaining each parameter's purpose: 'repo_slug: Repository slug (name)', 'pr_id: Pull Request ID', 'reviewer: UUID or account_id of the reviewer to add', and 'workspace: Bitbucket workspace (optional if configured)'. This adds substantial meaning beyond the bare schema, though it could provide more context about format expectations or constraints.

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 specific action ('Add a reviewer to a Pull Request') and resource ('Pull Request'), with explicit differentiation from sibling tools like 'remove_reviewer' by noting 'without removing existing reviewers'. This provides a precise verb+resource combination that distinguishes it from alternatives.

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 this tool (to add reviewers without affecting existing ones), but does not explicitly mention when not to use it or name specific alternatives. It implies usage for adding reviewers but lacks explicit exclusions or comparisons to tools like 'approve_pull_request' or 'request_changes_pull_request'.

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