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clikader

bitbucket-python-mcp

by clikader

add_pull_request_comment

Add general or inline comments to a Bitbucket pull request to provide feedback or start discussion on specific lines of code.

Instructions

Add a comment to a pull request.

Use this tool to add feedback or discussion to a pull request. Can add general comments or inline comments on specific lines of code.

Args: pr_id: Pull request ID. comment: The comment text to add. repository: Repository slug. If not provided, uses current repository context. workspace: Workspace slug. If not provided, uses the default workspace. file_path: Path to file for inline comment (optional). line_number: Line number for inline comment (optional, requires file_path).

Returns: JSON object confirming the comment was added.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pr_idYes
commentYes
file_pathNo
workspaceNo
repositoryNo
line_numberNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must fully disclose behavior. It states that comments are added (mutation) and that inline comments require file_path and line_number. However, it does not mention authentication needs, rate limits, or what happens if the PR does not exist. More detail would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose, then explains use cases followed by parameter details. It is concise with no wasted sentences, though the parameter list could be more compact (e.g., bullet points). Overall, it is well-structured and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters and no annotations, the description covers purpose, parameters, and return value. It mentions default behavior for workspace and repository. It lacks error handling or prerequisites but is complete for basic use. Output schema exists, so return description is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains all 6 parameters, including defaults for repository and workspace and the optional nature of file_path and line_number. Since the input schema has 0% description coverage, this adds significant value. It does not specify types but provides enough context for usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool adds a comment to a pull request, distinguishing between general comments and inline code comments. It uses a specific verb ('Add') and resource ('comment to a pull request'), and among siblings, it is distinct from tools like 'approve_pull_request' or 'request_changes'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells when to use the tool (adding feedback or discussion) and explains inline comment usage. However, it does not explicitly mention when not to use it or name alternative tools for related actions (e.g., requesting changes). This is clear but lacks exclusions.

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

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