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Lexmata

Bitbucket Cloud MCP Server

by Lexmata

update_pull_request

Modify pull request details including title, description, or target branch in Bitbucket Cloud repositories to keep code reviews current.

Instructions

Update a pull request title, description, or destination branch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYesThe workspace slug
repo_slugYesThe repository slug
pr_idYesThe pull request ID
titleNoNew title
descriptionNoNew description
destination_branchNoNew destination branch

Implementation Reference

  • Core implementation of updating a pull request by constructing the request body with optional title, description, or destination branch changes and sending a PUT request to the Bitbucket API.
    async update(
      workspace: string,
      repo_slug: string,
      pr_id: number,
      updates: { title?: string; description?: string; destination_branch?: string }
    ): Promise<BitbucketPullRequest> {
      const body: Record<string, unknown> = {};
    
      if (updates.title) body.title = updates.title;
      if (updates.description) body.description = updates.description;
      if (updates.destination_branch) {
        body.destination = { branch: { name: updates.destination_branch } };
      }
    
      return this.client.put<BitbucketPullRequest>(
        `/repositories/${workspace}/${repo_slug}/pullrequests/${pr_id}`,
        body
      );
    }
  • ToolHandler.handleTool case for 'update_pull_request' that validates inputs with Zod schema and calls PullRequestsAPI.update method.
    case 'update_pull_request': {
      const params = toolSchemas.update_pull_request.parse(args);
      const { workspace, repo_slug, pr_id, ...updates } = params;
      return this.prs.update(workspace, repo_slug, pr_id, updates);
    }
  • Zod schema defining input parameters for the update_pull_request tool.
    update_pull_request: z.object({
      workspace: z.string().describe('The workspace slug'),
      repo_slug: z.string().describe('The repository slug'),
      pr_id: z.number().describe('The pull request ID'),
      title: z.string().optional().describe('New title'),
      description: z.string().optional().describe('New description'),
      destination_branch: z.string().optional().describe('New destination branch'),
    }),
  • MCP tool registration including name, description, and input schema for update_pull_request.
    {
      name: 'update_pull_request',
      description: 'Update a pull request title, description, or destination branch.',
      inputSchema: {
        type: 'object' as const,
        properties: {
          workspace: { type: 'string', description: 'The workspace slug' },
          repo_slug: { type: 'string', description: 'The repository slug' },
          pr_id: { type: 'number', description: 'The pull request ID' },
          title: { type: 'string', description: 'New title' },
          description: { type: 'string', description: 'New description' },
          destination_branch: { type: 'string', description: 'New destination branch' },
        },
        required: ['workspace', 'repo_slug', 'pr_id'],
      },
    },
Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions what can be updated but doesn't disclose permissions needed, whether updates are reversible, rate limits, error conditions, or what happens to unspecified fields. For a mutation tool, this lack of transparency is a significant gap.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states the tool's function and scope, making it easy to parse and understand quickly.

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

Completeness2/5

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

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error handling, or return values, leaving gaps that could hinder an AI agent's ability to use the tool correctly in complex scenarios.

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

Parameters3/5

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

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value by listing updatable fields (title, description, destination branch), which aligns with schema properties but doesn't provide additional context like format constraints or examples beyond what the schema already specifies.

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

Purpose4/5

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

The description clearly states the action ('Update') and resource ('pull request'), specifying what fields can be modified (title, description, destination branch). It distinguishes from siblings like 'create_pull_request' or 'merge_pull_request' by focusing on updates, but doesn't explicitly contrast with 'update_issue' which has similar semantics for a different resource.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives is provided. It doesn't mention prerequisites (e.g., needing an existing pull request), exclusions (e.g., cannot update merged PRs), or comparisons to siblings like 'update_issue' for issue modifications. The description assumes context without explicit usage instructions.

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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