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Get Repository

bitbucket_get_repository
Read-only

Retrieve repository details including clone URLs and configuration from Bitbucket Data Center by specifying project key and repository slug.

Instructions

Get details of a specific repository including clone URLs and configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_keyYesThe project key (e.g. 'PROJ')
repository_slugYesThe repository slug

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds value by specifying the type of details returned ('clone URLs and configuration'), which goes beyond annotations. However, it doesn't disclose additional behavioral traits like authentication needs, rate limits, or error conditions. With annotations covering safety, this earns a baseline score for adding some context.

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 ('Get details of a specific repository') and adds specific value ('including clone URLs and configuration'). There is no wasted text, and it's appropriately sized for a simple read tool, making it highly concise and well-structured.

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's low complexity (a simple read operation), high schema coverage (100%), presence of annotations (readOnlyHint), and an output schema (implied by context signals), the description is reasonably complete. It specifies what details are returned, which complements the structured data. However, it could slightly improve by mentioning the output schema's role or error handling, but gaps are minor.

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%, with clear descriptions for both parameters ('project_key' and 'repository_slug'). The description doesn't add any parameter-specific information beyond what the schema provides, such as format examples or constraints. Given high schema coverage, the baseline score of 3 is appropriate as the schema carries the full burden.

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 verb 'Get' and resource 'details of a specific repository', specifying it includes 'clone URLs and configuration'. It distinguishes from siblings like 'bitbucket_get_repositories' (plural) by focusing on a single repository, though it doesn't explicitly name alternatives. This makes the purpose clear but lacks explicit sibling differentiation.

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

Usage Guidelines3/5

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

The description implies usage when needing repository details like clone URLs and configuration, but doesn't explicitly state when to use this vs. alternatives like 'bitbucket_get_project' or 'bitbucket_get_repositories'. It provides some context by specifying 'specific repository', but lacks clear exclusions or named alternatives, leaving usage somewhat implied rather than explicit.

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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