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clikader

bitbucket-python-mcp

by clikader

search_repositories

Search for repositories in a BitBucket workspace by name or other criteria. Returns a list of matching repositories.

Instructions

Search for repositories in a BitBucket workspace.

Use this tool to find repositories by name or other criteria. Searches within the specified workspace and returns matching repositories.

Args: query: Search query to filter repositories by name. If not provided, lists all repositories. workspace: Workspace slug. If not provided, uses the default workspace.

Returns: JSON list of matching repositories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
workspaceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description bears full responsibility. It states it returns a JSON list but does not mention whether the operation is read-only, any authentication requirements, rate limits, pagination, or error states. For a search tool, minimal behavioral context is provided.

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?

Description is reasonably concise with clear sections (Args, Returns). However, it could be slightly more terse without losing clarity. The structure aids readability.

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

Completeness3/5

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

Given low complexity (2 optional parameters, no enums) and the presence of an output schema, the description covers purpose and parameters adequately but lacks behavioral context (read-only assumptions, pagination, etc.). It meets minimum viability but has gaps.

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?

Schema description coverage is 0%, but the description adds meaningful context for both parameters: 'query' is a filter by name, 'workspace' defaults to the default workspace. This compensates for the schema's lack of descriptions.

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?

Description clearly states action (search), resource (repositories), and scope (in a BitBucket workspace). It also clarifies behavior when query is not provided (lists all repositories), making it distinct from siblings like list_repositories or get_repository.

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?

Explicitly says 'Use this tool to find repositories by name or other criteria.' While it doesn't list when not to use it, the context of sibling tools (list_repositories, get_repository) provides implicit guidance. Could be improved with direct 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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