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Import Repository

import_repository

Import and analyze a GitHub repository for testing. Creates a default project if none specified.

Input Schema

NameRequiredDescriptionDefault
branchNoBranch to analyze (defaults to main)main
contextNoExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
repo_urlYesGitHub repository URL (e.g., https://github.com/user/repo)
project_idNoExisting project ID to associate repository with
project_nameNoName for new project (required if create_project is true)
create_projectNoCreate a new project for this repository
training_consentNoWhether repository code can be used for training (default: opt_out)opt_out

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare a non-read-only, open-world, non-destructive operation; the description adds the useful disclosure that a default project is created when none is specified and that analysis is performed. It does not say how long analysis takes, whether it is synchronous, what permissions the GitHub URL requires, or what is produced.

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?

Two tightly written sentences with the core action front-loaded. Minimal but no wasted text; slightly more could be said without becoming bloated.

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?

With no output schema, the description should explain what the agent gets back (repository ID, analysis status, polling need) and how long the import takes. None of that is present, though the project-creation behavior is covered.

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 coverage is 100%, so the schema already documents all seven parameters including defaults and the enum. The description adds no parameter detail beyond the project-creation implication, which is baseline-appropriate.

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?

States a specific verb ('import and analyze') and resource ('a GitHub repository') with a clear testing scope. It implicitly distinguishes itself from read-only siblings like get_repository and list_repositories, but never names them, so the boundary with refresh_repository remains unclear.

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 indication of when to call this versus refresh_repository, get_repository, or list_repositories. The only guidance offered is about default project creation, which is a side effect, not a usage condition.

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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