danger/danger-js

Features

• CI Pipeline Integrations - Executes automated code review checks by adding a CLI command to the continuous integration build pipeline.
• Automated Code Review - Provides an automated system to analyze source code and enforce team conventions and etiquette via CI pipelines.
• VCS Metadata Abstraction - Fetches pull request and commit data by abstracting different version control APIs into a common interface.
• Quality Governance Systems - Enforces organizational quality standards by detecting debug statements and missing type annotations before code is merged.
• Commit Message Validation - Validates that commit messages adhere to specific formats and alerts users when standards are not met.
• Dependency Tracking - Tracks and validates dependency changes to maintain project health and keep packages updated.
• GitLab Integrations - TypeTalk connects to GitLab instances via API or OAuth tokens to automate code review conventions on open pull requests.
• Bitbucket Sync Filters - Connects to BitBucket Server instances to enforce code review conventions and provide automated feedback.
• Pull Request Review Interfaces - Reports failures and warnings directly into pull requests using inline comments and formatted tables.
• Policy Enforcement Rules - Automates checks for missing issue references, debug logs, and insufficient test coverage against team policies.
• Pull Request Linters - Scans code changes for problematic patterns and style violations specifically during the pull request review process.
• Version Control Provider Integrations - Establishes authenticated connections to BitBucket Cloud to automate review checks and post comments.
• CI Review Automations - Executes as a build step within a continuous integration pipeline to enforce team conventions.
• Pull Request Automation Tools - Automates repetitive pull request tasks such as linking Jira issues and validating PR descriptions.
• Code Review Bots - Functions as an automated agent that verifies commit messages and ensures pull requests meet project standards.
• Git Provider Connections - Authenticates requests to Git hosting providers using environment variables to access private repository data.
• Metadata Extraction - Retrieves pull request details, commit history, and reviewer activities from VCS providers for analysis.
• Automated Code Review Tools - Automatically inspects code changes and provides feedback on team conventions and etiquette within pull requests.
• Git - Abstracts GitHub, GitLab, and BitBucket APIs to retrieve pull request metadata and post automated comments.
• CI Pipeline Summaries - Posts test results, linting errors, and code coverage summaries as automated comments directly in the version control interface.
• Code Task Tracking - Lists all TODO or FIXME markers added or removed within a pull request to ensure resolution.
• Analysis File Filters - Groups specific files from a pull request to target analysis rules to a relevant subset.
• Analysis Report Aggregators - Parses structured JSON output from external linters and test runners to generate unified feedback summaries.
• Change Prohibitions - Flags specific code changes that should be avoided and notifies the developer.
• Source-to-Source Analysis - Analyzes original source code instead of compiled output by integrating with TypeScript and Babel.
• Custom Lint Rule Plugins - Packages common code review rules into shareable modules that other teams can install.
• Markdown Comment Rendering - Transforms analyzed metadata and tool results into formatted markdown tables and comments for VCS interfaces.
• Dependency Auditing - Scans lockfiles and manifests during review to detect outdated, duplicate, or insecure dependencies.
• Version Evolution Tracking - Tracks the evolution of project dependencies to ensure consumers are aware of version shifts.
• Change Set Size Limits - Checks the number of changed files against a maximum limit to keep reviews manageable.
• Metadata Validations - Verifies that pull requests include assignees and follow specific title patterns.
• Team Norm Validations - Executes common validations and utility checks on pull requests to ensure they adhere to team norms.
• PR Change Auditing - Scans modified files and commit messages to ensure required updates like changelogs are included.
• Git Hooks - Executes code review conventions via git-hooks to provide instant feedback before pushing code.
• Issue Tracking Integrations - Integrates external issue tracking systems directly into the development workflow by analyzing commit and PR metadata.
• Linter Result Aggregators - Analyzes ESLint output to integrate linting errors into a review aggregator for automated feedback.
• Polyglot Rule Runners - Uses a processing engine to execute review rules for any programming language.
• PR Metadata Validation - Verifies pull request bodies and labels to ensure team contribution norms are followed.
• PR Netiquette Enforcement - Inspects the pull request body for required content such as issue references or minimum character counts.
• VCS-Issue Linking - Provides bidirectional linking between Jira project issues and version control entities like pull requests.
• Dependency Addition Alerts - Notifies reviewers when new dependencies are added to the project configuration.
• Lint Result Commenting - Converts static analysis and linting reports into actionable inline comments within the pull request.
• Self-Hosted Git Services - Supports connectivity to self-hosted enterprise Git instances via custom API base URLs.
• Webhook Event Receivers - Receives and processes webhook events from external hosting platforms to trigger real-time automation tasks.
• Linter Rule Extensions - Imports shared community rules or custom logic to standardize checks across multiple projects.
• Runtime Configuration Transpilers - Uses TypeScript or Babel at runtime to execute code review rules written in transpiled languages.
• Anti-Pattern Detection - Scans code changes for problematic patterns or structural flaws and triggers warnings.
• Standardized Changelog Structures - Validates that changelog modifications follow a specific structural format including version lines and headers.
• Plugin-Based Rule Engines - Packages custom review conventions into shareable modules that can be imported across multiple projects.
• Annotation Scanning - Scans the codebase for FIXME and TODO markers and triggers failures if they are detected.
• Prohibited Pattern Scanners - Checks source code for suspicious words or patterns defined in a text file and alerts the user.
• PR Documentation Standards - Checks pull requests against predefined digital standards to ensure consistency and adherence to team norms.
• Annotation Verifiers - Checks that new JavaScript files include type annotations to maintain static type safety and codebase consistency.
• Pull Request - Analyzes TSLint JSON output files to automatically post warnings and failures to pull requests.
• Code Coverage Analysis - Posts a comment on a pull request displaying code coverage metrics generated during continuous integration.
• Debugger Statement Detection - Performs static analysis to detect console logging statements and prevent debug code from being merged.
• CI Log Parsing - Parses logs or JSON output from external CI processes to post failure details into the review.

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