Skill UI

A comprehensive deep dive guide for migrating translation memory (TM) and localization content from competing Translation Management Systems (TMS) like Crowdin, Phrase, or POEditor into Lokalise. This process involves exporting data from the source platform, transforming key variables and file structures to match Lokalise conventions, and finally performing a bulk API upload to establish a new, centralized localization repository. Perfect for re-platforming or migrating existing translation pipelines.

Automates Mistral AI workflows through the Composio MCP integration, letting teams upload files for fine-tuning, batch jobs, OCR, manage RAG document libraries, monitor tuning jobs, and retrieve or catalog data for cross-app pipelines.

This skill provides deep integration with Google NotebookLM, enabling users to query uploaded documentation using Gemini. It ensures source-grounded, citation-backed answers, significantly reducing hallucinations. Features include managing the notebook library (add, list, search), handling authentication, and implementing a structured follow-up mechanism for comprehensive research.

Automate OneDrive file management tasks through Composio's Rube MCP toolkit, handling uploads, downloads, search, sharing links, permissions, and folder navigation via documented tool sequences once the MCP connection is active.

Automate PandaDoc workflows from Claude Code so you can create documents from uploads or URLs, manage contacts and folders, configure templates and webhooks, and track document status without leaving the terminal.

Automate Replicate AI workflows via the Composio MCP integration to inspect model schemas, run predictions (sync or async), upload input files, list versions, and manage prediction history and related assets.

This comprehensive workflow guides developers through building a production-ready, full-stack web application entirely within the Replit environment. It covers setting up the entire architecture, including Express/Flask backend logic, robust PostgreSQL database integration for persistent data, implementing secure user authentication using Replit Auth, and managing file uploads via Object Storage. It is the definitive guide for launching a complex, scalable SaaS project from scratch.

Comprehensive guide to managing data securely in Replit applications. This skill covers three core storage systems: PostgreSQL for structured data and complex queries; Replit KV Database for caching and session management; and Object Storage for file uploads and blobs. Learn best practices including parameterized queries, TTL implementation, and secure data access patterns.

A comprehensive guide to integrating Sentry into continuous integration and continuous deployment (CI/CD) pipelines (e.g., GitHub Actions, GitLab CI, CircleCI). This skill automates complex tasks such as creating releases, uploading source maps for readable stack traces, associating commits, and tracking deployment environments, ensuring rapid and accurate debugging of production errors.

Integrate Sentry into your CI/CD pipeline to achieve end-to-end release tracking. This skill guides you through using the Sentry CLI and SDK to record deployments, associate commits, upload source maps, and monitor crucial release health metrics. Key functions include detecting regressions, calculating crash-free session rates, and tracking user adoption curves for every deployed version.

A comprehensive checklist for ensuring Sentry is properly configured before any production deployment. This guide covers best practices for managing environment variables (DSN), implementing release tracking, optimizing error and trace sample rates, uploading source maps, and filtering noise. Essential for go-live readiness and auditing existing monitoring setups.

This guide details how to use the Sentry CLI to manage the full application release lifecycle. Users can create versioned releases (using Semver or SHA), upload source maps to deminify stack traces, and associate specific git commits. This ensures that every error is accurately linked to the exact code version and deployment that caused it, significantly improving debugging and observability in CI/CD pipelines.