Skill UI

Master advanced testing strategies for smart contracts using industry-leading frameworks like Hardhat and Foundry. This skill covers unit testing, integration testing, gas optimization analysis, fuzzing for edge cases, and simulating real-world mainnet interactions via forking. Ideal for ensuring the security and reliability of decentralized applications (DApps).

Guides use of the Adaptyv Bio Foundry API and Python SDK to design protein experiments, submit sequences, automate workflows, and fetch BLI/SPR or thermostability assay results via authenticated requests for lab-ready studies.

Use the Adaptyv Bio Foundry API and Python SDK to design, submit, and retrieve protein experiments, including binding, thermostability, and expression assays via programmatic workflows.

This skill creates and synchronizes prompt-based AI agents directly into Azure AI Foundry using the Agent Service REST API. By defining agents in a local JSON manifest, the skill registers them server-side, making them instantly available for evaluation and invocation within the Foundry ecosystem. It is essential for deploying, updating, or managing AI agents at scale within the Azure cloud environment.

Comprehensive guide for setting up Continuous Integration/Continuous Deployment (CI/CD) pipelines for Palantir Foundry integrations using GitHub Actions. This workflow covers running PySpark unit tests, performing SDK integration tests with mocked APIs, and implementing custom linting rules to enforce Foundry-specific best practices. Use this when ensuring code quality and validating complex business logic changes in an automated build process.

This comprehensive guide provides quick, actionable solutions for the top common Palantir Foundry API and data transformation errors. It covers critical issues such as 401 Unauthorized, 403 Forbidden, ObjectTypeNotFound, and OutOfMemoryError. By offering specific code examples and best practices, this resource helps users efficiently debug and resolve complex issues in their Foundry pipelines.

This guide provides a comprehensive workflow for building robust ETL data pipelines within Palantir Foundry. It teaches how to utilize Python transforms, including the @transform_df decorator, for dataset-to-dataset processing. Key topics covered include multi-input joins, implementing incremental updates for efficiency, low-level file I/O, and configuring Spark resources for heavy computations. Essential for data engineers working with complex data modeling in Foundry.

This workflow provides comprehensive SDK access to the Palantir Foundry Ontology. It enables users to query, filter, link, and mutate Ontology objects, and execute defined business actions. Use this skill for building sophisticated, data-driven applications that require deep interaction with structured enterprise data, including cross-object navigation and advanced server-side aggregation.

This guide provides comprehensive technical instructions for optimizing Palantir Foundry costs. Learn to use incremental transforms to drastically reduce compute rebuilds, right-size Spark profiles based on data volume, and migrate from expensive API polling to efficient, event-driven webhooks, ensuring both cost efficiency and system stability.

Implement robust data governance and security measures within Palantir Foundry. This skill guides users through PII redaction, applying data markings (e.g., CONFIDENTIAL, RESTRICTED), ensuring GDPR/CCPA compliance, and establishing automated data retention policies. It provides methods for column-level security and auditable deletion workflows for sensitive information.

This comprehensive bundle collects all necessary diagnostic artifacts for troubleshooting Palantir Foundry issues. It gathers SDK versions, environment variables (with secrets automatically redacted), API connectivity status, and recent application error logs. This structured output is essential for creating detailed, actionable support tickets when reporting persistent platform malfunctions.

This skill provides a comprehensive guide for deploying Palantir Foundry integrated applications to major cloud platforms, such as GCP Cloud Run, AWS Lambda, and Docker. It covers best practices including containerization using Docker, implementing robust secrets management via cloud secret managers, establishing health check endpoints, and configuring environment-specific scopes. This process ensures applications are production-ready, secure, and highly available.