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).

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.

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.

A comprehensive guide for rapid incident response for Palantir Foundry systems. This runbook provides structured steps for triage, severity classification (P1-P4), and detailed playbooks for common issues like authentication failures, rate limiting, and build pipeline errors. It guides users through investigation, mitigation, and postmortem documentation to minimize downtime and ensure quick recovery.

A structured guide for setting up a robust local development environment for Palantir Foundry data pipelines. This workflow enables users to run Python transforms and unit tests using PySpark against sample data, and mock the Foundry API client, ensuring fast, isolated iteration cycles before deploying code to the official Foundry environment. Ideal for data engineers and developers building complex ETL logic.

This guide provides comprehensive best practices for configuring Palantir Foundry integrations across development, staging, and production environments. It details how to manage environment-specific credentials, hostnames, and scope policies using structured Python code and platform-specific deployment manifests (Docker Compose, Kubernetes, gcloud). Use this skill when implementing resilient, multi-tier SaaS deployments that require strict credential and configuration separation.

This guide provides a comprehensive reference architecture for building production-ready, enterprise-grade applications on Palantir Foundry. It covers the entire data lifecycle, detailing best practices for the standard data pipeline (Raw > Clean > Model), Ontology design, external API integration patterns, and robust multi-layered security models. Use it when designing, planning, or optimizing complex data infrastructure within Foundry.

This comprehensive guide details the process of implementing a secure and robust system for handling Palantir Foundry webhook events. It covers key steps including API-based webhook registration, mandatory signature verification with replay protection, sophisticated event routing for various object lifecycles (create, update, delete), and ensuring idempotent processing using caching mechanisms like Redis. Use this when external microservices must react reliably and immediately to changes within the Foundry Ontology or data assets.

A comprehensive, pre-deployment, defense-in-depth security audit tool for Solidity smart contracts built with Foundry. It combines static analysis (Slither, Aderyn), symbolic execution (Mythril), property-based fuzz testing, and key hygiene checks to proactively detect critical vulnerabilities like reentrancy, access control flaws, and arithmetic bugs before deployment to any EVM chain.