Skill UI

Detects prompt injection hidden in legal documents (pleadings, skeletons, evidence) before AI reads them. Scans PDF, Word, HTML, email attachments for invisible text, Unicode smuggling, and AI-directed instructions. Fails closed with optional hook integration.

Manages Stellar Anchor protocol compliance including SEP-10 authentication, SEP-24 interactive deposits and withdrawals, KYC lifecycle, and generates SQL, JSON, and CSV registers for auditable integration tracking.

Provides an auditable framework for conditional asset locking, timelock boundary verifications, and multi-signature release triggers on Stellar, with standardized data models and verification schemas for integration into CI pipelines.

A browser runtime skill that provides isolated WPE WebKit sessions, native input, screenshots, and ordered JSONL automation. Supports docker-based container lifecycle, deterministic testing, and GitHub Actions verification. Useful for reproducible browser checks and self-hosted runtime integration.

Inventory and govern a project's test assets. Connect requirements, business rules, risks, bugs, and cross-boundary contracts to stable TEST-IDs and executable evidence in the repository's existing test registry or TESTS.md. Use for test inventory, test gap analysis, unit/integration/contract/E2E/smoke classification, bug-to-test regression protection, consumer/provider contract testing, test-necessity review, and pre-delivery evidence review.

This skill helps design and review API contract tests between providers and consumers. It focuses on verifying wire-level behavior during schema changes, compatibility regressions, and client integration failures. By using local fixtures and existing tools, it ensures type assertions alone are not validation. It classifies changes as breaking or compatible, builds test matrices for various scenarios, and verifies boundaries without provisioning new services.

Creates disposable private webhook, email, and DNS inboxes via MCP so agents can wait for asynchronous callbacks, inspect received payloads, validate integration test events, and clean up safely.

This skill covers Quarkus-specific testing features including zero-config containers for databases like PostgreSQL and Kafka. It explains how to use annotations like @QuarkusTest, @QuarkusIntegrationTest, and @InjectMock for unit and integration testing. It also details test resources, profiles, continuous testing, and running tests with Maven. Ideal for developers writing or fixing tests in Quarkus projects.

Enables AI agents to discover, inspect, and run multi-step actions across user-connected apps via the Aident MCP server, with connection checks, cost preflight, approvals, and audit logging.

Create and manage monitoring alert rules for systems like Prometheus, MySQL, and Linux. Prefer importing validated integration templates before writing custom rules. Supports bulk imports or single metric alerts. Helps configure CPU, memory, and database alerts efficiently within Nightingale.

Guides creation of Nightingale (N9E) monitoring dashboards: prefer importing validated integration templates for Linux, MySQL, Redis, Kafka and more, or build custom panels with PromQL only.