Explorar skills

TypeScript development — use when the user works with TypeScript, type system patterns, generics, Zod, tsconfig, NestJS, branded types, or runtime validation. Covers type system mastery, framework integration, architecture patterns, security, and testing strategies. NOT for Python development (use python-development), NOT for React component patterns or hooks (use react-development), NOT for Next.

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

GitHub and Git workflow helpers, Issues and Projects v2 management via gh CLI; triggers on 'github', 'create issue', 'list issues', 'github project', 'project board', 'sync tasks', 'create pr', 'pr checks', 'retrigger tests', 'bump version', 'push'.

Use when the user has a proposal, position, or design and wants it adversarially pressure-tested before committing.

Create and evolve production-ready skills with reusable scripts, references, and validation. Use for new skill creation, skill upgrades, and enforcing consistent metadata and structure.

Systematically test authorized targets for SQL, XSS, SSTI, XXE, command, and request-smuggling injection classes.

Use when the user wants a thorough audit of the existing test suite — aggressively cutting tests that exist just to exist, rewriting weak ones to actually catch the bugs they should, identifying production code that is uncovered or thinly covered, and adding tests where coverage would catch real defects. Trigger on "audit tests", "find test bloat", "tests don't catch anything", or similar requests

Aggregate SAST, SCA, DAST, secrets, API, frontend, and backend security checks into one report.

Prioritize vulnerability remediation using KEV-style exploitation context plus asset criticality. Use for CVE triage, patch order decisions, and remediation reporting.

Generate a complete CRUD REST API with validation, error handling, auth middleware, tests, and OpenAPI docs. Use when asked to create API endpoints, REST resources, or backend CRUD operations.

Test and evaluate AI agents and LLM outputs using code-first evaluation framework with strong typing. Use when the user wants to: (1) Create evaluation datasets with test cases for AI agents, (2) Define evaluators (deterministic, LLM-as-Judge, custom, or span-based), (3) Run evaluations and generate reports, (4) Compare model performance across experiments, (5) Integrate evaluations with Pydantic

Define legal scope, rules of engagement, and authorization artifacts for downstream pentest execution.