Explorar skills

Set up visual regression testing with baseline screenshots across breakpoints. Auto-detects frontend framework (Next.js, React, Vue, Angular, Flutter, Storybook), configures Playwright screenshot comparison, BackstopJS, or Flutter golden tests, captures every page at mobile/tablet/desktop/wide viewports plus interactive states (hover, focus, error, empty, loading), stabilizes dynamic content to pr

Runs a 5-phase enterprise compliance and security hardening pipeline: regulatory review, GDPR audit, SOC 2 evaluation, dependency scan, and penetration test with cross-framework control mapping. Triggers on: \"full compliance suite\", \"enterprise compliance\", \"compliance suite\", \"SOC 2 and GDPR\", \"regulatory compliance\", \"multi-framework compliance\", \"compliance for regulated industry\"

Use when adding or reviewing data quality tests for dbt models in warehouse-backed analytics projects. Covers dbt generic tests, singular tests (assert_*.sql), accepted-values macros, dbt_utils patterns, cross-system consistency tests, and warehouse-oriented validation. Use when writing data tests, creating assert_*.sql files, testing business logic, or validating referential integrity.

Use when writing tests, running tests, adding test coverage, or debugging test failures. Unit and component testing with Vitest and React Testing Library.

Emergency bug fix pipeline — diagnose, fix, test, commit, push, and PR in 2 iterations max. Speed over perfection.

Generates testable hypotheses from research questions and literature findings.

Audit game analytics and telemetry implementation -- event tracking completeness, FTUE and monetization funnel coverage, retention metric infrastructure, A/B testing framework, heatmap data collection, churn prediction signals, and LTV modeling support. Covers Firebase Analytics, Unity Analytics, GameAnalytics, Amplitude, Mixpanel, Adjust, and custom pipelines. Use when verifying event tracking co

Build, test, inspect, install, and deploy MCP servers with FastMCP in Python. Use when creating a new MCP server, wrapping an API or database as MCP tools, exposing resources or prompts, or preparing a FastMCP server for Claude Code, Cursor, or HTTP deployment.

Use when encountering any bug, test failure, unexpected result, or failed replication - before proposing fixes or explanations

Weekly / monthly closed-loop reporter for Peec AI visibility growth. Measures what moved (visibility per prompt, cluster, zone) against what was invested (content published, pitches sent, forum answers), detects winning patterns, and outputs a ranked next-actions list — not a dashboard. Closes the feedback loop for the growth agent. Use weekly for active projects or monthly for maintenance-mode.

Workflow for writing tests against requirements — verifying that a feature, endpoint, or function behaves correctly according to its specification, not according to its current implementation. Reads the spec/requirement and the surface being tested (signatures, contracts, observable behavior); deliberately avoids mirroring implementation logic into the tests. Suitable for adding coverage after the

Build a production-ready data API from scratch: scaffold REST endpoints with models and validation, generate integration tests that verify every route, then load test for scalability. Use when you need an API backend, data service, CRUD layer, or microservice with verified correctness and performance.