cursor

Audit and maintain project rules in .cursor/rules/. Use when auditing project rules, checking prefix convention, syncing doc/rules.md, or when the user asks about .cursor/rules or prefix convention.

Use Apify Actors for scraping/data acquisition pipelines. Use when data collection from websites is required and needs repeatable runs.

Use browser automation MCP (Playwright/Browser/Browser-Use) to validate UI flows, capture screenshots, and reproduce issues. Use when visual verification or web flow testing is needed.

The user's dedicated browser for agents — a real browser signed into their accounts, with live logins and a persistent profile. Use it for any task that touches a website or browser (open, read, act, fill, sign in, download, verify). The user installed it precisely so agents default here unprompted — over in-app browser tools, devtools/playwright automation, or headless fetching.

Ensure commands and paths are safe across Windows + WSL + Docker (PowerShell vs bash, path translation, permissions). Use when instructions touch shell, filesystem, Docker, or OS-specific behavior.

Generate Cursor deeplinks (prompt/command/rule and MCP install links) using the repo generator and the project output contract. Use when the user asks for a Cursor deeplink, cursor:// links, cursor.com/link links, or wants to create prompts/commands/rules via deeplinks.

Implement or refactor data import/parsing so it streams files sequentially (memory-safe), validates/coerces types explicitly, skips irreparable records while logging them to an error CSV (full original columns + timestamp/file/line/error), emits rows_ok/rows_skipped/parse_errors metrics, and guarantees idempotent DB writes.

Conduct deep, source-grounded research with freshness checks and citations, then synthesize an actionable answer. Use for time-sensitive, niche, or high-stakes topics; when the user asks to “zweryfikuj”, “zrób research”, or when uncertainty is high.

Apply enhanced verification (CoVe-like review, security/arch/perf checks, targeted web research) for high-risk tasks or uncertainty. Use for security, infra, data loss risk, major refactors, or when facts may be outdated.

Apply frontend/UI design guardrails and the Impeccable anti-pattern checklist (pbakaus/impeccable) when building or reviewing visual UI — landing pages, dashboards, marketing sites, component styling. Use for design critique, polish passes, or before shipping new UI; pairs with vanilla-web/next-stack (implementation) rather than replacing them.

Keep the workspace tidy while the agent works: no orphan scratch docs/scripts, confine temp to .agent-scratch/ or tmp/agent-*, clean before declaring done. Use during implementation, multi-file edits, shell/write batches, or when marking work done — continuous hygiene, not post-hoc /cleanup.

KeePassXC cursor.kdbx — natywny keyring per OS, keepass-db.path bez fallbacków, agent instaluje brakujące narzędzia.

Drive BrowserClaw (BrowserOS agent browser) via MCP: logged-in local Chromium for agents, cockpit/audit/replay, snapshot→act refs, tab ownership. Use when a task needs the web, real logins/cookies, parallel agent tabs, or the user mentions BrowserClaw / agent browser. Prefer over Playwright, Claude-in-Chrome, or the user's daily Chrome unless the user points elsewhere.

Use BrowserOS MCP to automate the user's visible Chromium browser (sessions, cookies, manual CAPTCHA/2FA). Use when anti-bot protection, user intervention, OAuth in existing session, or Klavis Strata app integrations are needed.

Fetch version-specific library and framework documentation via Context7 MCP. Use when implementing against third-party APIs/SDKs where model knowledge may be stale, or when the user says "use context7" / asks for current docs for a named library.

Use GitHub MCP for issue/PR context, diffs, reviews, and automations. Use when the task references PR/issue numbers, review requests, or requires repo metadata beyond local git.

Query dashboards/logs/alerts to support incident analysis and regressions. Use when troubleshooting involves observability, incidents, latency, error rates.

Recall and reuse prior decisions, constraints, and artifacts using MCP memory (e.g., Neo4j). Use when the user references past work (“jak ostatnio”, “kontynuuj”), when resuming a project thread, or when a repeated topic suggests existing decisions.

Use Neo4j memory MCP for creating/updating linked memories (entities, relations), de-duplication (DRY), and retrieval queries for project continuity. Use when saving global learnings or querying graph relationships.

Automate browser flows and capture evidence (screenshots, console/network errors). Use for UI verification, repro steps, and end-to-end smoke tests.

Use Postman MCP to inspect/maintain collections, environments, and API workflows; generate or validate requests and tests. Use when API verification or collections are the source of truth.

Execute Shrimp tasks in order: load state, respect dependencies, implement, verify_task, update status. Use after task-planning-shrimp or when resuming in_progress/pending tasks (/next). Not for same-session-only Plan Mode work.

Execute end-to-end migrations and consolidate docs/scripts (remove dead files, keep canonical runbooks). Use when changing runtime model, reorganizing repo, or doing “repo cleanup”.

Next.js App Router frontend stack workflow: Server Components-first, Prisma server-only (Node runtime), Tailwind + shadcn/ui, TanStack Query, React Hook Form + Zod, and conventions for work under frontend/. Use when implementing or refactoring UI, routes, data fetching, mutations, or forms in this stack.

Produce a reviewable, file-referenced implementation plan that acts as a contract before execution. Use for risky ops, architecture changes, migrations, multi-file edits.

On-demand over-engineering review/audit using the "laziness ladder" (DietrichGebert/ponytail) — the always-on rung is already in USER_RULES.txt STATIC PRINCIPLES; this skill is for deep diff/repo audits and debt tracking. Use when the user asks to review a diff or repo for over-engineering, unnecessary abstractions, unused dependencies, or dead code, or invokes /ponytail_review.

FastAPI + Pydantic v2 backend workflow: implement/modify API endpoints with thin handlers + service layer, add pytest tests, manage idempotent Alembic migrations, and implement streaming ETL/parsers with invalid-row CSV logging. Use this skill when working on Python backend APIs, schema changes, or ingestion/parsing pipelines.

Enforce consistent Python typing (type hints + return types), concise Google-style docstrings, PEP 8/Black formatting, and unit tests when creating or editing Python code. Use when working on .py files, Python APIs, refactors, or bug fixes where maintainability and correctness matter.

Ground answers in the repository by reading relevant files, configs, and code paths. Use when the user asks to modify/debug code, configuration, CI/CD, or wants repo-specific reasoning.

Enforce SOLID design principles during code generation, refactors, and code review (SRP/OCP/LSP/ISP/DIP). Use when changing architecture, introducing new abstractions, reducing coupling, eliminating type-switches, or reviewing PRs for maintainability.

Provide structured outputs (plan/report/checklist/table) optimized for readability and reuse. Use when user requests a plan, report, checklist, template, or when high-risk requires explicit verification steps.

Plan and split work with Shrimp Task Manager MCP when backlog must persist across sessions and tasks have explicit dependencies. Skip for same-session planning (use Plan Mode). Requires shrimp-task-manager MCP + Docker volume.

Perform root-cause analysis for bugs/errors/regressions using logs, repro steps, and hypothesis testing. Use when the user reports “nie działa”, stack traces, failing tests, or regressions.

Build or modify plain HTML/CSS/JavaScript (no framework) using modular ES modules (ESM), SRP, minimal global state, and shippable runnable files with lightweight verification. Use for static pages, small UI widgets, vanilla JS refactors, and quick prototypes without React/Vue/Angular.