Append context-aware next-step suggestions after every agent response. Generates actionable follow-ups, surfaces unfinished tasks from memory, and includes at least one creative lateral suggestion. Self-learns user preferences for count, categories, and format. Use when: (1) any response is generated and nextsteps is active, (2) user says /nextsteps, "next steps", "what should I do", "suggestions", "what now", (3) user wants to customize suggestion count, categories, or format, (4) user says "disable next steps" or "enable next steps".

Prisma ORM patterns — schema design, migrations, type-safe queries, relations, transactions, connection pooling, error handling, testing, raw SQL safety, and performance. Use when building or reviewing apps with Prisma, when setting up a new database with Prisma, when writing tests for Prisma-backed code, or when debugging query performance.

Apply SOLID principles, detect design anti-patterns, and evaluate architectural tradeoffs for code reviews, design decisions, and refactoring. Use when reviewing code for maintainability issues, evaluating architecture decisions, identifying code smells and technical debt, or refactoring modules with coupling or testability problems.

Execute a strict Red-Green-Refactor TDD cycle for a single requirement at a time, in any language or framework. Use when the user provides a business rule, acceptance criterion, or feature requirement and wants a failing test written first, followed by minimum implementation, then a clean refactor. Works for unit tests, integration tests, UI component tests, and API tests across stacks including TypeScript, JavaScript, React, .NET (C#/xUnit/NUnit), Python, Java, and others. Triggered by phrases like "write a test first", "TDD", "red-green-refactor", "behavioral test", "test-driven", "failing test first", or "write the test before the code".

Extract actionable insights and valuable artifacts from web posts, articles, and technical documentation. Use when summarizing content, extracting key ideas from URLs/articles, preserving code snippets and diagrams, or creating visual summaries. Triggers on requests like "summarize this post", "extract insights from", "distill this article", "what are the key takeaways", or when a URL is shared for analysis.

Use when conducting a security audit, security review, vulnerability assessment, vulnerability check, or secure coding review on Hanami 2.x applications — validate params via the Params DSL in every Action, verify CSRF protection is enabled in config/app.rb, audit authentication checks via explicit `before :authenticate!`, check authorization with role/permission checks, never log passwords/tokens/secrets, use ROM query interface to prevent SQL injection (no string interpolation in `where("...")`), never use `raw` on user input in templates, store secrets in settings not hardcoded, and return generic error messages for auth failures. Validates parameter handling, CSRF, auth integration, XSS, session configuration, and hardening posture.

Configures and runs async Python tests with pytest-asyncio: installs the plugin, selects asyncio_mode (auto vs strict), scopes event loops (function/class/module/session), writes async fixtures with @pytest_asyncio.fixture, mocks coroutines with AsyncMock, and tests FastAPI (httpx.AsyncClient + ASGITransport) and aiohttp (aiohttp_client fixture) applications. Use when a Python project contains async def test_ functions, FastAPI/aiohttp endpoints, or any asyncio-based code that needs pytest integration. Do NOT use for general pytest fixture design, parametrize patterns, or conftest.py structure without an asyncio-specific problem (event-loop scoping, mode config, AsyncMock, ASGI client): use python-unit-tests for those.

ASP.NET Core project structure — Clean Architecture layers, minimal APIs vs controllers, IServiceCollection extensions, IOptions pattern, EF Core DbContext configuration, and proper DTO separation. Apply proactively when building any .NET API, even when the user does not ask for structure guidance.

Expert guidance for configuring and deploying the OpenTelemetry Collector. Use when setting up a Collector pipeline, configuring receivers, exporters, or processors, deploying a Collector to Kubernetes or Docker, or forwarding telemetry to Dash0. Triggers on requests involving collector, pipeline, OTLP receiver, exporter, or Dash0 collector setup.

Configures trace spans, defines custom metrics, sets up log exporters, and optimizes sampling strategies for OpenTelemetry instrumentation. Use when instrumenting applications with traces, metrics, or logs. Triggers on requests for observability, telemetry, tracing, metrics collection, logging integration, or OTel setup.

OpenTelemetry Transformation Language (OTTL) expert. Use when writing or debugging OTTL expressions for any OpenTelemetry Collector component that supports OTTL (processors, connectors, receivers, exporters). Triggers on tasks involving telemetry transformation, filtering, attribute manipulation, data redaction, sampling policies, routing, or Collector configuration. Covers syntax, contexts, functions, error handling, and performance.

Use when the user asks to run E2E tests, verify a web page, generate tests for an app, prove destructive actions are blocked, check if a UI element is visible, fill out a form, or drive a browser with natural language. Returns per-step results with safety classifications, policy decisions, DOM diffs, structured page context, and a signed audit trail.

Estimates implementation time for web development tasks (frontend and/or backend) by analyzing the existing codebase and calibrating for an AI coding agent as executor — not a human developer. Use when the user asks about effort, sizing, or feasibility: 'how long', 'how much work', 'estimate this', 'what is the effort', 'breakdown this task', 'can we do this in X days', 'is this a big task', 'how complex is', 'what's involved in', 'fits in the sprint', 'rough sizing', 't-shirt size', 'story points'. Also use when the user describes a feature and implicitly wants to know scope — e.g. 'we need to add X to the app', 'thinking about building Y', 'is this feasible by Friday'. Supports batch estimation from any structured source (BMAD output, spec folders, PRDs, backlogs, task lists) — use when the user mentions 'estimate the stories', 'estimate the epic', 'scan the backlog', 'estimate all tasks', 'estimate the specs', or points to a folder of task/story/spec files.

Use this skill to refactor, design, or review application architecture. Trigger it when discussing clean architecture, separating business logic from UI, or cross-platform/WASM development. This skill enforces the 'Headless Core & Passive View' pattern, it proactively refactors logic out of the UI, creates platform-agnostic Core interfaces, and ensures the View is a 'Humble Object' that only reflects state.

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