
93 results

Implement comprehensive E2E testing patterns using Playwright for web applications.

Parse, clean, validate, and convert various document formats into structured data.

Streamline parallel AI development with a multi-agent Git workflow for dynamic task management.

PostgreSQL/Supabase database specialist for schema design, query optimization, indexing strategies, Alembic migration safety, SQLAlchemy ORM/Core patterns, connection pooling, and migration review. Ensures database changes are safe, performant, and backward-compatible.

Python code review specialist with Pyrefly static analysis, Ruff typing rules (ANN/PYI/NPY), FastAPI patterns, SQLAlchemy async, Pandas/NumPy review, Alembic migrations, and Python testing conventions. Enforces strict type-hint correctness, performance-aware data code, and production-ready API patterns.

Search-first methodology — search before coding discipline, effective search strategies, when to search vs reason, query formulation, result verification, avoiding stale information, cross-referencing, documenting search findings.

Guidance for implementing repeatable workflows using Docker patterns.

Data processing specialist for Pandas/NumPy workflows, ETL pipelines, data validation, performance optimization, database migrations, streaming ingestion, data versioning, and big data integration. Builds production-grade data infrastructure for AI/ML workloads.

Implement API connector patterns for OAuth, webhooks, and rate limiting.

Identify and analyze documentation debt to enhance developer productivity.

Implement TypeScript patterns for type-safe and maintainable code.

Integrate LangChain and LlamaIndex for advanced RAG pipelines and retrieval strategies.

Streamline your MLOps processes with a structured workflow for training, evaluation, and deployment.

Skill authoring workflow for packaging repeatable practices as reusable skills.

Monitor and report the real-time status of multi-agent workflows with ease.

System design specialist for scalability, technical decisions, and component boundaries. Spawns parallel deep sub-agents for repository research and architecture spikes. Emits ADRs and requests AI-Judge validation after integrating research outputs. Uses opus model for deep reasoning.

Build autonomous AI agent workflows with safety and validation mechanisms.

FastAPI architecture patterns including system design, dependency injection, error handling, background tasks, WebSocket, testing, middleware, database integration, and OpenAPI design.

Create self-improving workflows with autonomous loop patterns for continuous feedback and quality checks.

Streamline AWS deployments with various patterns and infrastructure as code.

Comprehensive AWS DevOps practices for modern application deployment.

Data pipeline workflow for ETL, validation, and quality controls.

Develop and debug Chrome extensions using the WXT framework and Manifest V3.

Build and type error specialist who fixes compilation failures incrementally using Pyrefly (Python) and tsc/ESLint/Biome (TypeScript). Keeps diffs minimal, preserves behavior, and restores green CI fast.

Python testing workflow covering Pytest, FastAPI testing, Factory Boy, mocking, integration testing, property-based testing with Hypothesis, coverage, xdist parallelization, and AI-focused regression testing.

Security review methodology covering OWASP Top 10, input validation audit, auth/authorization review, secret management check, dependency CVE scan, threat modeling, and secure code review checklist.

Continuous validation through verification checkpoints, assertion quality, property-based testing, invariant checking, CI/CD validation, and automated feedback loops.

Generate comprehensive technical debt reports by consolidating insights from multiple sub-analyzers.

Documentation and codemap sync specialist. Handles OpenAPI spec regeneration, README/codemap updates, docstring refresh, architecture decision record maintenance, and example synchronization. Lightweight, cost-optimized agent focused on mechanical doc updates with minimal reasoning overhead.

Analyzes dependency debt to identify outdated packages, security risks, and maintenance issues.

Fast and authoritative documentation lookup agent using Context7 MCP.

Manage token budgets for LLM workflows with efficient context allocation and cost estimation.

End-to-end Playwright testing specialist for FastAPI + Next.js + Chrome extension (WXT) full-stack flows. Handles test authoring, flaky test diagnosis, CI integration, test stability, and cross-surface scenario coverage.

Orchestrates multi-agent Git workflows from issue to PR, ensuring clean and validated code delivery.

AI Judge is a gatekeeper agent for structured evaluations of research and implementation outputs.

Implementation planning for complex features. Breaks work into phases, identifies risks and dependencies, emits ADR IDs for architecture decisions, and requests AI-Judge validation passes before implementation begins. Uses opus model for deep reasoning.

Identify and analyze performance debt in your codebase to enhance efficiency.

Identify and report on process debt in your development workflow.

Dead code elimination, modernization, and code quality specialist. Handles Python upgrades, React 19 migration, TypeScript strict mode, dead code removal, dependency deduplication, and pattern modernization while preserving behavior and keeping every change reviewable.

RESTful API design — resource naming, error envelopes, versioning, pagination strategies, rate limiting, idempotency keys, request/response validation with Pydantic/Zod, HATEOAS, OpenAPI generation, API documentation.

ADR process — template, lifecycle (proposed → accepted → deprecated), storage convention, when to create ADRs, referencing ADRs in PRs and plans, ADR maintenance.

Identify and analyze security debt in codebases to enhance security posture.

Test-driven development specialist enforcing RED-GREEN-REFACTOR cycle with 80%+ coverage requirement. Guides Pytest patterns, FastAPI dependency overrides, Factory Boy factories, Hypothesis property tests, xdist parallelization, and TypeScript Vitest/Jest workflows.

Manage context windows effectively for LLMs with techniques like pruning and summarization.

Generate structured reports on codebases for onboarding and auditing.

Manage continuous agent workflows with quality gates and health monitoring.

Deep research methodology — multi-source investigation, web search with Exa, documentation traversal, cross-referencing sources, synthesizing findings, research report structure, evidence grading, conflicting source resolution, citation format.

Create and manage data pipelines for AI workflows using Airflow, Prefect, and Kafka.

Efficient patterns for building and training models in PyTorch.

React 19 and Next.js patterns including component architecture, state management, performance, styling, forms, testing, Chrome extension parity, DX tooling, micro-frontends, UI state machines, and AI chat surface composition.

Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.

Streamline your tasks with specialized workflow guidance for documentation lookup.

Git workflow for branches, commits, merges, and conflict management.

Provides structured workflow guidance for GitHub operations.

Guidance for implementing Hexagonal Architecture in software projects.

Configure and operate Model Context Protocol (MCP) servers for LLM clients.

MLOps practices for retrieval-augmented generation (RAG) systems, including model versioning and A/B testing.

Prompt optimization — compression, few-shot example selection, chain-of-thought alternatives, structured output, system prompt design, versioning and A/B testing, injection defenses, evaluation metrics, cache optimization, distillation patterns.

Comprehensive observability and telemetry solution for production systems.

Python data and backend patterns including Pandas, NumPy, SQLAlchemy 2.0, Alembic, data validation, performance optimization, and OOP composition.

Master the OpenAI API for production with best practices and patterns.

Deep codebase analysis agent. Maps architecture, data flow, coding styles, patterns, dependency graphs, and structural health. Produces a structured report after scanning. Use this to understand any codebase from scratch.

Systematically learns unfamiliar codebases to produce comprehensive learning reports.

Specialist in developing Chrome extensions using the WXT framework with Manifest V3 compliance.

Analyzes architecture debt to identify structural issues in codebases.

Code quality and maintainability reviewer with absorbed quality-nonconformance playbook. Checks for bugs, anti-patterns, performance issues, test coverage gaps, and regressions across Python, TypeScript, and web surfaces. Provides actionable, specific feedback before PR merge.

Analyze code quality debt to improve maintainability and readability.

Monitor and maintain the health of multi-agent workflows with proactive checks and anomaly detection.

Automate technical debt analysis across multiple dimensions and generate a unified remediation plan.

ML/AI/LLMOps/MLOps specialist for model training, evaluation, RAG pipelines, vector DBs, experiment tracking, hyperparameter tuning, deployment, and PyTorch build/CUDA toolchain triage. Owns the full ML lifecycle from data to production monitoring.

Specialist in Terraform, AWS CDK, and Kubernetes for managing infrastructure as code.

Multi-agent project manager that orchestrates concurrent workflows and resolves blockers in real-time.

Expert in end-to-end telemetry and observability for SRE teams, utilizing OpenTelemetry and Prometheus/Grafana.

Code review methodology for PRs covering correctness, security, performance, and maintainability. Includes DIFF analysis, risk assessment, test coverage verification, and a comprehensive review checklist.

Security-focused reviewer for vulnerability detection, auth validation, input sanitization, secret management, AI-specific threats (prompt injection, data leakage, MCP poisoning), API abuse prevention, and dependency auditing. Blocks unsafe changes from merging.

Analyzes test debt to identify coverage gaps, flaky tests, and quality issues in your codebase.

A comprehensive AI development toolkit featuring 59 skills and 33 agents for professional-grade workflows.

Reddit-focused research agent that uncovers real-world user experiences and community insights on technical decisions.

Automate CI/CD processes using GitHub Actions and Jenkins pipelines.

Agentic engineering patterns — agent orchestration, delegation contracts, multi-agent system design, memory graph usage, streaming/async pipelines, OOP decomposition, hierarchical delegation, context window management, and agent failure recovery.

Manage your feature backlog efficiently by prioritizing and tracking readiness of specs and Git issues.

Utilize the Claude API for advanced messaging, tool use, and extended reasoning capabilities.

Streamline your codebase onboarding with automated analysis and structured methodologies.

Project-wide coding standards enforcement: naming conventions, file organization, function size limits, complexity budgets, style guides, linting rules, code review standards, and language-specific conventions for Python and TypeScript. Includes linter configs and rules.

Provides structured guidance for executing Dmux workflows effectively.

Evaluation harness for LLM and code quality assessment. Covers Pass@k metrics, golden datasets, LLM-as-judge, benchmark suites, regression detection, and eval-driven development workflow.

Utilize Exa's neural search engine for advanced web research and technical investigations.

Iterative retrieval — progressive context loading, retrieval-then-refine loops, query rewriting, adaptive top-k, multi-hop retrieval, confidence scoring, fallback for low-confidence results, retrieval-time prompt guards.