Noah Sheldon

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.

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

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.

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.

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

Implement comprehensive E2E testing patterns using Playwright for web applications.

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

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.

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.

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.

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

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

Streamline AWS deployments with various patterns and infrastructure as code.

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

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

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.

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

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

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.

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

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

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.

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

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

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

Build autonomous AI agent workflows with safety and validation mechanisms.

Manage continuous agent workflows with quality gates and health monitoring.

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

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.

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

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.

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

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

Workflow guidance for Postgres Patterns.

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

Streamline your codebase onboarding with automated analysis and structured methodologies.

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.

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

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

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

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

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.

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.

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.

Implement TypeScript patterns for type-safe and maintainable code.

Identify and report on process debt in your development workflow.

Streamline your tasks with specialized workflow guidance for documentation lookup.

Analyzes architecture debt to identify structural issues in codebases.

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 workflow guidance for GitHub operations.

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

Skill authoring workflow for packaging repeatable practices as reusable skills.

Identify and analyze documentation debt to enhance developer productivity.

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

Guidance for implementing repeatable workflows using Docker patterns.

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.

Workflow guidance for Deployment Patterns.

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

Workflow guidance for Security Scan.

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

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

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

Efficient patterns for building and training models in PyTorch.

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

Generate structured reports on codebases for onboarding and auditing.

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.

Analyze code quality debt to improve maintainability and readability.

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

Guidance for implementing Hexagonal Architecture in software projects.

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

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.

Provides structured guidance for executing Dmux workflows effectively.

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

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.

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

Workflow guidance for Frontend Design.

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

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.

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

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

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.

Comprehensive AWS DevOps practices for modern application deployment.

Comprehensive observability and telemetry solution for production systems.

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.

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

Systematically learns unfamiliar codebases to produce comprehensive learning reports.

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.

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.

Fast and authoritative documentation lookup agent using Context7 MCP.

Workflow guidance for Database Migrations.

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