Claude Skills by baekenough

Show system status and health checks

6-stage structured development cycle with stage-based tool restrictions

Detect stuck loops and advise recovery strategies

PostgreSQL performance optimization guidelines from Supabase. Apply when writing SQL, designing schemas, configuring RLS, or optimizing database performance.

Use when encountering any bug, test failure, or unexpected behavior. Enforces a strict reproduce-first, root-cause-first, failing-test-first debugging workflow before fixing.

Auto-decompose large tasks into DAG-compatible parallel subtasks

Three-layer token defense stack — audit current settings, apply safe/CI levers, and monitor status

Type-safe TypeScript patterns from industry standards

Sync documentation with project structure

Update agents from external sources (GitHub, docs, etc.)

Deploy applications to Vercel with auto-detection and preview URLs

UI code review with 100+ rules for accessibility, performance, and UX

Use the project wiki as RAG knowledge source — search wiki pages to answer codebase questions before exploring raw files

Generate and maintain a persistent codebase wiki — LLM-built interlinked markdown knowledge base (Karpathy LLM Wiki pattern)

Worker-Reviewer iterative pipeline for quality-critical code with review cycles

Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts

Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile

Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation

Quantitative agent evaluation using 4-metric framework (correctness/step_ratio/tool_call_ratio/latency_ratio) with ideal trajectory annotation and capability-categorical taxonomy. Use when measuring agent efficiency, comparing agent variants, or gating new agents through correctness→efficiency phases. Complements harness-eval (SE benchmarks) and evaluator-optimizer (qualitative rubric).

Use when a design or decision needs adversarial multi-round scrutiny from several independent model vendors. Runs anonymized A/B/C reviewer rounds with a rotating judge and produces a consensus report.

Apache Airflow best practices for DAG authoring, testing, and production deployment

Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration

Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)

Analyze project and auto-configure agents, skills, rules, and guides

Audit agent dependencies and references

AWS patterns from Well-Architected Framework

Fetch Claude Code official documentation. Use when updating local reference docs or checking official spec.

Monitor Claude Code releases and auto-generate GitHub issues for each new version

Create a new agent with complete structure

code-review-graph (CRG) MCP wrapper — token-efficient context retrieval via AST knowledge graph. Exposes 4 core tools from CRG.

CVE triage workflow for vulnerability analysis, reproduction assessment, and patch verification

YAML-based DAG workflow engine with topological execution and failure strategies

dbt best practices for SQL modeling, testing, and analytics engineering workflows

Routes data engineering tasks to the correct DE expert agent. Use when user requests data pipeline design, DAG authoring, SQL modeling, stream processing, or warehouse optimization.

Research-validated planning — research → plan → verify cycle for high-confidence implementation plans

Multi-angle release quality verification using parallel expert review teams

Generate 4-6 parallel design mockups for rapid visual comparison — adapted from gstack /design-shotgun pattern

Routes development tasks to the correct language or framework expert agent. Use when user requests code review, implementation, refactoring, or debugging.

Refactor code for better structure and patterns

Review code against language-specific best practices

Brand-consistent editorial diagrams — SVG generation for release notes, architecture docs, and marketing materials

Django patterns for production-ready Python web applications

Docker patterns for optimized containerization

Parameterized evaluator-optimizer loop for quality-critical output with configurable rubrics

FastAPI patterns for high-performance async APIs

Fix broken agent references and symlinks

Flutter/Dart development best practices for widget composition, state management, and performance

Full Self Driving — autonomous release loop that processes all auto-dev-eligible GitHub issues until none remain, by repeatedly running /pipeline auto-dev then /homework.

Go backend patterns from Uber style and standard layout

Idiomatic Go patterns from Effective Go