baekenough

Full R017 verification (5+3 rounds) before commit

Load a skill profile to switch active plugin set. Use when user wants to focus on a specific workflow (web-app/data-eng/harness-dev/minimal) and reduce skill enumeration block size per

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

Deploy applications to Vercel with auto-detection and preview URLs

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

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

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

Structured SE task evaluation using 15 benchmark definitions from claude-code-harness research

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

Multi-angle release quality verification using parallel expert review teams

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.

Invoke and resume YAML-defined pipelines by name — /pipeline auto-dev runs the full release pipeline

Analyze release workflow findings and recommend follow-up actions — execute immediately or register as issues

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

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

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.

Invoke and resume YAML-defined pipelines by name — /pipeline auto-dev runs the full release pipeline

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.

On explicit /homework invocation, analyze the current and linked previous sessions, extract mistakes (찐빠), and report them via omcustom-feedback with a confirmation gate. Auto-activation on session cleanup/session-end signals is OPT-IN (default OFF) — requires an explicit project/user directive. Use when explicitly auditing recent work for harness gaps.

hada.io RSS feed monitoring for AI agent/harness articles with automated /scout analysis

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

Multi-LLM adversarial consensus loop — 3+ LLMs compete to find flaws in designs/specs until unanimous agreement is reached

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

Multi-LLM adversarial consensus loop — 3+ LLMs compete to find flaws in designs/specs until unanimous agreement is reached

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

Execute OpenAI Codex CLI prompts and return results

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

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

AI가 콘텐츠만 작성하면 키보드 네비·사이드 네비·풀스크린 no-scroll이 보장되는 단일 HTML 발표자료(슬라이드 덱)를 생성하는 스킬. PPT 대체용 웹 기반 슬라이드.

Multi-LLM adversarial consensus loop — 3+ LLMs compete to find flaws in designs/specs until unanimous agreement is reached

Execute Google Gemini CLI prompts in non-interactive mode and return structured results. Enables hybrid AI workflows combining your AI agent's reasoning with Gemini's code generation. Supports text, JSON, and stream-JSON output, approval modes (normal, yolo, sandbox, plan), model override, timeout control, and working directory selection. Use for code generation, research, analysis, and reasoning tasks via Google Gemini CLI.

Analyze external URLs to evaluate fit with your project and auto-create GitHub issues with structured verdicts. Uses a lightweight project fingerprint for token-efficient codebase analysis with git-hash-based cache refresh.

YAML-based sequential workflow engine — define, list, run, resume, add, and delete pipelines from natural language or YAML files. Supports skill invocation, free-form prompts, conditional steps, foreach iteration, state tracking, and halt-and-resume error recovery.

Execute OpenAI Codex CLI prompts in non-interactive mode and return structured results. Enables hybrid AI workflows combining your AI agent's reasoning with Codex code generation. Supports text and JSON output, effort levels (minimal to xhigh), model override, timeout control, and full-auto mode. Use for code generation, research, analysis, and reasoning tasks via openai codex CLI.