Use when the user wants to systematically fix AI code slop — duplicated logic, over-engineering, silent error swallowing, convention drift, cargo-cult patterns, and other LLM-introduced architectural decay — over a specified duration
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트
Produce a researched long-form article from a topic prompt via an orchestrated pipeline - research agent (first-person sources, working-definition gate), narrative-architecture outline, writer/cold-reviewer loop with an explicit ACCEPT/REVISE verdict contract, then a catalog-deslop pass with a regression gate. The orchestrator dispatches subagents only; the writer never judges its own draft. Use when the user says "article factory", "write an article about X", "run the article pipeline", or asks for a researched long-form piece produced end-to-end. For essays and micro posts in the user's own voice without a research stage, use the prose skill instead.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트
Runs autonomous keep/discard experiments on a codebase to optimize a single metric for a fixed duration, in the style of karpathy/autoresearch. Use when the user says "autoresearch" (optionally with a focus, e.g. "autoresearch the optimizer"), asks to run experiments on a repo overnight, to hill-climb or optimize a metric autonomously, or points at a repo with a karpathy-style program.md.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트
Create custom modules for [Harbor Boost](https://github.com/av/harbor/tree/main/boost), an optimizing LLM proxy. Use when building Python modules that intercept/transform LLM chat completions—reasoning chains, prompt injection, structured outputs, artifacts, or custom workflows. Triggers on requests to create Boost modules, extend LLM behavior via proxy, or implement chat completion middleware.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트
Systematically explore and test any software project (CLI, API, Backend, Library, etc.) to find bugs, usability issues, and edge cases. Produces a structured report with full reproduction evidence (exact commands, inputs, logs, and tracebacks) for every issue.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트
Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
av/skills☆ 202026년 10월 12일 업데이트