Build production-grade, phone-friendly terminal UIs (full-screen TUI dashboards) with zero terminal libraries — pure-core architecture, ANSI-safe layout math, line-diffed painting, SGR mouse + touch gestures, hit-testing, narrow-width responsive layouts, and a headless test harness. Distilled from the axfleet fleet-monitoring TUI. MUST trigger when the user says: "build a TUI", "terminal dashboard", "terminal UI", "full-screen CLI", "ncurses-style", "做个 TUI", "终端面板", "终端界面", "命令行 dashboard", "TUI 适配手机/Moshi", "mouse support in terminal", or asks to add tabs/mouse/touch/responsive behavior to an existing terminal program. Cross-platform: works on Claude Code, OpenAI Codex, OpenCode, and OpenClaw.
Activate BEFORE starting any /goal or self-driven autonomous loop. Suppresses end-of-turn status summaries, handoff prose, and "where to pick up next session" wrap-ups that prematurely signal completion. Companion hooks block Stop events when wrap-up patterns appear mid-loop, and block writes to HANDOFF/STATUS/NEXT-SESSION files until the loop is explicitly cleared. Invoke once at loop start with `start <predicate>`; clear on completion with `clear`. Composes with /goal — does not replace it.
Engineering workflow router — picks direct / light / full superpowers cycle based on RISK, not file count. AUTO-INVOKED for tasks touching 3+ files or creating new functionality, but defaults to LIGHT process unless the work has real architectural risk (concurrency, atomicity, protocol, schema). One entry point over the superpowers engine + audit/pr/sweep loops. Skip for bug fixes, typos, single-function changes, and questions. RUNS AUTONOMOUSLY by default — only pauses on Critical Decision Triggers (see Phase -1).
Design, audit, or improve durable context and memory systems for AI agents using layered observations, reflection, conservative promotion, progressive disclosure, and replayable boundary artifacts. Use when building long-running agent memory, deciding what belongs in sessions versus rules or skills, preventing context bloat, or turning repeated corrections and workflows into durable assets. Do not use it to copy another person's private axioms or automatically promote one-off observations.
Diagnose unclear, intermittent, cross-component, or high-impact bugs with evidence and falsifiable hypotheses. Use when the cause is not evident, a previous fix attempt failed, behavior differs across environments, or the failure crosses data or control-flow boundaries. If the cause is already local and obvious, use the fast path instead of turning the bug into an investigation ceremony.
Design or audit model capability, reasoning depth, agent roles, delegation boundaries, and review topology from the actual shape of work. Use when choosing between direct execution and delegation, defining a multi-agent workflow, assigning heterogeneous capability tiers, or correcting wasteful or shallow agent orchestration. Do not invoke it merely because agents are available or to protect the coordinator from reading important context.
Use when designing, auditing, or improving an AI-native workflow, agentic project, coding-agent setup, skill, pipeline, scheduled automation, or LLM-backed product where deterministic code and AI judgment interact.
卡兹克风格公众号长文写作skill——强口语化、叙事驱动、四层自检(L1硬性规则→L2风格→L3内容→L4活人感)的高质量内容产出。 适用场景：需要卡兹克式口语风格的公众号长文（"用卡兹克风格写"、"按khazix风格出稿"、"写一篇有活人感的文章"），或需要叙事驱动+文化升维的深度长文。 不适用：企业官号正式文案、多风格通用写作（用wechat-article-writer）、短内容（小红书/推特）。 触发词：卡兹克风格、khazix风格、活人感写作、写稿子、帮我写长文。