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Found 67 Skills
Token-optimized CLI proxy: wrap noisy commands (test runs, builds, git, grep, gh, logs, directory walks) so a filtered summary reaches context instead of a raw dump. Use before running any command whose output is large or repetitive, and to decide when filtering would hide the line you actually need.
한국어 마크다운 볼트(옵시디언 세컨드브레인) 전용 감사·최적화 스킬. 9개 프레임워크(F1 Anthropic CLAUDE.md, F2 Karpathy Wiki, F3 Caveman 압축, F4 Chroma Context Rot, F5 Anthropic Memory, F6 Progressive Disclosure, G7 위생, F8 Reflection, F9 아키텍처·탐색성)를 모든 .md 파일에 적용한다. 영어 원본 os-optimizer와 달리 (1) 사용자에게 보이는 모든 출력(안내·질문·발견 항목·리포트·요약)을 한국어로 내고, (2) 한국어 텍스트에 맞게 토큰 추정 공식·em대시 치환·파일 크기 예산·문체 위생 규칙을 조정한다. 발견된 모든 문제는 구체적 수정안과 함께 나오며(경고만 남기지 않음), 사용자가 항목별로 지금 적용 또는 계획 저장을 고른다. TaskCreate로 진행 상황을 실시간 노출한다. 트리거: os optimizer 한국어, 볼트 감사, 볼트 최적화, 세컨드브레인 감사, 세컨드브레인 정리, 볼트 정리, 프레임워크 감사, 탐색성 점검, 아키텍처 감사, reorg vault, 볼트 리팩터. 볼트 루트에서 실행한다.
Optimize token consumption in Claude Code through cache management, context forking, model selection, and input filtering. Use when user mentions high token costs, context window bloat, slow sessions, cache invalidation, verbose agent output, heavy MCP load, or any context management issues. Covers four critical axes - cache misses, context bloating, wrong model/effort level, and verbose input formats. Triggers on "tokens", "cost", "expensive", "context", "cache", "slow session", "optimize", or symptoms of token waste even without explicit mention.
Track session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.
Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
Configure RTK (command output), Caveman (prose), and stacked compression modes. Manage language packs, custom rules, and test prompt compression reducing tokens by 60–90%.
Orchestrate bounded Codex, Claude Code, Agy, Kimi, or custom CLI workers to finish work with the least lead context and provider usage, following playbooks such as plan big, execute small. Use when the user asks to orchestrate, delegate, compare agents, conserve agent tokens or quota, recover a worker, report what an orchestration did and cost, or work without MCP or Python, when the user types /alethe or a short command such as "alethe report" or "alethe stop", and when they want it on from now on, at any point of a task and alongside other skills. Also use it proactively, without being asked, when a request is large enough to split into bounded independent units, such as a multi-file refactor, a migration, an audit or research across many files. Do not use for a small mechanical task unless explicitly requested.