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概要と使いどころ
Orchestrates end-to-end interview preparation for senior ML/AI engineers targeting Anthropic and peer companies. Use for prep timeline generation, story coherence across rounds, mock scheduling, and debrief analysis. Activate on "interview prep", "interview loop", "Anthropic interview", "prep timeline". NOT for resume writing, career narratives, or individual round-type practice.
日本語の概要は準備中です。原文の説明を表示しています。
Designs human-in-the-loop review points for DAG workflows. Determines what to present to the human, how to collect feedback, and how to route approve/reject/modify decisions back into the DAG. Use when adding approval gates, designing review UX, or handling human feedback in agent workflows. Activate on "human review", "approval gate", "human-in-the-loop", "human gate", "approval workflow", "user review step". NOT for executing human gates at runtime (use dag-runtime with Temporal signals), general UX design, or chatbot conversation design.
日本語の概要は準備中です。原文の説明を表示しています。
Cooperative vibe coding across machines — real-time collaborative development with humans and AI agents. Covers current tools (Live Share, Code With Me, Zed, Cursor multiplayer, tmux), git-based async patterns, AI agent coordination, and the aspirational future of multi-human multi-agent development. Activate on: "pair programming", "vibe coding together", "collaborative coding", "mob programming", "remote pairing", "code together", "multiplayer coding", "Live Share", "Code With Me", "ensemble programming", "cooperative development". NOT for: building a real-time collaboration ENGINE (use real-time-collaboration-engine), git workflow mechanics (use git-best-practices), single-user AI coding assistance (use prompt-engineer).
日本語の概要は準備中です。原文の説明を表示しています。
Assesses whether hysterectomy and oophorectomy are medically necessary as part of gender-affirming surgery for transgender patients. Triggered when a patient is planning gender-affirming surgery and clinicians need to determine if total hysterectomy and oophorectomy should be included.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end workflow orchestrator. Walks the 11-phase pipeline, invoking each phase skill in order inside an internal loop, yielding at consent gates (/approve-direction, /approve-swarm, /grant-commit), and exiting cleanly on yield/failure/done. Decides swarm-vs-solo at Phase 6. Auto-loops /tdd on integrate failures that don't require a spec change. The harness_continuation Stop hook is a safety net that re-fires harness only when the loop exited mid-flow.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
日本語の概要は準備中です。原文の説明を表示しています。
Use when designing product-led retention — habit formation, trigger-action-reward, network vs single-user loops. Triggers on 'why don't users come back', 'design a habit loop'.
日本語の概要は準備中です。原文の説明を表示しています。
Use when shaping an engineering hiring loop — stages, take-home vs live, calibration, bar-raiser, signal-vs-noise audit. Triggers on 'design our interview loop', 'audit our hiring bar'.
日本語の概要は準備中です。原文の説明を表示しています。
[Code Quality] Use when you need to combine /why-review + /fix in a recursive loop — each round runs /why-review to find validated findings then /fix to resolve them, then loops again over the CHANGED target until a fresh full /why-review produces zero findings (nothing left to fix).
日本語の概要は準備中です。原文の説明を表示しています。
[Code Quality] Use when you need to combine /changes-review + /fix in a recursive loop — each round runs /changes-review (report-only) to surface validated findings over a fixed diff scope, then /fix to resolve them, then loops again with a FRESH full /changes-review over the CHANGED diff until one complete pass produces zero validated findings (nothing left to fix).
日本語の概要は準備中です。原文の説明を表示しています。
How to MEASURE this repo instead of eyeballing it — interpret the loop-station context-budget trend (history.jsonl, thresholds, the tokenizer-switch gotcha), read a session trace, use the eval ledger (cost-per-success), and pick the right evidence tool (app-shots, smoke-deployed, db-counts, --check modes). Use when asked "is the harness bloating", "how big is CLAUDE.md really", "did this agent run actually succeed", "prove this works", "what evidence do we have", or when tempted to declare a capability (browser, tool) unavailable. For RUNNING the loop-station scripts, defer to the loop-station skill — this skill is interpretation + the wider evidence toolkit.
日本語の概要は準備中です。原文の説明を表示しています。
Observe the harness itself — (WS1) measure context budget as a deterministic, trendable inventory (tokens per CLAUDE.md / skill / agent, lexical redundancy, per-CI cold-write totals; committed history.jsonl), (WS2) reconstruct the real invocation trace (which skills/agents/tools fired and how they nested) from session transcripts, and (WS-A) roll the per-run CI traces up into a committed weekly usage record (per-skill invocation counts; usage.jsonl) — the usage side of the dead-weight join. Use for "context budget", "how big is CLAUDE.md / our skills", "is the harness bloating", "how do our agent loops actually run", "which skills actually get used", "trace this session", "loop station".
日本語の概要は準備中です。原文の説明を表示しています。
从整个工作区出发，系统性地重组认知结构并整理全局文档归属。适用于首次建立认知结构、或积累了大量散落文档需要批量归档时。基于三大闭环框架（Loop1 Skill体系 / Loop2 思维体系 / Loop3 场景投射）做全工作区分类路由。触发词：「系统整理」「重组认知结构」「从文档构建认知结构」「整合文档」「全量梳理」「认知结构乱了」「全工作区整理」「文档归属梳理」「如何加入认知结构」「怎么加入认知结构」「按规范加入」「未更新的文档怎么处理」「这些文档要怎么整理」「有没有关于X的已有文档」。注意：若用户仅询问流程而非执行重组，执行 Step 0.5（检查分类清单现状）后，先向用户展示已有文档状态和分类建议，再确认是否执行完整重组。
日本語の概要は準備中です。原文の説明を表示しています。
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
日本語の概要は準備中です。原文の説明を表示しています。
명령형 for/while 루프를 Stream API/Collection Pipeline으로 변환하여 데이터 흐름 의도 명확화. "스트림으로 바꿔", "루프를 파이프라인으로", "for문 stream", "/replace-loop-with-pipeline" 요청 시 사용. 단, 루프 안 로직이 컬렉션 클래스로 모여야 하면 /first-class-collection이 적합. /replace-loop-with-pipeline [commit-ref]로 호출.
日本語の概要は準備中です。原文の説明を表示しています。
Detects deeply nested loops with duplicated inline logic and recommends extracting into small, named functions. Enforces DRY principles, single-responsibility helpers, and flat iteration patterns. Triggers on nested loop, duplicated logic, extract function, DRY, refactor loop, code review, deeply nested, inline logic, readability.
日本語の概要は準備中です。原文の説明を表示しています。
Interaktives Reißverschluss-Audit-Verfahren für eine Serie von Apps/Prüfobjekten: der User testet live und gibt kurzes Feedback im Chat, der Agent startet dabei bereits das nächste Objekt UND wertet parallel das Feedback des vorigen aus (strukturiert erfassen, Reparaturaufträge sofort an Worker delegieren) — statt sequenziell zu warten. Nutze diesen Skill bei "human-loop-audit", "lass uns die Apps im Reißverschluss durchtesten", "ich teste, du wertest aus und reparierst", oder wenn eine Reihe von GUIs/Produkten gemeinsam mit dem Nutzer durchgetestet werden soll und Befunde sofort in Reparaturen münden sollen. Abschluss ist eine strukturierte Befundliste je Objekt (Funktioniert/Defekt/Wunsch) plus die Liste der bereits gestarteten Reparaturen.
日本語の概要は準備中です。原文の説明を表示しています。
Start, inspect, or continue a persistent SIPS self-improvement loop. Use when the user asks for /selfloop, wants the agent to iteratively improve itself, or wants a goal dedicated only to SIPS and agent capability.
日本語の概要は準備中です。原文の説明を表示しています。
River Review のメインエントリポイント。 レビュー依頼の intent classification → 専門 skill 選択 → 実行 → finding verification → feedback classification → fixture / reference / suppression への還元までを束ねる improvement-loop orchestrator。
Expert en agent loops (ARIS, Ralph, recherche autonome, build-score-budget, guardrails)
日本語の概要は準備中です。原文の説明を表示しています。
Run a prompt repeatedly on an interval, using the harness built-in plus loop templates. Generated from plugin-commands.json; invoke as $bdb-aos:loop.
日本語の概要は準備中です。原文の説明を表示しています。
Use when turning something that happened into something that makes the next run better - "write a retro", "record this paper cut", "this bug escaped verification", "make this an eval", "why do we keep hitting this", "did that change actually help", "scorecard", "what did we learn from that run", "lessons keep getting re-learned". Covers the six-step loop (capture, classify, convert, change, measure, retro), the repo artifact each step produces, and how escaped bugs become eval cases. Do NOT use to design or judge a single workflow experiment (see `workflow-experimentation`, which this loop feeds), to decide where to run work (see `dogfooding`), or to debug one failed execution in the moment.
日本語の概要は準備中です。原文の説明を表示しています。
Master orchestrator for the 5-step productivity loop. Runs audit, architect, analyst, refinery, and compounder in sequence or individually. Use when you want to run the full loop, start the system, check system status, resume from where you left off, or run a specific step. Manages state, sequencing, and skill chaining. Supports full loop, single step, resume, and status-only modes.
日本語の概要は準備中です。原文の説明を表示しています。
Master orchestrator for the 5-step productivity system. Runs the full audit-architect-analyst-refinery-compounder loop or individual steps. Use when: (1) "run the full loop", "start the system", "architect system", (2) "run step N", "run audit", "run architect", (3) "what step am I on?", "system status", "where am I in the loop?", (4) "continue", "resume", "next step". Manages state, sequencing, and skill chaining across all 5 steps.
日本語の概要は準備中です。原文の説明を表示しています。