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概要と使いどころ
Run Claude Code in autonomous iteration loops until task completion — PRD-based feature development, test coverage improvement, lint fixing, documentation generation, dataset creation, or framework migrations. Uses in-session loop mechanism with specialized templates. Triggers on autonomous loop, iterate until done, run until passing, keep going until, ralph, PRD execution.
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 strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.
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。
Cyclical dogfooding loop: test AI-AGENT-STORIES.md against the live graph, discover new stories, analyze gaps, fix root causes, re-test, write report. Use when: (1) user says "/gap-loop", (2) periodic dogfooding session, (3) after a release or major feature to re-validate stories, (4) before sprint planning to prioritize product gaps.
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 the Codex Optimized Development, Evaluation, and Remediation (CODER) Loop with an orchestration-only coordinator, non-overlapping task-family owners, fresh independent reviewers, evidence-scoped remediation, and final coordinator acceptance. Discover and compose optional MSW, Timebox, MSL, and Codex Voice Optimizer companions as the Slopware Dev Stack without making them dependencies. Use in Codex when the user invokes the CODER Loop, asks to divide a complex change into bounded implementation families with independent reviewers, requests multi-agent implementation without overlapping ownership, requires review and repair until every blocking gap is independently rechecked, asks for the CODER tutorial or Slopware Dev Stack, or wants CODER to install or use its companions. Do not trigger for an ordinary single-agent change, a review-only request, or a non-Codex host.
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 iterate-until-pass loops with ralph-worker agents in a worktree. Use when running [ralph]-marked tasks or looping until verify passes.
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 strict multi-iteration Reflex Loop with phases (PLAN, PRODUCE||PREPARE, EVALUATE, CRITIQUE, REFINE) to improve an artifact until quality gates pass or iteration limits are reached. Use when user asks for iterative refinement, quality-gated generation, or "generate -> critique -> refine" loops.
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 viral referral programs with incentive structures, sharing mechanics, and tracking. Covers one-sided, two-sided, tiered, and milestone models with viral coefficient calculations. Use when someone wants word-of-mouth growth, viral loops, invite programs, or says 'referral', 'viral loop', 'word of mouth', 'invite program', 'refer a friend', 'growth loop', 'referral incentive', 'affiliate program', 'ambassador program', 'get users to invite friends', or 'organic growth'. Even casual mentions like 'how do I get my users to spread the word' or 'can users invite others' should trigger this. Includes anti-fraud measures and copy templates for both referrer and referee. Use this whenever user-driven acquisition or viral mechanics are discussed.
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。
Design AI feedback loops for continuous improvement. TRIGGERS - Use when user needs help with ai-feedback-loop related tasks.
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。
Design agricultural cooperatives. TRIGGERS - Use when user needs help with agricultural-cooperative related tasks.
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 the user asks about the CTI Hyperloop framework, the intelligence lifecycle as a high-tempo loop, or how to map intelligence work across strategic / operational / tactical levels with bidirectional feedback. Liberty91's operational doctrine.
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。
设计 Loop 中的 Maker-Checker 模式: 用独立 agent 审查产出,避免自产自检。 当用户发现 loop 产出质量不稳定、agent 自我评估过于宽容、或需要提升产出可信度时使用。 不适用于: 产出可以客观验证 (测试通过/失败) 的任务、或成本极其敏感的场景。 关键 trigger: "agent 自评不准确"、"产出质量不稳定"、"怎么让 agent 审查 agent"。
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。
识别和管理 Loop 系统的认知风险: 自动化程度越高,你真正理解的部分越少。 当用户发现"仓库里有很多代码但我看不懂"、"loop 产出很多但不确定对不对"、或需要向团队警示 AI 使用风险时使用。 不适用于: 纯技术调试、或产出完全可客观验证的场景。 关键 trigger: "AI 生成的代码我看不懂"、"产出太多理解不过来"、"AI 使用风险"。
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。
"Apply the Co-opetition Value Net framework (Brandenburger and Nalebuff, 1996) to map cooperative and competitive dynamics in business relationships. Use this skill when the user needs to identify complementors, analyze the PARTS framework, or design strategies that simultaneously cooperate and compete with the same players.".
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。
Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached. Use for virtual peer review, reviewer-author revision loops, rebuttal preparation, resubmission polishing, journal paper improvement, response-to-reviewers drafting, and deciding when additional data, experiments, theory, modeling, or author judgment is required before further revision.
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。
Execute ENCODE Hi-C pipeline from FASTQ to contact matrices and loop calls. Child of pipeline-guide. Provides Nextflow execution with Docker and cloud deployment. Use when processing Hi-C data, generating contact matrices, or calling loops. Trigger on: Hi-C pipeline, chromatin conformation, contact matrix, loop calling, TAD detection, Juicer, HiCCUPS, 3D genome.
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。
Manage persistent coding sessions across Claude Code, Codex, Antigravity (agy), Grok Build, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 78 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "auto research", "switch model", "hand off a session", "session handoff", "switch engine", "continue on codex", "continue on claude", "move this session to another engine", "multi-agent coding", "coding session", "session inbox", "grok session", "grok build", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness", "clawo runs", "run ledger", "session cost", "coding-agent token usage", "spend cap", "budget limit", "maxBudgetUsd", "durable workflow", "resume a run", "verify a coding run", "acceptance contract", "evidence bundle", "did the agent's tests actually pass", "protected tests", "agent edited the tests", "human gate", "repair loop", "clawo workflow", "clawo verify", "clawo solve", "clawo fanout", "fix and verify", "solve from the terminal".
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。
Orchestrate work as a cyclic directed graph of subagent-executed nodes with transition criteria on edges, budgeted cycles, and per-node gates (runtime verification, metric, or artifact). Use when the user says "workgraph", "run this as a graph", "graph this work", or when a goal has parallel branches, feedback loops, or mixed gate types that a linear loop cannot express. Every node is sized to a 64k context budget, so small goals run as a two-node do/verify graph and large goals scale out without caps. For clock-driven or metric-driven single loops, timeboxed-iterating and autoresearch remain lighter.
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。
Assemble a finished piece from human-written fragments via an orchestrated two-loop pipeline - an assembly loop (assembler + cold reviewer) that sequences the fragments into a draft, then a polish loop (polisher + cold reviewer), then frequency analysis and a catalog-deslop pass with a regression gate. Two modes with opposite fidelity contracts - stitch mode preserves the author's exact wording, narrative mode preserves every idea but may rewrite freely. Use when the user says "mosaic", "assemble my fragments", "stitch these notes into a post", or provides a fragments file to turn into a finished piece. For writing from a topic with research, use article-factory; for prose from scratch, use the prose skill.
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 the systems of a game from a locked concept — core loops, meta loops, player verbs, progression, content systems, level structure, and narrative integration. Triggers on "game design doc", "GDD", "system spec", "core loop design", "progression design", "level design", "MDA", or "design the systems". Produces a design doc plus per-system specs that game-balancer numbers, iap-manager stocks, and godot-engineer builds. Stops at design — no number tuning, pricing, or engine code. For balance numbers see game-balancer; for the engine implementation see godot-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。
Autonomous goal loop — give it ONE goal plus how to verify it, the agent runs check→fix→check itself and comes back only with the finished result (code with audit, research with fact-check, content with critique, audit/backtest). Self-verification instead of constant supervision, with hard safety guards. Vary the loop with a verification rubric designed before it runs. Triggers — "work autonomously to the result", "don't come back until it's done", "run the loop yourself", "drive it to done".
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。
Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to cursor-implementation-loop, this plugin's kernel skill, with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to cursor-implementation-loop. Requires this plugin's cursor-implementation-loop skill; they ship together.
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。
Own goal-first engineering outcomes: investigate, find root cause, design, plan, then delegate implementation unit-by-unit to implementation-loop with verification and honest reporting. Use to fix, build, or own an outcome end to end; investigate-and-fix; "make X work"; or plan-then-execute in one request. A request with an approved plan or equivalently precise spec that needs nothing beyond implementation belongs directly to implementation-loop. Requires implementation-loop and an authenticated backend CLI to execute.
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 autonomously improving a measurable scalar metric through bounded, git-tracked iterations: modify one scoped change, verify, keep or revert. Triggers on /mk:loop, 'optimize coverage/bundle size/lint count', 'iterate until the metric improves'. NOT for subjective cleanup (see mk:cook), known-root-cause bugs (see mk:fix), behavioral grading (see mk:evaluate), or shipping (see mk:ship).
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。