7,422 件 ・ 関連度順
概要と使いどころ
AI 工作资产化诊断器 / Assetization Router：当用户提供 AI 协作会话、重复任务、prompt、工作流描述、 团队 AI 使用场景或一次成功交付过程，并要求判断应该沉淀成 Prompt、Context Pack、Workflow、Skill、 Loop、System，或根本不值得沉淀时使用。它只做诊断、分层和下一步资产建议，不替代具体 Skill 创建、 PRD 起草、调研、实现或自动化执行。不用于普通事实查询、一次性文案、trace 根因分析或高责任专业判断。
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。
复杂探索资产化 / Complex Exploration：当用户面对复杂、不确定、多轮迭代的产品策略、Roadmap、商业化定价、竞品定位、复杂 PRD 前置探索、项目复盘或方法论沉淀任务时使用。它先判断任务类型，暴露隐含假设，重构真正问题，规划探索路径和中间产物，并在结束后沉淀认知、结构、方法论、工具和影响力资产。不用于简单润色、翻译、摘要、明确执行任务；问题只需早期认知校准时优先用 ai-collaboration-calibration，已有方案要压力测试时用 grill-me，系统专题研究用 research-topic-compiler。
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。
Agent trace 诊断器：当用户提供 trace、日志 JSON、agent 执行记录、工具调用序列，或说“看下这个日志/trace，定位根因”“只说明问题不要改文件”时使用；用中文输出核心根因、可视化执行流程图、trace 证据链、可能文件/行和修复建议，默认只读。不用于没有日志证据的新功能设计、普通代码解释或直接修复代码。
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。
设计脑暴 / 实现前方案校准：当用户想把已基本成立的想法、功能方向或产品问题，在写 PRD、画 mockup 或进入开发计划前，先比较方案、确认取舍、对齐 UI/视觉约束，并收敛成可执行设计 spec 时使用。 可用中文唤起：“先脑暴一下方案”“先不要写 PRD，帮我设计几种路径”“参考 brainstorming 把这个需求变成设计 spec” “实现前先讨论设计”。问题还没定义清楚时先用 ai-collaboration-calibration；已有方案要压力测试时用 grill-me； 直接写 PRD 时用 prd-architect；grill-me 返回精确设计 gap 时，本 Skill 只输出 Design Delta。
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。
协作校准 / 认知校准 / 问题脑暴：当用户有模糊感受说不清问题、方案越补越复杂、想挑战假设、 想重新定义问题、想知道成熟领域里怎么叫这个问题时使用。 可用中文唤起："帮我想想""先聊一下""一起脑暴""我感觉有问题但不清楚是什么" "先别执行，帮我看清问题""挑战我的假设""这个方案是不是想错了""帮我做认知校准" "双向钢人""钢人论证一下""正反最强论证，给我明确判断"。 也适用于：用户直接说"帮我做 X 功能""接入 Y 平台"但背景复杂、或对话早期感觉方向可能跑偏时， AI 主动识别并建议进入脑暴模式。 这里的“挑战假设”主要指问题定义、目标、约束和领域定位层面的假设；如果问题已确认且用户已有具体方案、 计划、架构或决策要压力测试，应转用 grill-me。不用于翻译、摘要、格式整理、单文件小改等简单执行任务。
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。
研究データ管理計画（DMP）の作成とデータ公開・保管方針の整理を支援する
GEODE CHANGELOG.md management rules. Version releases, change logging, scope determination, format standards. Triggers on "changelog", "release", "version", "릴리스", "변경사항", "버전".
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。
Reference when designing autonomous agent systems or deciding agent freedom/safety/context management/collaboration infrastructure. 10 design principles distilled from Karpathy autoresearch (autonomous ML experiment loop) + AgentHub (agent-native Git DAG). Triggered by "autoresearch", "agenthub", "ratchet" ("래칫"), "context budget", "dumb platform", "program.md", "overnight", "autonomous experiment" ("자율 실험"), "branchless", "single-file constraint" ("단일 파일 제약"), "fixed time budget" ("고정 시간 예산") keywords.
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。
Manages Pi packages across their lifecycle: discovers, audits, installs, upgrades, removes, enables, disables, filters, and configures extensions, skills, prompts, and themes from npm, Git, or local sources. Use before any Pi package install or upgrade, when reviewing available updates, changing package activation or configuration, or maintaining the package inventory.
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。
Structures git branches and worktrees: keeps unrelated changes on separate branches, isolates each in its own worktree created so the repository's setup runs, records dependencies with git-machete, and recombines them into a temporary mixdown branch for local testing. Use before creating any branch or worktree in a codebase that works on more than one branch, including branching off the default branch to start a change; when starting work in a fork, clone, or third-party checkout; when choosing what a new branch should be based on; when a branch is growing a second unrelated concern; when deciding whether to stack branches or keep them independent; when preparing a change for a pull request or patch submission; when handed an existing worktree or branch to implement and commit in a fork; or when a local build needs several in-progress branches combined. Not needed where the repository clearly commits everything to the trunk, or holds notes or personal data rather than code.
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 working in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.
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。
Enforces Beads policy for a repository maintained initially by one owner, granting issue-management and commit authority while requiring explicit permission for Git pushes (other than to the user's own fork) and Dolt sync or push operations. Use when the user asks to enroll, repair, or operate a solo-maintainer Beads workspace, and when working with Beads in a repository that may carry a beads-solo enrollment, including when bd refuses a schema migration or mentions a remote.
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。
Gives a repository one idempotent, repo-local worktree setup script (local env files, dependency install, build steps) that worktrunk's `.config/wt.toml` pre-start hook and Orca's `orca.yaml` scripts.setup both call, so every new git worktree is usable at once. Use when adding or fixing worktree setup hooks, writing `wt.toml` or `orca.yaml` setup, when new worktrees lack dependencies or `.env` files, or when asked to make worktrees "just work" in a repo. For creating a worktree in a repo that already has setup, use `git-branch-management` instead.
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。
Preserve output from expensive one-shot commands for monitoring and later analysis. Use when rerunning a build, API query, CI inspection, or diagnostic would be costly and a managed background process is not the better interface.
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。
Grind through ready beads in priority order by running several issues at once, each in its own isolated git worktree managed by worktrunk (`wt`), then merging the finished branches back one at a time. Use when asked to work the beads queue in parallel, to run N issues concurrently, or when a serial grind is too slow and the ready issues are independent.
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。
Deterministic AI development workflow orchestrator. Manages task boards (.jonggrang/jonggrang-tasks.json), runs 16-phase pipelines (BUGFIX/SMALL/MEDIUM/LARGE), installs lifecycle hooks for Claude Code and OpenCode, and coordinates five specialist roles (Lead/Developer/Reviewer/TestLead/Tester). Use when planning features, executing multi-step development workflows, or orchestrating AI coding agents. Run via npx jonggrang.
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。
Generate TUI screen/view with layout, keybindings, state management, and tests
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。
Eng manager-mode plan review. Lock in the execution plan, data flow, diagrams, edge cases.
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。
IBM's autonomic computing vision for self-managing systems with self-configuration, healing, optimization, and protection
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。
Jetpack Compose navigation expert with type-safe routes, Hilt DI, and MVVM/MVI architecture. Activate on: Jetpack Compose navigation, Compose type-safe routes, Hilt dependency injection, MVVM Android, MVI pattern, Compose state management, NavHost, ViewModel. NOT for: XML layouts (use frontend-architect), iOS SwiftUI (use swiftui-data-flow-expert), React Native (use react-native-architect).
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。
Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (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。
Manage feature manifests for code traceability. Use when creating new features, updating existing features, checking feature health, or exploring the feature-to-code relationship. Activates for manifest validation, feature creation, changelog updates, and traceability queries.
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 introducing a feature flag system, choosing between release flags / experiment flags / operational flags / kill switches / permission flags, designing percentage rollouts, building kill-switch + circuit-breaker patterns, structuring evaluation contexts (user IDs, plan tier, region), or building flag-cleanup discipline. Triggers: LaunchDarkly / GrowthBook / Unleash / Flagsmith / OpenFeature, percentage ramp, sticky bucketing, kill switch wired to alerting, "we still have flags from 2 years ago", flag debt, OpenFeature provider, evaluation context, default value on provider failure. NOT for A/B test statistical analysis (separate skill), traffic-split routing at the edge, build-time bundler defines, or environment-based config.
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 database schema with Drizzle ORM and SQLite migrations. Use when adding tables, modifying columns, creating indexes, or running migrations. Activates for database schema changes, migration generation, and Drizzle query patterns.
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。