学ぶ目的やこれまでの理解に合わせて、短い対話型レッスンと復習用資料を作るスキル。学習記録を残し、複数回のセッションにわたる学びを支えます。
- 新しい分野を継続して学びたいとき
- クイズとフィードバックで練習
- 復習用の早見表を作りたいとき
768 件 ・ 関連度順
概要と使いどころ
学ぶ目的やこれまでの理解に合わせて、短い対話型レッスンと復習用資料を作るスキル。学習記録を残し、複数回のセッションにわたる学びを支えます。
工場やオフィスの電力・天然ガス調達を、料金体系、使用量、契約条件から検討するスキル。供給会社の比較、ピーク料金対策、再生可能エネルギー契約や予算作成を支援します。
正解が一つに定まらない判断を、長期的な影響、前提への疑問、実行の現実性、失敗リスクの四つの視点で検討し、反対意見も見える形で推奨案をまとめるスキル。
競合のブランド表現やサービス、実績などを共通の基準で採点し、根拠付きの比較カードと戦略上の二軸図にまとめ、自社が狙う位置の競合を把握するスキル。
2つのエージェントが別々に加えた変更のGit競合を、双方の差分と意図から中立的に解決。競合箇所ごとの判断理由を記録し、ビルドやテストで統合結果を確認します。
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
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。
Guide the user's first Paperclip task when its description invokes /first-task. Interpret the opening answer, clarify their goal, propose a plan or a single task, and wait for approval before hiring agents or executing approved 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。
Plan a weekly editorial calendar by mapping company goals to publishable topics, owners, status, and verification notes.
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 a HANDOFF.md that captures goal, current state, files touched, failed attempts, and next steps — so a fresh Claude session can continue exactly where this one left off. Use when sessions are getting long, Claude keeps retrying the same broken solution, or the user wants to step away and resume later.
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。
Post-implementation gate review: run manual QA on the real surface yourself, then launch ONE gate reviewer (never a panel) to audit goal, constraints, code quality, security, missed context, and QA evidence. Use before a PR handoff or when the user explicitly asks to review completed 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。
Codex-only team orchestration: run a named team of cooperating Codex workers with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of agents/threads/sessions, or to work on something as a team in parallel. FIRST inspects the active tool surface (checking tool_search for deferred tools) and tells the user the route: native MultiAgentV2 agents (flat spawn_agent with task_name) when available, Codex App threads as the fallback, or a plain-subagent split when neither set exists. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team.
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 goal as a project: you coordinate. Use for "agents <task>", "take this to done", "work on this in parallel", "what are my threads doing", "pick up <slug>", "resume <slug>", "keep going until it is merged". Under `/agents` you do the work yourself unless it needs several lanes or a long wait — you judge; the plan line says why. No target you could verify (a file, API, number or measure) → the grill interview first, not threads. Read this skill before proposing anything for `/agents`: without it a proposal is in-session subagents.
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。
Formats and structurally validates local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.
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 agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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。
Curated upstream guidance for Apify Integration Development; use when the workflow matches the user goal.
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。
Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.
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。
Turn any concept, lesson, slide deck, or source material into a Feynman learning cycle in which learners explain first, expose the smallest gap, rebuild the explanation through Socratic prompts, strip jargon, stress-test analogies, and transfer the idea to a new context. Use when the user asks for teach-back, learning by explaining, or a Feynman-style classroom. Do not use when the Feynman technique itself is merely the lesson topic or when study strategy should remain a parallel goal.
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。
Infuse social-emotional learning (SEL) into a concept-centered OpenMAIC classroom as a parallel learning goal. Use when the user asks to add emotional awareness, self-management, empathy, collaboration, relationship skills, resilience, or responsible decision-making to a subject lesson. Do not use when SEL itself should be the standalone content of a counseling, advisory, psychology, or homeroom lesson.
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。
Infuse learning strategies and metacognition into a concept-centered OpenMAIC classroom as a parallel goal. Use when the user wants students to learn how to learn while studying a subject: retrieval practice, self-explanation, prediction before feedback, monitoring understanding, deliberate review, or productive failure. Do not use when learning science or study skills should be the standalone subject of the lesson.
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。
Spin up a personal, motivating daily focus board that renders in a browser canvas and that the user drives by talking to their AI partner. Tasks track status (to-do → in progress → done) with timestamped progress notes and roll up into a "today's momentum" feed; numeric-goal tasks (pages, pomodoros, reps) render as progress-bar counters. Executive-function / neurodivergent-friendly by design: Focus mode, kind "not today" carryover (no overdue-shaming), a brain-dump box, reduced-motion, and gentle deadline countdowns. Add, reorder, and relabel tasks live, assign Eisenhower priority (Do first / Schedule / Delegate / Later), open with an above/below-the-line check-in and a daily mantra, and save an end-of-day recap. Use when someone wants to plan their day, stay focused, kick off a work session, or track progress. Progress persists in the browser (localStorage).
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。
Find, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.
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 iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
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。
Reorient in the current Claude Code session with an evidence-backed map of its goal, pivots, outcomes, current step, and open decisions.
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。
Cancel any active OMC mode (autopilot, ralph, ultragoal, swarm, ultrapilot, pipeline, team) and clean up retired legacy state
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。