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概要と使いどころ
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。
Draft performance reviews, self-assessments, peer reviews, and upward feedback in your own voice. Analyzes your contributions, emails, and meeting history via WorkIQ, then produces honest, impact-focused drafts using the STAR format. USE FOR: write my performance review, draft self-assessment, peer review, 360 feedback, annual review, mid-year review, upward feedback, write review for colleague, performance appraisal.
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。
Author a NEW skin for the reskinnable-demo app. A skin is a self-contained domain plugin under src/skins/<id>/ that implements the frozen `Skin` contract (src/shell/skin-contract.ts) to swap the app's entire experience — brand, theme, layout, pages, tools, data, and agent — as a live sales demo. Use when the user says "add a skin", "create a skin", "new skin", "reskin the app", "make a <domain> skin", or wants the app re-themed as a new product. Do NOT use for editing the shell itself (src/shell/**), the shared token vocabulary (src/app/globals.css), or the shipped skins unless explicitly asked.
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。
Work on one hard mathematics problem in this session yourself, with no sub-agents: reason in stages, record each settled step in a notes file so that nothing written is lost if a response is cut off, and end with a self-contained proof.md. Usage: /math-proof:solo <the problem, stated in full, or the path of a file holding it>.
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 personal Claude Code usage & impact report ("receipts") from this machine's local session transcripts — for justifying Claude Code usage/spend to a manager, self-review, or "what have I been using this for" check-ins. Mines ~/.claude/projects locally (no extra API calls beyond one final write-up), cross-references local git history, and writes a markdown report plus a self-contained HTML receipt to your home directory. Use when the user asks for "receipts", an "impact report", "usage report", wants to "show my Claude Code activity", "prove the value of Claude Code", or runs `/receipts`.
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 before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against references/review-rules.md, traces call paths for dead code). Reports findings grouped by severity, flagging what to fix before submitting (blocking issues + dead code) vs what to leave for the actual review. Report-only — does not edit files.
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。
Configure, extend, debug, or contribute to PicoClaw itself. Use when the task is about PicoClaw CLI commands, config.json, gateway, auth, models, skills, MCP servers, cron, routing, sessions, self-evolution, built-in slash commands, or repository internals. Use PicoClaw-native workflows, terminology, paths, and configuration.
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。
Structure a performance review with self-assessment, manager template, and calibration prep. Use when review season kicks off and you need a self-assessment template, writing a manager review for a direct report, prepping rating distributions and promotion cases for calibration, or turning vague feedback into specific behavioral examples.
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。
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
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 how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
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。
Diagnoses, remediates, and manages Identity and Access Management (IAM) access issues on Google Cloud. Supports two distinct operational modes: (1) Requester Flow for developers encountering access denials (capturing error context, self-service PAM JIT activations, elevated developer self-remediation, or logging structured tickets), and (2) Resolver Flow for privileged administrators (authoritative Policy Troubleshooter analysis, deny policy exemptions, least-privilege role discovery, and PAM/IAM provisioning).
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。
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
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。
Renders the current session's output (analysis, research, red team, report, plan) as an extremely well-designed, self-contained HTML artifact via a deterministic renderer — the model distills content into typed JSON, the tool owns all layout/typography/color. USE WHEN /HTML, HTML artifact, render this as HTML, make this an HTML page, artifact of this analysis, designed HTML output. NOT FOR deployed websites or web apps (build the project directly), web UI design systems (use Webdesign), static images or diagrams (use Art), or writing the underlying analysis itself (run the analysis first, then /HTML renders it).
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。
Matomo Reporting API extension. Self-hosted or Matomo Cloud analytics as a GA4 alternative or complement. Organic traffic, landing pages, device / country breakdowns, referrers, search keywords. Triggers on "Matomo", "self-hosted analytics", "analytics ohne Google", "GA4 alternative", "Matomo Reporting", "Piwik".
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 wants Codex to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, wants Codex to review past sessions, learn preferences, consolidate memory/skills, run dry-run/run/adopt/status for SkillOpt-Sleep, or schedule background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated memory + skills behind a held-out gate.
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 wants the dsh agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, skill/memory consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule background self-optimization. Drives the skillopt_sleep engine through the skillopt_* tools: harvest past sessions -> mine recurring tasks -> replay via a selected backend -> consolidate validated skills behind a held-out gate.
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 wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule background self-optimization. Drives the skillopt_sleep engine: harvest past sessions -> mine recurring tasks -> replay through a selected backend -> consolidate validated CLAUDE.md/SKILL.md behind a held-out gate.
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。
Provides guidance for experiment tracking with SwanLab. Use when you need open-source run tracking, local or self-hosted dashboards, and lightweight media logging for ML workflows.
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。
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation 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。
当用户发现自己在为立场辩护、看不清现实、或反复立志却改变不了自己时调用。 核心理念: 身份是认知牢笼也是行为杠杆——放下身份才能看清真相(痛苦=真相时刻), 更新自我形象才能替代自律(对外承诺)。 不适用于: 需要专业心理咨询的深层创伤。 Triggers: 立场/身份/自我/看不清现实/改变不了自己/自律失败/identity/self-image
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。
Analyzes DWARF debug information in compiled binaries. Use when inspecting .debug_* sections, DIE trees, or DW_TAG_/DW_AT_ entries with dwarfdump/llvm-dwarfdump or readelf, verifying debug info with llvm-dwarfdump --verify, answering DWARF standard questions, or writing code that parses DWARF (libdwarf, pyelftools, gimli).
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 you have a task and must decide WHO does it — yourself, a spawned subagent, or another agent in the topology that already holds the context. The rule: how much would a blank slate have to read in to do this correctly? A lot → route to a context-holding agent; a little → subagent; unsure → a real agent or yourself. NOT the mechanics of fanning out (that's dispatching-parallel-agents / subagent-driven-development) — this is the who/whether decision, and the failure mode that makes teams abandon 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。
Monitor Nx Cloud CI pipeline status and handle self-healing fixes automatically. Use when user says "watch CI", "monitor pipeline", "check CI status", "fix CI failures", or "self-heal CI". Requires Nx Cloud connection. Do NOT use for local task execution (use nx-run-tasks) or general CI debugging outside Nx Cloud.
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。
Diagnose and repair LoopX control-plane drift or agent behavior drift. Use when a LoopX task makes unexpectedly small progress, follows a stale or contradictory recommended_action, ignores a higher-priority blocked item while doing fallback work, reports vague owner/user gates, loses todo projection, misaligns benchmark treatment with the real product path, mixes temporary artifacts into commits, or when the user asks for root-cause analysis, self-repair, or why the harness/agent behaved unexpectedly.
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。