1,200 件 ・ 関連度順
概要と使いどころ
Use when sending local changes back to the project (an added journal profile, a fixed checklist item, an adapted skill) or reporting a false positive or bug. Finds what changed, scans it for patient data, shows every line and sends nothing until you confirm.
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 a medical AI paper should be found and cited by AI search engines and RAG tools. Optimizes the title, abstract, summary box (Key Points, Research in Context), keywords, preprint, GitHub README/CITATION.cff and Hugging Face card, returning a visible pass/fail checklist.
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 sub-agent hand-off for a fiddly, fully-specified exploit-compile / escalation RUN - the main agent stays on strategy and the board while a cheap sub-agent runs an exact copy-paste checklist behind a false-root/hostname guardrail. Use for "delegate", "offload", "hand this to a sub-agent", "spin a haiku", or the moment a foothold plus a working escalation vector is identified. Main agent dispatches, waits (no parallel duplicate), integrates the result.
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。
Technical implementation of GDPR Article 25(2) data protection by default. Covers strictest privacy settings as default configuration, minimum data collection, limited storage duration, restricted accessibility, and opt-in rather than opt-out patterns. Includes implementation checklist and system design requirements.
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 creation and review of data processing agreements under GDPR Article 28(3), covering all eight mandatory clauses. References the 2021 Standard Contractual Clauses and provides a compliance checklist for processor contracts. Activate when onboarding processors, reviewing DPAs, or auditing processor compliance. Keywords: DPA, data processing agreement, Article 28, processor, mandatory clauses, standard contractual clauses.
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 preparation for supervisory authority (DPA) inspections and investigations including document readiness checklists, interview preparation for key personnel, technical demonstration procedures, on-site logistics, response protocols, and post-inspection follow-up. Covers unannounced inspections, formal audits, and complaint-triggered investigations. Keywords: DPA inspection, supervisory authority, investigation, readiness, interview preparation, response protocol.
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 for implementing GDPR-valid consent under Article 7 conditions and Article 4(11) definition. Covers five core requirements: freely given, specific, informed, unambiguous, and clear affirmative action. Includes pre-ticked boxes prohibition per Planet49 CJEU C-673/17, consent form audit checklist, and practical implementation 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。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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。
Production QA gate for Blender assets using viewport screenshots, validation checklists, naming audits, and ship/no-ship verdicts via MCP.
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。
Deploy funnelcake (api + relay) to ANY environment (production, staging, poc) on GKE via ArgoCD. Use when: (1) Deploying new funnelcake commits, (2) Building Docker images for GKE (amd64), (3) Running ClickHouse migrations, (4) Troubleshooting ImagePullBackOff errors, (5) Syncing staging/poc after production deployment. Covers complete workflow with PRE-FLIGHT CHECKLIST to prevent common deployment failures.
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 before pushing a PR that touched UI to find untranslated keys in any of the 21 non-English locales and to catch user-visible English strings that bypass context.l10n. Reports findings as a checklist; refuses to declare clean until all are addressed or explicitly waived. Invoke with /check-l10n.
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。
Comprehensive product launch planning including GTM strategy, launch checklists, stakeholder communication, beta testing plans, and post-launch analysis. Execute successful product launches with coordinated teams.
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。
ACTIVATE when evaluating acquisition targets, conducting M&A due diligence, planning integration strategy, analyzing synergies, preparing sale materials, assessing culture fit, valuing targets, creating merger checklists, or managing M&A transactions. Critical for executives involved in buy-side or sell-side M&A, from initial target evaluation through post-acquisition integration.
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 operating, debugging, deploying, or monitoring a Telegram bot or Telegram-to-agent gateway. Triggers on "telegram bot down", "bot not responding", "debug bot", "check webhook", "polling vs webhook", "restart bot", "deploy bot", "bot logs", "agent gateway", "Telegram Bot API error", "send test message", "бот не отвечает", "проверь бота", "логи бота", "перезапусти бота". Covers health checks, logs, webhook/polling diagnostics, environment validation, safe restart/deploy checklists, Bot API smoke tests, forum topic delivery, privacy mode, gateway routing, and incident 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。
Draft privacy-policy language and a review checklist tailored to a business model, data practices, and relevant jurisdictions. Use when the user requests a privacy policy or needs to map disclosures for GDPR, CCPA, or similar frameworks; do not use it to guarantee legal compliance.
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 structured customer onboarding workflows with phased checklists, email templates, success milestones, and ownership assignments. Use when the user requests onboarding playbook creation or provides relevant inputs for this 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。
Think and work like an expert Machine Learning Researcher. Use when a task calls for Machine Learning Researcher judgment. Reasons from population risk, double descent, and inductive bias; enforces sacred test sets, hierarchical ablations, nested CV, and HELM/Dynabench-aware benchmarking; reports with NeurIPS and Pineau reproducibility checklists while treating leakage, meta-overfitting, benchmark contamination, Goodhart gaming, and seed variance as first-class failure 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。
Think and work like an expert Mineralogist. Use when a task calls for Mineralogist judgment. Reasons from crystal chemistry, Pauling coordination, and converging optics–XRD/Raman–EPMA evidence; uses RRUFF/Mindat/AMCSD and CNMNC Checklist 2025 while treating preferred orientation, clay EG/heat triads, metamict amorphization, and QEMSCAN library bias as first-class failure 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。
Think and work like an expert Health Economist. Use when a task calls for Health Economist judgment. Reasons from QALY/ICER and NMB opportunity-cost framing, NICE reference case and WTP bands, cohort Markov/PSM models with PSA (CEAC/CEAF), ISPOR transferability and DCE conjoint checklists, CHEERS 2022 and trial-based RCT-CEA reporting.
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。
Think and work like an expert Deep Learning Scientist. Use when a task calls for Deep Learning Scientist judgment. Reasons from CNN/Transformer inductive bias, Li et al. loss landscapes, grokking/mode connectivity, and Kaplan/Chinchilla scaling (~20 tokens/param); designs ResNet/ViT/DiT/MoE/FlashAttention stacks with FLOPs-matched ablations; trains AdamW+cosine/WSD via Megatron-FSDP/DeepSpeed; evaluates FID/MMLU-Pro/MMLU-CF with lm-eval decontamination and Pineau/NeurIPS reproducibility checklists.
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。
Think and work like an expert AI Researcher. Use when a task calls for AI Researcher judgment. Reasons from data generating processes, inductive biases, and compute-data-algorithm trade-offs through train/val/test discipline, seed sweeps, ablation ladders, and standards like NeurIPS reproducibility checklists, model cards, and lm-eval-harness, while treating data leakage (Kapoor & Narayanan taxonomy), benchmark contamination, spurious correlations, and reward-model overoptimization as first-class failure 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。
Create a research thesis — theses/{nnn}-{slug}/ via mkdir-as-CAS, pillar-prioritized spec.md, initialized thesis.md, and the thesis-quality checklist. Refuses creation while the workspace constitution is unratified (spec 046 Q83 A+).
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。
The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrong_if, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human structured questions WITH options (max 5 per round), encode the answers back into spec.md's Clarifications section, and re-evaluate checklists/thesis-quality.md after every write (Q32 bidirectional maintenance).
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 research tasks — checklist soft gate, phase dispatch with explicit thesis_dir, budget enforcement (halt + approval card on overrun), skill_pin recording (version_hash content-hashed per skill directory), [x] written on completion.
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。