「logic」の検索結果

CHAIN multiple existing skills into custom multi-step workflows. Programmable skill combinations with automatic handoffs. Create composite skills from building blocks with conditional logic.

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。

Applies TRIZ cross-domain analogical reasoning to find solutions from adjacent fields. Use when stuck on a problem and needing inventive perspectives.

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。

Applies CQRS and Event Sourcing for read/write separation and audit trails. Use when designing systems with complex domain logic or full state-change history.

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 checking a radiology or medical AI study design before drafting or submission. Reviews the analysis unit, cohort logic, leakage risks, comparator, validation strategy and reporting-guideline fit. AI-vs-expert benchmarks are /design-ai-benchmarking.

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 GemPy 3.x for CPU-first 3-D implicit geological modeling, structural data preparation, grid evaluation, visualization, persistence, and optional integrations.

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。

Operate ChatterBot conversational dialog engine workflows, including chatbot setup, training, logic adapters, storage backends, Django integration, and optional LLM adapters.

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 Biotite for computational molecular biology workflows: sequence analysis, structure analysis, biological database access, file-format conversion, application wrappers, and optional molecular interfaces.

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 determination of the correct lawful basis under GDPR Article 6(1)(a)-(f) for each processing activity. Includes decision tree logic for consent vs legitimate interest vs contract necessity. Activate when evaluating legal grounds for processing or reviewing lawful basis selections. Keywords: lawful basis, Article 6, consent, legitimate interest, legal obligation, contract.

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。

Builds a multi-channel DSAR intake system supporting web form, email, phone, and in-person requests with identity verification tiers, automated routing logic, SLA tracking, and response generation. Activate for DSAR intake, rights request portal, multi-channel intake, SLA tracking, request management 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。

Implements GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.

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 GDPR Article 22 rights related to solely automated decision-making and profiling, including identification of automated decisions, meaningful human oversight implementation, logic explanation requirements, and contestation mechanisms. Activate for automated decision, profiling, Art. 22, algorithmic decision, AI decision 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 generating or modifying any Spring Boot class — controllers, services, repositories, DTOs, mappers, or configuration. Enforces strict layer separation and prevents business logic from leaking across boundaries.

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。

Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.

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。

Psychological horror art direction for Blender assets inspired by Silent Hill, Resident Evil, Chilla's Art, Fear to Fathom, and Iron Lung. Use for sparse industrial environments, analog aesthetics, and tension-driven lighting.

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。

PS1/PSX-era horror art direction combining low-poly affine textures, limited color depth, fog, and psychological horror staging for Blender assets.

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。

Fetch upcoming economic events and data releases using FMP API. Retrieve scheduled central bank decisions, employment reports, inflation data, GDP releases, and other market-moving economic indicators for specified date ranges (default: next 7 days). Output chronological markdown reports with impact assessment.

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。

McKinsey-style storyline framework for building presentation decks. Use when users need to structure presentations, pitch decks, or strategic communications. Creates logical flow where each storyline becomes a slide title, progressing from problem to solution.

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。

Applies the reasoning, principles, and frameworks of Jürgen Schmidhuber (LSTM co-inventor and deep learning pioneer). Reach for this skill whenever tackling problems involving sequence learning, artificial curiosity, intrinsic motivation, reinforcement learning architectures, or predicting long-term technological and cosmic evolution. Use this when discussing AGI timelines, the history and attribution of AI breakthroughs, data compression as learning, or when designing autonomous agents that must set their own goals. Trigger this skill for topics like recurrent neural networks, algorithmic information theory, open-source AI democratization, and evaluating true existential risks versus media hype.

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。

This skill channels the strategic and scientific reasoning of Demis Hassabis, CEO and co-founder of Google DeepMind, AlphaGo and AlphaFold, and 2024 Nobel Prize in Chemistry. Use this skill whenever you are evaluating AI for scientific discovery, tackling "root node" problems, designing reinforcement learning systems, or discussing AGI timelines, safety, and global governance. Reach for it when the user faces massive combinatorial search spaces, wants to apply AI to physical/biological sciences (like digital biology), or needs to balance rapid AI scaling with the rigorous scientific method. Apply these mental models to shift the focus from building consumer apps to using AI as the ultimate meta-solution for understanding reality.

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。

Generates 20+ scroll-stopping ad hooks organized by psychological angle (pain, curiosity, social proof, contrarian, urgency) with platform-specific formatting, A/B variations, and psychology breakdowns

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。

Fix test failures when adding retry/fallback logic causes mock call count mismatches. Use when: (1) Test fails with "Expected: <1>, Actual: <2>" or similar call count errors after adding retry or fallback mechanisms, (2) MissingStubError appears for methods in new fallback code paths, (3) Mockito verify().called(N) assertions fail after behavior changes. Applies to Dart/Flutter with Mockito, but pattern is universal.

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。

Fix Node.js pg-pool not reconnecting after CloudSQL connection reset (ECONNRESET). Use when: (1) Retries fail with same ECONNRESET error despite retry logic, (2) "Connection terminated" or "connection already closed" errors persist across retries, (3) "remaining connection slots are reserved" errors in CloudSQL, (4) High-concurrency Node.js app with pg-pool and CloudSQL/managed PostgreSQL. The pool caches dead connections - you must recreate the pool, not just retry.

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。

Fix psycopg2 "could not receive data from server: Operation timed out" or "connection already closed" errors when using Cloud SQL with long-running Python scripts. Use when: (1) psycopg2.OperationalError after a period of no DB activity, (2) DB connection works initially but fails after a non-DB phase (API calls, file processing, CDX scans), (3) Cloud SQL managed PostgreSQL kills idle connections. The fix is to defer DB connection opening until needed, or add reconnection logic for long-running batch processes.

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 need to display chronological events and activities.

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。