'strategies' 검색 결과

Meta-cognitive and practical strategies for learning any language -- learner autonomy, goal setting, strategy taxonomy (Oxford's SILL framework), memory strategies, cognitive strategies (note-taking, summarizing, analyzing, reasoning), compensation strategies, metacognitive strategies (planning, monitoring, evaluating), affective strategies (managing anxiety, self-encouragement), social strategies (collaboration, questioning, empathy), immersion design, study habit optimization, plateau diagnosis, and motivation maintenance. Use when designing a language learning plan, diagnosing a learner's stuck points, selecting study methods, or building self-directed learning skills.

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Design backtests that evaluate trading strategies against historical data. Account for trading costs, avoid using future information or excluding delisted securities, and compare strategies using separate development and evaluation periods.

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• Build a backtesting system for trading strategies
• Check for bias in historical performance estimates
• Compare strategies after accounting for trading costs

Use when you need to apply testing strategies for Java code — RIGHT-BICEP to guide test creation, A-TRIP for test quality characteristics, or CORRECT for verifying boundary conditions. This should trigger for requests such as Review Java code for testing strategies; Apply RIGHT-BICEP testing strategies in Java code; Apply A-TRIP testing strategies in Java code; Apply CORRECT boundary condition verification in Java code. Part of Plinth Toolkit

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Browse registered trading strategies and compare evidence from backtests, which simulate trades on historical data. Filter by market conditions, trade counts, risk-adjusted returns, and cost feasibility, inspect evidence age, and rebuild the evidence cache from local runs.

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• Browsing registered trading strategies
• Finding strategies with evidence for falling or rising markets
• Checking a strategy's evidence quality and age

Analyze Google Ads campaign history, conversion volume, and budgets to choose suitable bidding strategies for each campaign. Get recommended targets, reasons for each choice, and a transition plan covering timing and short-term risks.

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• Choose bidding strategies for a newly managed account
• Review campaign bidding strategies each quarter
• Reassess bidding after conversion volume changes

Turn trading rules into Python code and configuration files, then test them against historical data. Review performance, position sizing, and trading costs, and revise strategies using the results produced by the backtest engine.

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• Building and backtesting a trading strategy from rules
• Revising strategies based on backtest results
• Testing stock and cryptocurrency portfolios together

Analyze the volatility implied by option prices across strike prices and expiration dates. Compare calendar spreads and other volatility strategies, then assess portfolio risk using Greeks, measures of how option values respond to market changes.

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• Compare implied volatility across strikes and expiration dates
• Evaluate calendar spread strategies
• Review portfolio risk using Greeks

Use investor psychology to examine trading signals and risk controls, especially in China A-shares. The skill provides sentiment measures, checklists for biased decisions, and frameworks for assessing momentum, which follows trends, and reversal strategies.

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• Reviewing market optimism and fear
• Examining momentum and reversal strategies
• Checking investment decisions for cognitive biases

Develop cryptocurrency trading bots with Hummingbot documentation and code examples. Explore exchange connections, price and order book data, and strategies such as market making, which places buy and sell orders, or arbitrage across markets.

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• Developing a cryptocurrency trading bot
• Exploring market making and arbitrage strategies
• Checking exchange connection settings

Extract YouTube transcripts and analyze messaging, structure, intended viewers, emotional appeal, credibility, and calls to action—requests for viewers to act. Analyze one video or compare several keyword-selected videos to identify recurring strategies and content gaps.

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• Compare competitors' video content strategies
• Research intended viewers and their problems
• Identify topics competitors have not covered

Options trade execution, directional strategies long call covered call collar, spread strategies bull call bear put ratio ladder, volatility strategies straddle strangle strap strip, liquidity cost and implied volatility filters, integration with gold.technical_setups for options setup matching

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Builds regime detection models with hidden Markov, threshold, and Bayesian change-point methodologies for strategy adaptation. Use when modeling regime changes, detecting market shifts, or adapting strategies to market conditions.

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Constructs stat arb strategies with pair selection, signal generation, and portfolio optimization under market neutrality constraints. Use when building stat arb models, designing market-neutral strategies, or optimizing pair portfolios.

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Knowledge base from the NASA Fault Management Handbook (NASA-HDBK-1002, Draft 2, April 2012). Use for the systems-engineering discipline of designing what a system does when it fails — the fault/failure/anomaly vocabulary, the five FM strategies (two prevention strategies — design-time fault avoidance and operational failure avoidance — plus three tolerance strategies — failure masking, failure recovery, and goal change), the six FM process activities across NASA mission phases Pre-A to E, response-latency-versus-time-to-criticality (TTC) design trades, fault/failure containment regions and FEPPs, the four redundancy approaches, top-down FM requirements development, FM verification vs. validation, the seven dedicated FM milestone reviews (FMCR/FMARR/FMPDR/FMCDR/FMTRR/FMLRR/FMCERR), FM organizational structure, and mined NASA Lessons Learned. Space-mission oriented (flight/ground/operations); spacecraft examples throughout. IMPORTANT: built from an UNAPPROVED DRAFT — several sections (detailed architecture building blocks, the Assessment & Analysis guidance, and Operations & Maintenance) are placeholders in the source and are thin here. Thin on detailed FDIR algorithms, terrestrial/IT fault management, and any approved-standard terminology that may have changed since Draft 2.

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공장과 사무실의 사용량, 요금 체계, 계약 조건을 바탕으로 전력과 천연가스 조달을 검토합니다. 공급업체 비교, 최대 수요 요금 대책, 재생에너지 계약 평가와 예산 수립을 지원합니다.

• 여러 사업장의 에너지 견적 비교
• 요금제와 최대 수요 요금 검토
• 재생에너지 계약과 인증서 평가

웹 앱의 운영 환경 배포 절차와 점검 항목을 정리합니다. CI/CD 자동화, Docker 컨테이너화, 상태 확인과 롤백 계획을 다룹니다.

• 테스트와 배포 자동화
• 앱의 Docker 컨테이너화
• 운영 환경 배포 방식 선택

AI 에이전트의 작업 결과와 상황을 기록하고 과거 경험으로 다음 방법을 선택하는 기능을 구현합니다. 성공과 실패 패턴 대조, 전략 비교, 학습 효과 확인도 다룹니다.

• 과거 결과로 작업 방법 선택
• 코드 리뷰와 버그 수정 전략 비교
• 현재 상황과 학습한 패턴 대조

여러 AI 서비스와 모델을 하나의 모델 ID로 묶고, 19가지 라우팅 방식과 장애 시 전환 순서를 설정하며 선택 결과와 응답 시간, 성공률, 비용을 확인합니다.

• 하나의 모델 ID로 여러 AI 모델 사용
• 장애 시 모델 전환 순서 설정
• API 호출 전 라우팅 결과 확인

Find marketing ideas for a SaaS or software product based on its stage, audience, budget, and team. Draw from 139 ideas to shortlist relevant options, with starting steps, expected outcomes, and resources needed.

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• Finding new ways to promote a software product
• Choosing marketing tactics on a limited budget
• Exploring promotion ideas before launch

Helps plan and implement database structure changes and data transformations using Sequelize, TypeORM, or Prisma. Includes staged changes intended to avoid downtime, plus transaction and backup examples for rolling back failed migrations.

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• Renaming database columns in stages
• Splitting stored addresses into separate fields
• Preparing rollback steps for failed migrations

Choose embedding models, which represent text as numerical vectors, for meaning-based search and RAG applications. Compare options for code, prose, and multilingual content, and plan document splitting, preprocessing, caching, and dimension reduction to improve retrieval quality.

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• Choosing an embedding model for RAG
• Reviewing document chunk size and boundaries
• Planning code or specialist document search

Organize complex work for a team of AI agents by splitting tasks, defining dependencies, and documenting ownership and completion criteria. Provides strategies for tracking progress, spotting blockers, and redistributing work when workloads become uneven.

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• Splitting complex work among multiple AI agents
• Mapping dependencies and execution order
• Defining file ownership and acceptance criteria

Design CI/CD pipelines that move applications through development, staging, and production. Define approval and security checks, gradual release strategies, health checks, and rollback procedures, and investigate gates or deployments that fail to progress.

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• Designing CI/CD pipelines across multiple environments
• Introducing canary or blue-green releases
• Investigating stalled approvals and release gates

Organize feature development across multiple agents by dividing work, assigning one owner per file, and agreeing on interfaces before implementation. Provides strategies for shared files, branches, and integration so agents can build separate parts of the same system.

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• Dividing a large feature among multiple agents
• Assigning file ownership to avoid conflicting edits
• Agreeing on APIs before parallel implementation