'efficiency' 검색 결과

[omh] Run efficiency and context usage report: report supplied local run efficiency while provider data stays unobserved. Use when the user says: run-efficiency, run efficiency report, local run efficiency, context utilization, tool duration report, 실행 효율 리포트, 컨텍스트 사용량, 도구 지연 시간.

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Analyze SaaS sales opportunities, revenue forecast errors, and sales and marketing efficiency. Generates reports on stalled deals, pipeline risks, prediction bias, and customer acquisition economics for weekly sales reviews and quarterly business assessments.

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• Reviewing weekly sales coverage and stalled opportunities
• Finding dependence on a few large deals
• Comparing revenue forecasts with actual results over time

Evaluate SaaS customer economics and cash efficiency using acquisition costs, customer lifetime value, margins, and payback periods. Compare segments and channels, estimate how long cash will last, and assess whether to expand spending or improve efficiency.

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• Reviewing customer economics before increasing paid acquisition
• Comparing acquisition costs and payback across channels
• Estimating cash runway and funding needs

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Evaluates sales efficiency with CAC payback, sales cycle analysis, channel economics, and pipeline conversion metrics. Use when assessing GTM efficiency, analyzing sales productivity, or evaluating distribution strategy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Evaluates capital efficiency with burn multiple, net new ARR per dollar burned, and path to profitability analysis. Use when analyzing burn efficiency, assessing capital needs, or modeling runway scenarios.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 (Mathis 2023/2024) for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2 / PE3 / PE3b / PEmax / PEAR variants, MOSAIC in situ saturation mutagenesis (Hsu JY et al 2024 bioRxiv), the PRIME pooled-screen methodology (Erwood/Doman 2023 Nat Biotechnol 41:885; ~3,699 ClinVar variant screens), chromatin context as a primary determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 (Mathis 2023/2024) for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2 / PE3 / PE3b / PEmax / PEAR variants, MOSAIC in situ saturation mutagenesis (Hsu JY et al 2024 bioRxiv), the PRIME pooled-screen methodology (Erwood/Doman 2023 Nat Biotechnol 41:885; ~3,699 ClinVar variant screens), chromatin context as a primary determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

REA의 CI와 테스트 모음을 조사하여 결함을 놓치는 판정과 테스트 데이터의 차이를 검증합니다. 필요한 검출 능력을 유지하면서 실측을 바탕으로 실행 비용도 검토합니다.

• 결함을 놓치는 CI 판정 조사
• 테스트 데이터와 현재 사양의 차이 확인
• 느린 테스트 모음의 불필요한 비용 측정

Review recent code changes from four angles: reuse, quality, efficiency, and whether fixes address underlying mechanisms. Combine findings, apply suitable cleanup with tests, and leave changes that could affect behavior for human review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cleaning up recent code changes
• Finding duplicated logic and reusable helpers
• Reviewing efficiency in the last commit

Create agents that learn from interactions and adapt their behavior over time. Monitor learning progress, review efficiency and accuracy metrics, trigger adjustments from feedback, and share acquired knowledge with other agents through dedicated tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create an agent with initial learning settings
• Monitor learning progress, efficiency, and accuracy
• Adjust agent behavior based on feedback

Review changed code from four angles: reuse, simplicity, efficiency, and whether fixes address the underlying mechanism. Applies suitable improvements within the reviewed scope while preserving intended behavior, and reports fixes or skipped findings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clean up code changes before committing
• Replace duplicated logic with existing helpers
• Reduce redundant computation and repeated I/O

Guide Angular development, code review, and refactoring with prioritized performance rules. Review rendering efficiency, loading time, and bundle size—the amount of code delivered to browsers—alongside data fetching and server-rendered page setup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Writing Angular components with performance in mind
• Reviewing code for performance bottlenecks
• Reducing bundle size and loading time

Choose and track startup metrics suited to the business model and funding stage. Calculate customer acquisition cost, customer lifetime value, retention, and cash usage, then organize trends and targets for operational reviews and investor reporting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose core metrics for a startup's stage and business model
• Calculate customer acquisition cost and lifetime value
• Review retention, growth efficiency, and cash usage

Audit GitHub Actions workflows and run history to identify wasted automated checks and runner time. Get up to three evidence-based improvements aimed at reducing runtime or cost while preserving required validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate long GitHub Actions runs
• Review CI costs and unnecessary workflow runs
• Improve caching and cancellation of overlapping runs

Audit GitHub Codespaces startup time and spending, then identify up to three evidence-based improvements to development containers, machine sizes, prebuilds, or idle timeouts, with validation results and expected impact.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating slow Codespaces startup
• Reviewing Codespaces spending
• Trimming unused development container components

Configure large language model training with NVIDIA Megatron-Core across multiple GPUs. This skill helps choose how to split computation, set training parameters, monitor GPU efficiency, and address memory limits or unstable training.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning multi-GPU training for a LLaMA-style model
• Distributing MoE model experts across GPUs
• Tuning training throughput and GPU utilization

Turn company strategy into operational plans through process design, OKRs—objectives paired with measurable results—and regular reviews. Produce bottleneck analyses, efficiency scorecards, meeting schedules, and readiness reports for teams preparing to grow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connecting company goals to department and team OKRs
• Finding process bottlenecks and planning improvements
• Assessing operational readiness for team growth

Review and simplify code while preserving its behavior. Check readability, reuse, and efficiency, assess whether tests and comments add value, and verify applied changes with the project's configured checks before review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cleaning up code after implementation
• Improving readability before code review
• Auditing tests for practical value

Assess SaaS business health across growth, customer retention, profitability per customer, and cash efficiency. Use available metrics to build a stage-aware scorecard, identify warning signs, and prioritize improvements for business reviews or fundraising preparation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a business health scorecard for a board meeting
• Prioritizing improvements during a quarterly business review
• Reviewing business metrics before fundraising

Review a git diff or explicit file scope for reuse, code quality, efficiency, clarity, and standards issues, then optionally apply safe Codex-driven fixes. Use when the user asks to "simplify code", "review changed code", "check for code reuse", "review code quality", "review efficiency", "simplify changes", "clean up code", "refactor changes", or "run simplify".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes base editing and prime editing outcomes including editing efficiency, bystander edits, and indel frequencies. Use when quantifying CRISPR base editor results, comparing ABE vs CBE efficiency, or assessing prime editing fidelity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiments to assess editing efficiency.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.