'observation' 검색 결과

로컬 claude-mem의 작동 상태와 중요 기록 캐시를 점검합니다. 기록을 제외하거나 복원하고 계층 간 규칙 충돌을 보고하는 정기 운영용 스킬입니다.

• 작동 상태와 중요 기록 캐시를 갱신할 때
• 원본 이력을 보존하며 기록을 제외할 때
• 제외한 기록을 복원할 때

Refactor large SwiftUI screens into smaller views with clear inputs and state ownership. Organize actions, shared dependencies, and observable models while preserving existing layout and behavior, making the code easier to read and test.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Split a large SwiftUI screen into smaller views
• Clarify state ownership and data flow
• Move business logic out of the view body

Grok Bot의 claude-mem에서 완료한 작업을 검색 가능한 XML 기록으로 정리합니다. 대기나 초기화처럼 기록이 필요 없는 상태는 별도 표시로 구분합니다.

• 완료한 작업을 검색용으로 기록할 때
• 대기 상태와 기록할 작업을 구분할 때
• claude-mem의 기록 형식을 통일할 때

Review SOC 2 Type II audit readiness through six questions about controls, the organizational safeguards assessed over an observation period. Identify evidence gaps, control changes, and exceptions, then organize readiness findings and three concrete next actions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check readiness before the observation period begins
• Review control operation midway through the period
• Check evidence coverage before audit fieldwork

Turn observations or preliminary data into competing scientific hypotheses grounded in literature. Develop explanations, assess what could disprove them, and produce testable predictions and experimental designs in a structured report with diagrams.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Develop hypotheses from observations or preliminary data
• Compare competing explanations for a phenomenon
• Define predictions that could disprove a hypothesis

Build testable scientific hypotheses from observations or preliminary data. Compare competing explanations against published evidence, define measurable predictions, and propose experiments, then organize the findings into a research report with diagrams and detailed supporting material.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Develop testable hypotheses from preliminary observations
• Compare competing explanations using published research
• Plan experiments that distinguish between hypotheses

Capture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations or user-supplied traces/transcripts; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Plugin observation capture/review require either the Codex skill-up plugin or an observer-enabled DSH skill-up plugin. User-supplied external evidence can be reviewed without a plugin; evaluation remains multi-engine.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design a focused lesson observation protocol with specific look-fors and evidence collection methods. Use when planning peer observations, coaching visits, or developmental classroom visits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design a focused lesson observation protocol with specific look-fors and evidence collection methods. Use when planning peer observations, coaching visits, or developmental classroom visits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guide a person in systematic observation of systems, patterns, or phenomena. AI coaches neutral attention, field notes methodology, pattern recognition, hypothesis formation, and structured reporting for debugging, research, and system understanding. Use when a person wants to understand a system's behavior before intervening, when someone keeps jumping to conclusions and needs the discipline of observation first, when preparing an evidence-based report, or when studying team dynamics or process effectiveness through direct observation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Caveman 관측 보고서를 바탕으로 사용자가 선택한 대상의 최소 코드 변경을 검토합니다. 승인 후 동일한 입력으로 변경 전후의 품질과 자원 사용량을 비교합니다.

• Caveman 관측 보고서 검토
• 변경 전후 토큰 수와 바이트 수 비교
• 최적화 후 품질 유지 여부 확인

claude-mem 작업 기록을 주제, 기간, 파일별로 골라 목적에 맞는 지식 기반을 만듭니다. 대화를 통해 과거의 판단과 수정 이력을 질문할 수 있습니다.

• 특정 기술 주제의 지식을 모을 때
• 지정한 기간의 판단을 돌아볼 때
• 서비스 수정 이력을 대화로 확인할 때

Combine laboratory animal welfare measurements into reference-relative RELSA severity scores. Analyze individual trajectories, explore forecasts for specified observation times, and derive candidate score zones, with explicit checks on normalization, reference selection, prediction intervals, and evaluation limits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Combine animal welfare measurements into daily scores
• Compare group severity using a shared reference
• Explore severity forecasts at specified observation times

Turn observations or preliminary findings into testable research plans. The skill separates candidate hypotheses from evidence, develops competing explanations and distinguishing predictions, and helps specify measurements and analysis plans for preregistration, a research plan recorded before testing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn an observation into testable research hypotheses
• Compare competing explanations and distinguishing predictions
• Define measurements and review an analysis plan

Understand how agentmemory automatically records tool activity, prompts, and session boundaries through hooks, actions triggered by session events. Use it to check integration setup, investigate missing records, and distinguish capture from optional summaries and context injection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understanding automatic session recording
• Investigating missing observations
• Checking capture and summary settings

Summarize recent agent sessions for the current project, grouped by date with highlights from recorded observations. Review today, the last seven days, or a chosen number of sessions, with totals for sessions, days, and observations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review today's agent work
• Recap project activity from the last seven days
• Summarize a chosen number of recent sessions

Plan and analyze A/B tests, prepare tabular data, and train and evaluate prediction models. Estimate intervention effects from observational data, track model experiments with MLflow, and translate statistical findings into business decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning A/B test sample sizes and analyzing results
• Preparing tabular data for prediction models
• Comparing model performance and recording experiments

Turn enterprise red-team findings into client-facing reports with clear observations, business impact, remediation, and reproducible evidence. The skill provides report structure, severity and status guidance, and a Markdown-to-DOCX workflow with embedded screenshots and delivery checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing final enterprise red-team reports
• Explaining findings to technical and business readers
• Packaging screenshots and evidence into DOCX

Plan interviews and focus groups for qualitative research, which explores people’s experiences and views. Develop question guides, follow-up prompts, discussion plans, transcription conventions, and participant review procedures suited to the study.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a semi-structured interview guide
• Planning focus group discussions
• Choosing transcription conventions

Turn observations or preliminary data into competing scientific hypotheses grounded in literature. It compares explanations, evaluates how they could be tested or disproved, and proposes experiments and measurable predictions in a structured report with diagrams.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Developing hypotheses from preliminary observations
• Comparing competing explanations for a phenomenon
• Planning experiments to distinguish hypotheses

Capture ideas for videos, articles, businesses, and small projects in separate files, with entry numbers and source details. The skill commits and pushes the additions to a Git repository for later review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving video and article ideas
• Recording observations and hypotheses
• Collecting startup and small project ideas

Refactor SwiftUI screens into smaller view types while preserving layout and behavior. Organize state, dependencies, and actions, and check that observable models use the appropriate state wrappers for the app’s supported iOS versions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Split a long SwiftUI screen into smaller views
• Move actions and business logic out of the view body
• Review observable state and model initialization

Analyze how long events take to occur, including records where observation ends before the event. Use Python to prepare data, fit and compare survival models, and evaluate predictions with measures suited to incomplete observations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Analyze time to events with incomplete observations
• Compare Cox models and Random Survival Forests
• Select features in datasets with many variables

Develop testable scientific hypotheses from observations, preliminary data, and published evidence. The skill compares competing explanations, defines measurable predictions, proposes experiments, and organizes evidence and decision criteria into a structured research report.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Developing hypotheses from preliminary data
• Comparing competing explanations for a phenomenon
• Designing experiments to distinguish hypotheses