'baseline' 검색 결과

Bootstrap the central system spec at `docs/system/` for a repository that has never had one. Scans the governed surface, proposes a concept map clustered by directory, and materializes elements + shards ONLY after a human confirms that map. Use when adopting the baseline on an existing project, or when the corpus needs re-deriving from scratch. Re-runnable. Requires `memory.architecture_map.enabled` and a declared `governed_surface`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run an org-team workflow — a flat pod of up to four peer Claude Code sessions claims lane-tagged slices of an approved spec over the baseline MCP channel and implements them concurrently, each in its own git worktree. Each peer DECIDES its own in-lane implementation choices in its own main context (Article X); only un-decidable or cross-lane forks escalate peer→lead→human (yield_fork for task-bound forks, ask_lead for free-form queries). Opt-in and OFF by default (velocity.org_mode.enabled). Graduates the retired sprint-dispatch prototype into the constitutionally-sanctioned org-team model (Article X — Multi-session coordinated workflows). Requires git.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build editorial/magazine/report webpages on a GENUINE Müller-Brockmann modular grid (International Typographic Style). Encodes the discipline (columns + modules + baseline, grotesque type, flush-left, restrained black/white/red palette) AND the front-end engineering to make the grid real, visible, and verified: one CSS-variable source of truth, an interactive grid-toggle overlay, subgrid bands, 8px baseline lock, and runtime optical alignment. Triggers: "magazine spread", "grid system", "Swiss design", "editorial layout", "show the grid", "align everything to the grid".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Audit ClawJS/Clawix code hygiene without editing code, producing categorized findings, baseline status, and validation evidence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run or change the macOS UX trace harness for action-to-visual-completion latency, scroll stability, fixture pressure, and baseline evidence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Run and interpret Clawix UI geometry, screenshot, protected-surface, and debt-baseline checks without authorizing visual repair.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Knowledge base from NIST SP 800-37 Revision 2, the Risk Management Framework (RMF) for information systems and organizations. Use for the seven RMF steps (Prepare, Categorize, Select, Implement, Assess, Authorize, Monitor) and their tasks; the three-tier organization-wide risk model; authorization boundaries; the requirements-to-controls relationship; security categorization (FIPS 199/200 high-water mark) and control selection/tailoring (SP 800-53/53B baselines); assessment, the authorization decision and risk acceptance, continuous monitoring and ongoing authorization; the security/privacy distinction; and supply chain risk management. This is the security-and-privacy-risk-governance edge of systems engineering — it governs how much protection and whether to accept residual risk, complementing the disciplines that decide how protection is built. Does NOT reproduce the SP 800-53 control catalog or its baselines, the FIPS impact tables, or the ISO/IEC/IEEE 15288 process text; it names and routes to them rather than restating them.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Knowledge base from the GAO Schedule Assessment Guide (GAO-16-89G, 2015). Use for building, assessing, or auditing a program's integrated master schedule (IMS): the ten best practices of a reliable schedule (capture, sequence, resource, duration, traceability, valid critical path, reasonable total float, schedule risk analysis, updating, baseline), the four characteristics (comprehensive, well-constructed, credible, controlled), critical path method arithmetic (forward/backward pass, total float), schedule risk analysis (Monte Carlo, contingency), statusing and baseline control, and the Appendix II audit triad. Scheduling/time-management oriented: it is the authority on schedule reliability, but it is NOT a cost-estimating guide, a full SE process model, an agile guide, or a risk-management framework — see sibling packs (gao-cost, dau-se-guidebook, nasa-schedule, nasa-risk) for those.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Establish build performance baselines and apply systematic optimization techniques. Only activate in MSBuild/.NET build context. USE FOR: diagnosing slow builds, establishing before/after measurements (cold, warm, no-op scenarios), applying optimization strategies like MSBuild Server, static graph builds, artifacts output, and dependency graph trimming. Start here before diving into build-perf-diagnostics, incremental-build, or build-parallelism. DO NOT USE FOR: non-MSBuild build systems, detailed bottleneck analysis (use build-perf-diagnostics after baselining).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

検査器（linter / ガード / CI ゲート / バリデータ / フィルタ）そのものの検出力が差分で静かに落ちていないか、また新設した検査が実際に検出できることが実証されているかを diff-time で検出する。Check 1 unverified detection reduction（検査器の検出ロジック（正規表現・除外パターン・解決集合・allowlist・baseline）を変更して検出件数が減ったのに、減った 1 件ずつが誤検出であった根拠が示されないまま「誤検出を潰した」「N → M 件に減少」と改善として主張している）、Check 2 unproven guard detection power（新しい検査ロジック・CI ゲート・バリデーションを追加・変更したのに、検出すべき入力を注入して検出されること／検出すべきでない入力で黙ることを示す変異注入の証跡が無く、「追加した」「CI が緑」を検出力の証拠として扱っている）、の 2 Check を対象とする report-only。テスト自身のアサーションが実質何も検証していない構造は test-assertion-effectiveness、レビュー基準・品質ゲートの明示的な弱体化（ルールの削除・閾値の引き下げ・suppression entry 追加・lint ルールの無効化）は review-criteria-integrity、リファクタ完了主張一般の検証は refactor-claim-audit、workflow の permissions と action pin は gha-workflow-security、設定ファイルの構文・型の妥当性は config-json へ委譲する

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Review board (Busabase App-in-Skill) that runs a fixed suite of mock test cases against a baseline vs candidate agent version and surfaces rubric-scored regressions before a release. Use when the user invokes $kelly-agent-eval or /kelly-agent-eval, wants to review agent-version regressions, compare baseline vs candidate quality, triage a release, or record a release approve/block decision. Deterministic mock rubric scores only — not a real LLM-judge call, and it never deploys anything.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Signals scout that watches a PostHog project's most-viewed dashboards and insights for recent anomalies — sudden bursts, drops, flat-lines, and trend breaks at the daily or hourly level. It discovers what the team actually looks at (view counts, dashboard access), curates a durable watchlist in the scratchpad, and balances re-checking known high-value insights (exploit) against discovering new ones (explore) across runs, since no single run can cover a busy project. Anomalies are scored by robust deviation from each insight's own seasonality-matched baseline; it emits a finding only when a move clears the confidence bar, otherwise it updates the baseline memory and closes out empty. Self-contained peer in the signals-scout-* fleet.

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Rigorous methodology for evaluating ML models on established benchmarks. Covers proper train/val/test splits, baseline verification from original papers, exact metric formula discrepancies, data-leak detection checklist, multi-seed robustness, and honest reporting templates. Use when claiming to beat published baselines, writing methods papers, or auditing existing results.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Simulate transcription factor perturbation effects on cell state in silico with CellOracle and Dynamo, and predict transcriptional responses to genetic perturbations with GEARS, scGen, and CPA. Covers the direction-not-magnitude principle, local-linear validity, the GRN/velocity error it inherits, baseline discipline (mean and additive baselines), and the validation gap. Use when predicting TF knockout or overexpression effects, ranking driver TFs for fate transitions, or planning perturbation experiments. For GRN construction see multiomics-grn; for experimental Perturb-seq see single-cell/perturb-seq.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Simulate transcription factor perturbation effects on cell state in silico with CellOracle and Dynamo, and predict transcriptional responses to genetic perturbations with GEARS, scGen, and CPA. Covers the direction-not-magnitude principle, local-linear validity, the GRN/velocity error it inherits, baseline discipline (mean and additive baselines), and the validation gap. Use when predicting TF knockout or overexpression effects, ranking driver TFs for fate transitions, or planning perturbation experiments. For GRN construction see multiomics-grn; for experimental Perturb-seq see single-cell/perturb-seq.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Paces a Claude subscription's usage — how fast to spend this week, what can still run at N% weekly, whether planned work fits before a reset. Reads the 5-hour, weekly, per-model and CI-minutes meters, sets a spend mode (normal, pace, turbo, overnight, work-day, owner-away, reset-eve) and re-cuts waves that don't fit. Also when something ate usage overnight, CI minutes run low, context runs high (compact or clear?), a new model needs a measured baseline, or which skill or subagent used tokens; or say pacewright (check, mode, fit, context, uba, baseline, spend, refresh). The plan table is dispatchwright's; the handoff, handoffwright's; one artifact's cost, skillwright's slim; the meter statusline, rigwright's; a scheduled check, agentwright's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

고정된 샘플 데이터와 실제 렌더링 부품으로 OpenClaw 터미널 화면을 시제품으로 만들고, tmux에서 두 개에서 여섯 개의 안을 나란히 조작하며 비교합니다.

• 초기 설정 화면의 안을 비교합니다
• 채팅과 선택 화면의 배치를 검토합니다
• 기존 화면과 개선안을 비교합니다

Parallels 가상 머신에서 OpenClaw 설치, 초기 설정, 업데이트를 검증합니다. macOS, Windows, Linux의 기본 동작을 확인하고 실패 원인을 구분합니다.

• 세 운영체제에서 신규 설치 확인하기
• OpenClaw 업데이트 과정 검증하기
• 기존 스냅샷에서 검증 다시 시작하기

Git 기록에서 OpenClaw 릴리스 변경 내역을 다시 작성합니다. 사용자 영향별로 정리하고 Issue와 PR 참조, 기여자 표기의 누락을 검증합니다.

• stable 버전 공개 전 변경 내역 작성
• 이전 beta 배포 기준과의 차이 정리
• 기여자와 PR 참조 표기 확인

고객이나 거래처에 보낼 답장 초안을 사람의 승인과 연결하고 승인된 본문, 수신 대상, 전송 결과를 기록합니다. 오래된 승인 사용과 중복 전송을 방지하도록 설계합니다.

• 고객 답장에 사람의 승인 적용
• 승인된 본문과 전송 결과 기록
• 수정 전 승인으로 전송되는 상황 방지

배포된 URL의 페이지와 API 응답, 정적 파일, 지속 연결, 성능 저하를 점검합니다. 단일 점검, 기간을 정한 모니터링, 검증 환경과 운영 환경 비교를 지원합니다.

• 배포 후 운영 및 검증 환경 점검
• 병합이나 의존성 업데이트 후 수정 확인
• 공개 직후 사이트 지속 모니터링

공통 기준으로 코드의 명명, 가독성, 원본 데이터를 바꾸지 않는 갱신 방식과 오류 처리를 검토합니다. 중복과 복잡한 구조를 찾아 유지보수하기 쉽게 정리합니다.

• 기존 코드의 명명과 가독성 검토
• 긴 함수와 깊은 조건 분기 정리
• 새 모듈의 코딩 규칙 통일