'stability' 검색 결과

Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs covalent inhibitors and warheads targeting cysteine, lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Quantify homologous recombination deficiency (HRD) from tumor copy number using the three genomic-scar metrics — loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (TAI) — with scarHRD, and via the whole-genome HRDetect and CHORD models. Covers the genomic instability score, the PARP-inhibitor clinical context, whole-genome-doubling correction, and the scar-versus-state distinction. Use when computing an HRD score for PARP-inhibitor eligibility, deriving LOH/LST/TAI scars from allele-specific copy number, deciding between scar-based and mutational-signature HRD methods, or interpreting an HRD result in a BRCA-reverted or low-purity tumor.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Recommends RT-CGM devices for adult patients with well-controlled type 1 diabetes who are willing and able to use the devices on a nearly daily basis. Trigger phrases include 'Controlled T1DM patient interested in CGM' and 'Consider RT-CGM for glycemic stability in well-controlled T1DM'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill recommends urgent treatment (within 24–72 hours) of hypercortisolism when life‑threatening complications of Cushing's syndrome such as infection, pulmonary thromboembolism, cardiovascular events, or acute psychosis are present. Trigger phrases include sepsis, PE, chest pain with hemodynamic instability, new‑onset psychosis, or delirium in a patient with known or suspected Cushing's.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert-level plasma physics knowledge. Use when working with plasma state, Debye shielding, plasma oscillations, magnetohydrodynamics, plasma confinement, fusion plasmas, space plasmas, plasma waves, or plasma instabilities. Also use when the user mentions 'plasma', 'Debye length', 'plasma frequency', 'MHD', 'magnetic confinement', 'tokamak', 'plasma instability', 'Alfven wave', 'Langmuir probe', 'ionosphere', or 'solar wind'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Plan, write, and maintain automated tests in any language, with worked examples in Python and JavaScript/TypeScript. Use this skill whenever the user wants to write or plan tests, apply TDD (red-green-refactor), structure unit tests with arrange-act-assert and given-when-then naming, choose between fakes, stubs, and mocks, set up dependency injection for testability, build integration tests with testcontainers, database seeding, or transaction rollback, write Playwright or Cypress end-to-end tests, use property-based testing with Hypothesis or fast-check, create pytest fixtures or factory_boy factories, review coverage or mutation testing, or triage flaky tests in CI. Also trigger for "test pyramid", "test trophy", "test isolation", "mocking", "snapshot tests", "golden files", "parametrized tests", "make the tests pass".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Harness-first workflow for evaluating and improving terminal UIs through real interaction. Use this whenever the user wants to review a TUI experience, compare before/after behavior, identify UX friction, validate navigation or filtering flows, inspect visual stability, or turn observed interaction problems into concrete follow-up tests and improvement recommendations. Prefer this skill any time a TUI should be exercised through a reproducible PTY/session harness instead of only reading code.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review product designs before engineering handoff or release for flow and state coverage, business-rule alignment, implementation clarity, accessibility, responsiveness, analytics, and testability.

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.

Synthesized reference notes from three US Government vehicle-safety sources: NHTSA Cybersecurity Best Practices for the Safety of Modern Vehicles (updated 2022, final), NHTSA Automated Driving Systems 2.0: A Vision for Safety (2017), and a 16-section selection of 49 CFR Part 571 (FMVSS) pinned at eCFR versioner date 2025-01-01. Use for voluntary vehicle cybersecurity practices, the ADS 2.0 twelve priority safety design elements, and FMVSS occupant protection, brakes/stability/lighting, and fuel/EV integrity requirements. Not ISO 26262, not ASPICE, not ISO/SAE 21434, not UNECE R155/R156, not SAE J3016, and not the full Part 571; the FMVSS material is a selection of vehicle-level minimum performance standards, not a process standard.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Knowledge base from MIL-HDBK-338B (Electronic Reliability Design Handbook). Use for electronic reliability engineering: R/M/A theory, reliability specification/allocation/prediction, parts management and derating, reliable circuit and fault-tolerant design, environmental and human performance reliability, FMEA/FMECA/FTA/sneak circuit analysis, design reviews and testability, FRACAS, reliability demonstration and growth testing, and systems-level R&M parameters. Covers selected Part 2 design-guidance topics only; skips large annex/part-stress tables. Guidance handbook — not a contractual requirement text. Does not replace MIL-HDBK-217 prediction libraries, service-specific reliability regs, or safety standards (see mil-std-882).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design custom action/filter hooks emitted by a plugin: action vs filter semantics, prefixed names, docblocks, parameter stability, *_ref_array forwarding, and deprecated hook migration. Use when adding, reviewing, evolving, or deprecating a public hook surface. Triggers on do_action, apply_filters, apply_filters_deprecated, do_action_deprecated, apply_filters_ref_array, do_action_ref_array, did_action, did_filter, or hook @since docblocks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Senior Kotlin specialist code review — framework-agnostic. Use whenever the user asks to review, audit, critique, or get feedback on Kotlin code, a file, a class, a function, a module, a diff, a branch, a commit, or a pull request. Judges Kotlin language idioms, logic correctness, architecture and layering, concurrency (coroutines, Flow, structured concurrency, cancellation, race conditions), null safety, exception safety, testability, performance, and security. Detects force-unwraps, unchecked casts, GlobalScope, leaked mutability, broken structured concurrency, hidden side effects, weak abstractions, untestable seams, allocation hot spots, weak crypto, input-validation gaps, and PII logging. Outputs prioritized findings with file:line anchors and minimal-diff fixes. No assumptions about DI framework, UI framework, or build system.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Optimize a single Jetpack Compose @Composable function. Use when the user wants to improve, polish, animate, or refactor ONE Composable — keywords like "optimize this composable", "make this smoother", "add animation to this", "split this composable", "fix recomposition", "this composable is laggy", "polish this UI", or when user pastes/points to a single @Composable function. Analyzes the target for recomposition issues, missing animations, size/concern splits, and stability problems, then iterates with the user via AskUserQuestion to pick which optimizations to apply, then delegates implementation to the kta-compose-developer agent and summarizes changes. Input MUST be exactly one Composable (file path + function name, or function name alone).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when working with Aws Ecs — aWS ECS cluster health, service status, task analysis, capacity provider management, and deployment tracking. Covers service stability, task failure investigation, container insights, resource utilization, and scaling analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Ensure .NET/C# code follows maintainable, modern best practices. Use when reviewing or improving C# code, solution structure, async patterns, dependency injection, or testability.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

When the user wants to monitor, triage, or reduce their app's crash rate — including setting up Crashlytics, prioritizing which crashes to fix first, interpreting crash data, and understanding how crashes affect App Store ranking. Use when the user mentions "crash", "crashlytics", "crash rate", "ANR", "app not responding", "crash-free sessions", "crash-free users", "symbolication", "stability", "firebase crashes", "app crashing", or "crash report". For overall analytics setup, see app-analytics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.