「diagnostic」の検索結果

Think and work like an expert Atmospheric Scientist. Use when a task calls for Atmospheric Scientist judgment. Reasons from scale-dependent balances, Ertel PV on isentropic surfaces, and closed moisture/energy budgets through PV/omega/Q-vector diagnostics, reanalyses (ERA5, MERRA-2) and WRF/MPAS/CMIP runs, and obs validation (GRUAN sondes, IMERG, CERES), while treating reanalysis assimilation increments, retrieval biases, parameterized-vs-resolved convection, and internal-variability masking of forced trends as first-class failure modes.

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Build forest plots (HR, OR, RR, beta-coefficient summaries with CIs) and funnel plots (meta-analysis publication-bias diagnostics) using forestplot, metafor, ggforest, and MendelianRandomization with proper axis-scaling, summary-diamond placement, subgroup nesting, and Egger / trim-and-fill asymmetry tests. Use when summarizing effects across subgroups, trials, or instruments — meta-analysis, Mendelian randomization, subgroup HRs.

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Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the p53-dependent G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-frequency tables; and failure modes from amplicon misalignment or contamination. Use when quantifying editing from amplicon sequencing, choosing CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.

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Clinical variant interpretation using ClinVar, ACMG guidelines, and pathogenicity predictors. Prioritize variants for diagnostic and research applications. Use when interpreting clinical significance of variants.

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Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.

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Analyzes base-editing screens for variant function. Covers library design (Sanson 2020 GRACE, Hanna 2021 BRCA1/2 SNV scanning, Cuella-Martin 2021), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end, wider for ABE8e), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.

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Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.

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End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, classifier training with nested CV, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.

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Run Bayesian phylogenetic analysis with MrBayes, BEAST2, RevBayes, and PhyloBayes including MCMC convergence diagnostics and model comparison. Use when needing posterior probability support, Bayesian model averaging, site-heterogeneous models for deep phylogenies, or formal model comparison via stepping-stone sampling.

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Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

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codeck entry point. Scans local files for materials, shows pipeline dashboard with diagnostic intelligence, guides user to the next step. Use when the user says "codeck", "new deck", "make a presentation", "make a deck", "new slides", "build a presentation", "export", "speech", "script", or wants to start or continue a presentation project. /codeck is the user-facing entry; legacy sub-skills are internal modules.

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Run the konsistent CLI, review all reported violations, and fix them in the codebase. Use when the user wants to "fix konsistent violations", "resolve konsistent errors", "clean up konsistent diagnostics", "make konsistent pass", "address structural convention violations", or asks to run konsistent and act on the results. The skill is interactive: it requires explicit user decisions when many violations stem from the same rule (rule vs. code question), explicit user confirmation before modifying any code, and a triage step for non-trivial violations. For editing `konsistent.json`, this skill defers to the `konsistent-config` skill.

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Review EXISTING test code for quality, smells, and testability issues. Detects test smells across six dimensions — readability, reliability, diagnostic value, design, AI-generated, and coverage — analyzes testability of application code, and backs the qualitative smells with mutation testing. Use when: "review my tests," "test quality audit," "test smells," "testability analysis," "are these tests any good." Not for: generating new tests — use `ai-test-generation`. Not for: testing AI features in your product — use `ai-system-testing`. Related: unit-testing, shift-left-testing, coverage-analysis, ai-test-generation.

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You are an expert in Biome, the Rust-based toolchain that replaces ESLint and Prettier with a single, fast tool. You help developers configure linting, formatting, and import sorting for JavaScript, TypeScript, JSX, JSON, and CSS — achieving 100x faster execution than ESLint+Prettier with zero configuration, unified diagnostics, and IDE integration.

日本語の概要は準備中です。原文の説明を表示しています。

🤖 Andru.ia Solutions Architect - Hybrid Engine (v2.0) workflow skill. Use this skill when the user needs Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

🤖 Andru.ia Solutions Architect - Hybrid Engine (v2.0) workflow skill. Use this skill when the user needs Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Semantic Python code queries via a stdio LSP client driving pyright-langserver. Provides binding-resolved go-to-definition, find-references, hover types, type diagnostics, file symbol outlines, and project-wide symbol search — name resolution and type inference that tree-sitter and ripgrep cannot do. Use when you need to follow an import to a definition, find all real uses of a symbol (excluding same-named-but-unrelated ones), get an inferred type, surface type errors, outline a file, or search symbols across a project. Triggers on "go to definition", "find references", "what type is", "resolve this symbol", "symbol outline", "find symbol in project", "pyright", "type-check this file".

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Diagnose an AWF (Agentic Workflow Firewall) failure from an error, workflow run URL, or symptom. Covers auth (api-proxy, enterprise/BYOK Copilot, OIDC, mcpg), ARC/DinD and self-hosted runners, alternative runtimes (gVisor/Kata/chroot), Squid/DNS/egress denials, CI and gh-aw safe-output failures, and suspected security regressions. Routes to the canonical diagnosis registry in docs/diagnostics.

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Suede-affiliated engineering-as-marketing strategy for selecting, scoring, and scoping calculators, graders, generators, and other free interactive tools. Use when the user wants a lead, link, education, or product-adoption asset with a measurable path to the paid product. NOT FOR: downloadable lead assets (use suede-lead-magnets), implementation of a full website (use suede-site-alchemy), or search diagnostics (use suede-seo-audit).

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Generate a full operational status report for the Aivena bot. Checks all subsystems: extensions, webserver, Telegram, chat bridge, heartbeat, cron, database, memory, CRM, calendar, task management, jobs/telemetry, and storage. **Triggers — use this skill when:** - User asks for "status", "bot status", "system status", "operational status" - User asks "is everything running?", "how's Aivena doing?" - User says "health check", "diagnostics", "systems check" - User asks "what's the state of the bot?"

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CRE Capital Markets and Debt Maturity suite - 8 specialist skills for maturity diagnostics, refinance proceeds gaps, extensions, workouts, rescue capital, term sheet comparison, CMBS special servicing readiness, lender updates, and recap IC memos.

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Use only after explicit Codex `$superloopy:i-have-adhd` or Claude Code `/superloopy:i-have-adhd` invocation, or when a qualifying leading `loopy`/`루피` task receives Superloopy's non-diagnostic ADHD-friendly output overlay. Do not activate from typos, fragmented writing, urgency, grammar, language proficiency, or ordinary discussion of ADHD, attention, focus, accessibility, or cognitive load.

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Home Assistant custom integration development in Python. Covers custom_components, DataUpdateCoordinator, config_flow, OAuth2, conversation agent, HACS publishing, device registry, entity platforms, services, repair issues, diagnostics, Bluetooth integrations, and multi-coordinator patterns.

日本語の概要は準備中です。原文の説明を表示しています。