「setting」の検索結果

Apply or adapt a dual-theme soft-neumorphic UI board for dashboards, workspaces, settings panels, admin tools, and design-system previews. Use when Codex should build or restyle interface work in a tactile soft-neumorphic style with both light and dark themes, shared semantic tokens, large radii, raised surfaces, inset fields, restrained accent states, and a complete preview board covering foundations, controls, navigation, data display, and feedback.

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。

Apply or adapt a dual-theme liquid glass UI board for premium dashboards, workspace launchers, settings surfaces, design-system previews, and glossy interface concepts. Use when Codex should build or restyle interface work with frosted translucent panels, aurora glow accents, pill controls, circular glass actions, blurred color blooms, and a polished light-plus-dark material system.

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。

Apply or adapt a dual-theme neo-glow control board for UI kits, design-system previews, settings surfaces, admin panels, control rooms, and dense operational interfaces. Use when Codex should build or restyle interface work with bright white or dark control surfaces, compact neumorphic cards, vertical icon rails, blue/cyan halo accents, glowing active states, luminous toggles, and a board focused on control states, inputs, and specification details.

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。

Apply or adapt a complete dual-theme UI specification board for product interfaces. Use when Codex should build or restyle dashboard, admin, workspace, settings, or system UI with both light and dark themes, shared semantic tokens, structured component states, and a full preview board covering foundations, controls, navigation, data display, and feedback 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。

Check and install prerequisites for the Todo app project. Use when setting up the development environment, when a user first opens the workspace, when troubleshooting missing tools, or when the user mentions setup, install, prerequisites, or environment.

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。

Look up how Claude Code itself works — hooks, skills, subagents, MCP, plugins, settings — from the official docs, so answers come from the current spec instead of memory.

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。

Use when building Grafana dashboards backed by Prometheus, Loki, or Tempo, designing PromQL/LogQL queries, wiring template variables, setting alert rules, building SLO dashboards, or maintaining dashboards as code. Triggers: rate() vs increase() confusion, irate vs rate, label_replace, recording rules, alerting rule expressions, multi-dimensional template variables, ad-hoc filters, dashboard JSON model, provisioning via Terraform/grafonnet, p99 / histogram_quantile usage. NOT for Datadog/New Relic dashboards (vendor-specific), Grafana plugin development, or Loki ingestion pipeline tuning.

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。

Schema design, normalization decisions, indexing strategies, and migration safety for relational databases. Use when designing tables, choosing between normalize vs denormalize, selecting index types, planning zero-downtime migrations, or setting up connection pooling. Activate on "schema design", "normalization", "denormalization", "foreign key", "index strategy", "migration", "connection pooling", "composite key", "surrogate key", "soft delete", "polymorphic association". NOT for PostgreSQL-specific query tuning or EXPLAIN analysis (use postgresql-optimization), NoSQL or document database design, or cloud database provisioning.

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Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.

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。

Cloudflare Workers, KV, Durable Objects, and edge computing development. Use for serverless APIs, caching, rate limiting, real-time features. Activate on "Workers", "KV", "Durable Objects", "wrangler", "edge function", "Cloudflare". NOT for Cloudflare Pages configuration (use deployment docs), DNS management, or general CDN settings.

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。

Filter and select sequences by criteria (length, ID, GC content, N content, motifs, patterns, description) using Biopython, streaming so large files never load into RAM. Use when subsetting a FASTA/FASTQ file, removing unwanted or low-quality records, or selecting records by specific criteria. Use the paired-end-fastq skill instead whenever the input is paired R1/R2 reads.

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。

Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

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。

Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.

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Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.

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。

Generate consensus FASTA sequences by applying VCF variants onto a reference with bcftools consensus, or build viral/amplicon consensus with iVar. Use when reconstructing a sample-specific reference or haplotype, deciding -H haplotype vs IUPAC vs all-ALT projection, masking no-coverage sites so a consensus does not manufacture false reference calls, or setting iVar min-depth/min-frequency policy for surveillance genomes.

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。

Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.

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。

Define database models with clear naming, appropriate data types, constraints, relationships, and validation at multiple layers. Use this skill when creating or modifying database model files, ORM classes, schema definitions, or data model relationships. Apply when working with model files (e.g., models.py, models/, ActiveRecord classes, Prisma schema, Sequelize models), defining table structures, setting up foreign keys and relationships, configuring cascade behaviors, implementing model validations, adding timestamps, or working with database constraints (NOT NULL, UNIQUE, foreign keys). Use for any task involving data integrity enforcement, relationship definitions, or model-level data validation.

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。

Implement authentication and authorization with Better Auth - a framework-agnostic TypeScript authentication framework. Features include email/password authentication with verification, OAuth providers (Google, GitHub, Discord, etc.), two-factor authentication (TOTP, SMS), passkeys/WebAuthn support, session management, role-based access control (RBAC), rate limiting, and database adapters. Use when adding authentication to applications, implementing OAuth flows, setting up 2FA/MFA, managing user sessions, configuring authorization rules, or building secure authentication systems for web applications.

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。

Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.

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。

Assess whether a hospitalized adult with diabetes on insulin pump therapy remains a candidate for continued inpatient pump use. Consider triggers such as the clinician asking "Is this patient appropriate to continue insulin pump in hospital?" and evaluate for impaired consciousness, inability to adjust pump settings, critical illness, DKA, or hyperosmolar hyperglycemic state.

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Assesses that CGM low- and high-glucose alarm thresholds are individualized to optimize patient benefit and minimize alarm fatigue. Triggered by clinician prompts to 'Review low-glucose alarm thresholds' or 'Ensure alarms are individualized and not excessive'.

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。

Assesses a patient’s ability to operate an insulin pump and make setting changes, evaluating dexterity, vision, mental health, and cognition for independent or assisted use. Triggered by phrases such as 'Check patient can manipulate pump controls' and 'Evaluate dexterity and vision for pump use'.

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。

This skill directs lifelong treatment of cardiovascular risk factors, osteoporosis, and psychiatric symptoms in all patients with Cushing's syndrome until biochemical resolution of hypercortisolism. Use when managing any CS patient for long‑term comorbidity control; triggers include persistent hypertension, dyslipidemia, low bone density, depression, anxiety, or cognitive changes in the setting of known or suspected CS.

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。

Recommends ACTH stimulation during AVS to improve success rate of bilateral selective catheterization, acknowledging unclear impact on diagnostic accuracy for laterality. Triggers include when setting up AVS and asking 'Should I administer ACTH?' or considering procedural optimization.

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。