'aria' 검색 결과

Configures environment variables for Power Pages site settings to support ALM across environments. Creates environment variable definitions in Dataverse, guides the user through linking site settings to those variables via the Power Pages Management app, adds the variables to the solution, and generates a deployment-settings.json file with per-stage override values. Use when asked to: "configure environment variables", "add env vars", "set up deployment variables", "make site settings environment-specific", "configure ALM variables", "set up env-specific settings", "add deployment settings", "configure per-environment settings".

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Use when working with icons in any project. Search 1.4M icons, add them as source files (no giant dependency), migrate existing icon libraries, and run as an MCP server. Commands: `aria-icons search`, `aria-icons add`, `aria-icons get`, `aria-icons migrate`, `aria-icons doctor`.

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Query gnomAD (Genome Aggregation Database) for population allele frequencies, gene constraint scores, and variant annotations to interpret ENCODE regulatory variants. Use when the user needs allele frequencies for variants in ENCODE regulatory elements, wants to assess gene constraint (pLI, LOEUF) for ENCODE target genes, needs population-specific frequencies for GWAS variants overlapping cCREs, wants to filter variants by rarity before functional annotation, or is interpreting ENCODE CRISPR/MPRA results in the context of population genetics. Also use when the user mentions gnomAD, allele frequency, pLI, LOEUF, constraint, rare variants, population frequency, ExAC, or variant filtering.

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Guide for annotating ENCODE regulatory variants with ClinVar clinical significance. Use when users need to check if variants in ENCODE peaks have clinical associations, find pathogenic variants in regulatory regions, or assess variant clinical impact. Trigger on: ClinVar, clinical significance, pathogenic variant, variant classification, clinical variant, disease variant, VUS, benign, likely pathogenic.

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Compare button and link text with accessible names, the names assistive technology uses for controls. Identify mismatches and suggest ARIA label changes so people using voice control can refer to the words they see.

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• Comparing visible button text with accessible names
• Reviewing links that are hard to activate by voice
• Checking label fixes with accessibility tools

Review file explorers and other expandable tree interfaces so screen reader users can identify each item. Check descriptive names and expanded states, then suggest fixes using visible text or ARIA attributes, which provide information to assistive technology.

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• Reviewing names in a file explorer
• Checking expanded states in nested navigation
• Adding descriptive labels to icon-only tree items

Check whether aria-hidden on the document body hides an entire page from screen readers, tools that read content aloud. Identify problematic states and suggest limiting hiding to specific background containers.

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• Checking accessibility when a modal opens
• Investigating why a page is missing from screen readers
• Reviewing body attributes across UI state changes

Review whether ARIA roles, which describe interface elements to assistive technology, have the required parent roles. Find misplaced menu items, tabs, or list items, suggest suitable containers, and explain how to verify the corrected structure.

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• Checking parent roles for menu items
• Reviewing tab and list structures
• Auditing design-system components

Build or update a Figma design system from existing code. Organize shared colors, spacing, and typography, create reusable components with states and theme bindings, document their use, and check differences between the implementation and Figma.

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• Building a Figma component library from existing code
• Organizing shared settings for light and dark themes
• Creating a button with variants and variable bindings

Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards. USE THIS SKILL WHEN: - You need to review or audit actuarial models (reserving, pricing, capital) - Someone asks about loss triangle analysis or reserve adequacy - You are evaluating IBNR calculations, chain ladder methods, or Bornhuetter-Ferguson - A project involves insurance pricing, GLM rating models, or ratemaking - You need to assess Solvency II SCR calculations or RBC compliance - Someone mentions actuarial opinions, ASOP compliance, or SOA standards - You are reviewing stochastic models, ESG configurations, or DFA frameworks - A codebase uses actuarial libraries (chainladder, lifetables, ChainLadder R package) TRIGGER PHRASES: "actuarial", "loss reserving", "IBNR", "chain ladder", "premium pricing", "mortality table", "Solvency II", "capital adequacy", "ratemaking", "GLM pricing", "risk-based capital", "reserve analysis", "actuarial opinion"

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Analyze budget vs. actual variances, identify root causes, and recommend corrective actions. Use when an accountant or finance professional says "explain this variance", "budget vs. actual analysis", "why did we miss budget", "favorable / unfavorable variance", "price volume variance", "management reporting commentary", "explain the P&L variance to the CFO", "what drove the cost overrun", "revenue shortfall analysis", or needs to write the narrative behind a financial result. Also trigger when someone shares a table of actuals vs. budget and needs to explain the gaps - even if they don't use the word "variance".

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標準原価差異分析スキル。標準原価（予定原価）と実際原価の差異を価格差異・数量差異に分解し、 材料費・労務費・製造間接費のカテゴリ別に集計・分析する。差異の有利/不利判定、 責任部門の特定、根本原因の仮説提示を行う。CSVデータのアップロードによる自動分析に対応。 Use when: 製造原価の差異分析を行いたいとき。標準原価計算制度の運用、 月次原価差異レポート作成、原価低減活動の効果測定に使用。 Triggers: "標準原価", "原価差異", "価格差異", "数量差異", "standard cost", "cost variance", "price variance", "quantity variance", "予定原価", "操業度差異", "原価管理"

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Turns an actuals-versus-budget extract (spreadsheet, export or pasted table) into a DRAFT variance table with absolute and percentage variances, favourable or adverse marking and a ranking by size, then drafts plain-language driver hypotheses for each material variance as questions to verify with a named owner, never as asserted causes. Use when the user asks to "explain these variances", "why are we over budget on this line", "write the variance commentary for the management pack", "actuals versus budget analysis" or "which lines drive the variance". Do not use for a dataset with no budget or comparison column, use dataset-insight-pack instead; for weekly operational figures against last week, use kpi-weekly-report-writer. Drafts for human review; never approves, authorises or signs off.

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End-to-end Coval adversarial / red-team testing workflow. Builds one adversarial test set (12 core attack vectors plus legitimate controls, each with an expected-behavior checklist), creates a persistent "Adversarial User" persona and a Composite Evaluation metric that scores each scenario against its own expected behaviors, launches a multi-iteration run against the agent (voice or chat), polls for completion, builds a per-scenario pass/fail scorecard, and creates a saved report grouped by Test Case. Use when a user wants to follow the Adversarial & Red-Team Testing cookbook (https://docs.coval.dev/guides/adversarial-red-team-testing) without doing each step by hand. Triggers: "adversarial test set", "red team my agent", "jailbreak / prompt-injection testing", "test my agent against bad actors".

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Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.

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Review dialogs to check whether screen readers can announce their purpose when they open. Identify missing or unclear labels, suggest title or label associations, and explain how to verify the changes with accessibility tools.

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• Checking names on modal dialogs
• Reviewing labels on alert dialogs
• Auditing shared dialog components

Check checkboxes, radio buttons, and switches for descriptive names that screen readers can announce. Identify missing or unclear labels, suggest appropriate HTML or ARIA labeling, and explain how to verify the changes with accessibility tools.

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• Checking labels on checkboxes and radio buttons
• Reviewing whether switch names explain their purpose
• Fixing missing or unclear accessible names

Check form fields for accessible names, the labels used by screen readers and voice controls. Identify missing or placeholder-only labels and suggest fixes using associated labels or ARIA attributes that supply or reference label text.

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• Finding missing labels in forms
• Fixing fields that rely only on placeholder text
• Checking names on custom form controls

Review progress bars to ensure screen reader users can tell which task they represent. Add descriptive accessible names, check progress semantics, and verify value attributes when the current progress is known.

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• Check progress bars for missing accessible names
• Label loading indicators with their task
• Review progress values and ranges

Check buttons, links, and other controls for clear accessible names, the labels used by assistive technology. Identify missing or vague names and suggest descriptive text or aria-label attributes that explain each action or destination.

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• Find buttons and links with missing names
• Replace vague labels with descriptive wording
• Review accessible names in shared components

Inspect hidden page regions for links, buttons, or inputs that still receive keyboard focus. Identify elements that screen readers cannot announce, suggest focus handling changes, and explain how to verify the resulting keyboard behavior.

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• Checking hidden regions for focusable controls
• Investigating silent focus during keyboard navigation
• Reviewing accessibility in shared UI components

Add, rename, or review SGLang environment variables using consistent definitions, types, names, and access methods. The skill also guides migration from old names and temporary test overrides that restore the original values afterward.

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• Adding a new SGLang environment variable
• Migrating deprecated environment variable names
• Temporarily overriding settings in tests

Analyze differences between financial budgets, actual results, forecasts, or prior periods. Break changes into measurable drivers, explain business causes, and prepare management commentary with waterfall breakdowns that show how each factor contributes.

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• Explain differences between budget and actual results
• Break down revenue or expense changes by driver
• Prepare variance commentary for management

Inspect and edit Figma files through JavaScript using the Plugin API. Create shapes, text, reusable components, and design variables, then check structure and screenshots as changes are made in small steps.

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• Inspect pages and existing components in a Figma file
• Create reusable components and variants
• Create and bind color or spacing variables