432 件 ・ 関連度順
概要と使いどころ
Audit data quality across six DAMA DMBOK dimensions — Completeness, Accuracy, Consistency, Timeliness, Validity, Uniqueness. Produces a scored data quality report with issue log and remediation plan. Use when profiling datasets, onboarding new data sources, or building data quality gates.
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。
Identify and simulate Data Poisoning attacks aimed at degrading or skewing an AI model's accuracy. This skill focuses on Adversarial Machine Learning concepts where attackers inject malicious or mislabelled data points into training or fine-tuning datasets (e.g., feedback loops) to bias the AI.
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 this agent when you need to review UniProt annotation rules (ARBA, UniRule) for quality, biological accuracy, and GO annotation appropriateness. This agent performs comprehensive analysis of rule condition sets, evaluates literature support, assesses taxonomic scope, and recommends curation actions.
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。
Audit a spreadsheet for formula accuracy, errors, and common financial-model mistakes. Use for selected ranges, single sheets, or whole-workbook model checks including balance-sheet balance, cash tie-out, roll-forwards, and logic sanity.
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。
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 provides guidance for maintaining documentation consistency with implementation in the vscode-sidebar-terminal project. Use this skill when creating or updating documentation, verifying documentation accuracy, preparing releases, or when the codebase has changed and documentation may need updates. This skill should be used proactively after implementing features or bug fixes.
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。
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 a task needs the judgment of an Etcher/Engraver — compensating a resist pattern for expected undercut before etching fine detail, calculating etch time from a known etch rate rather than judging completion visually, verifying a functional engraving's line width/depth against its actual accuracy requirement, or re-validating process parameters on a new material batch before production.
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 a task needs the judgment of a Data Entry Keyer — resolving an illegible or ambiguous source-document field before keying it, running key-verification (double-key) reconciliation on a batch, deciding whether a production-speed quota is compromising accuracy, or sampling a completed batch for a quality-control audit.
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 a task needs the judgment of a Molder, Shaper, or Caster (ceramics, concrete, and similar non-metal, non-plastic materials) — calculating mold/pattern dimensions from a material's actual characterized shrinkage rate, deciding whether a demolding decision should follow a fixed time or a material readiness signal, controlling drying/curing rate to avoid cracking on uneven-thickness parts, or verifying mold dimensional accuracy after extended 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。
Detect documentation drift, stale references, and cross-document inconsistencies in any project. Scans for code-doc drift (API/function changes not reflected in docs), cross-doc drift (conflicting information across documents), and stale references (broken links, deleted files, outdated versions). Use when checking "doc freshness", "stale docs", "documentation drift", "broken links", "outdated documentation", "doc accuracy", "docs out of date", "doc audit", "doc health", or "verify documentation".
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。
Code comment accuracy verification, documentation completeness assessment, comment rot detection.
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。
Evaluating diagnostic tests — sensitivity, specificity, ROC analysis, likelihood ratios, and study design.
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。
Elicit step-by-step reasoning from language models to boost accuracy on math, logic, and multi-step problems.
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。
Analyzing behavioral experiment data — RT/accuracy preprocessing, mixed-effects models, and robust inference.
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。
Audit personal finance and budgeting app spending intelligence features. Triggers: you need to evaluate transaction categorization accuracy (MCC mapping, ML classification, merchant matching).
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。
Audit workplace risk scoring systems and occupational safety programs -- evaluate job hazard analysis (JHA/JSA) methodology and task-level hazard identification, risk matrix calibration for likelihood and consequence scales, exposure assessment accuracy for chemical, noise, vibration.
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。
Audit corporate tax compliance systems across jurisdictions. Analyzes tax engine configuration (Avalara, Vertex, ONESOURCE), nexus determination and Wayfair economic nexus tracking, sales/use tax calculation accuracy, federal and state income tax compliance (book-to-tax adjustments, NOL.
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。
Audit workforce scheduling systems for labor optimization and compliance. Triggers: you need to evaluate labor demand forecasting accuracy, shift generation and optimization algorithms.
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。
Analyze insurance underwriting systems for risk assessment accuracy, pricing adequacy, and portfolio exposure management.
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。
Audit ESG reporting software and sustainability metric accuracy. Analyzes Environmental (Scope 1/2/3 emissions, water, waste, biodiversity), Social (workforce diversity, pay equity, human rights due diligence), and Governance (board composition, ethics, risk) data collection against GRI.
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。
End-to-end affordable housing compliance and risk audit: analyze property management and waitlist operations, predict eviction risk with early warning models, review Fair Housing Act and HUD regulatory compliance, and model rent burden and subsidy accuracy across the portfolio..
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。
Audit workforce skill gap identification systems and labor market alignment. Triggers: you need to evaluate skill taxonomy quality, individual and aggregate gap analysis accuracy.
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。
Audit retirement planning software for projection model accuracy, asset allocation by age, Social Security optimization, tax-advantaged account strategy, withdrawal sequencing including Roth conversion ladders, Monte Carlo simulation quality, and inflation adjustment methodology..
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。