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Found 145 Skills
Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
PluginEval quality methodology — dimensions, rubrics, statistical methods, and scoring formulas. Use this skill when understanding how plugin quality is measured, when interpreting a low score on a specific dimension, when deciding how to improve a skill's triggering accuracy or orchestration fitness, when calibrating scoring thresholds for your marketplace, or when explaining quality badges to external partners like Neon.
Checkpoint - Pre-publish review with multi-layer deep analysis. Triggers: Preparing to publish an npm package, requiring pre-release review, or checking code change quality. Review Layers: - Per-Change: In-depth analysis of each change group (up to 10 Agents) - Holistic: Parallel review by 5 roles (Architecture/Development/Testing/Security/Documentation) - Synthesis: 1 Agent summarizes review results Commands: - /把关 - Start pre-publish review - /把关 check - Check unpublished changes - /把关 version - Recommend version upgrade - /把关 report - Generate review report - /review - English command Capabilities: Unpublished change detection, in-depth per-change analysis, multi-role review, version recommendation, release risk assessment.
Analyzes codebases to identify refactoring opportunities based on Martin Fowler's catalog of code smells and refactoring techniques. Detects duplicated code, high coupling, complex conditionals, primitive obsession, long functions, and other structural issues. Produces a structured refactoring report with prioritized findings saved to docs/_refacs/. Use when auditing code quality, preparing for a refactoring sprint, or reviewing architectural health. Don't use for style/formatting issues, performance optimization, or security audits.
Deep diagnostic of Claude/SDD configuration. Read-only. Produces audit-report.md consumed by /project-fix. Trigger: /project-audit, audit project, review claude config, project health check.
Measure and improve the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For deployment, use agent-platform-deploy.
Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column distributions, identifying nulls and outliers, or deciding which dimensions to analyze.
Technical solution evaluation and code review in the style of Linus Torvalds. Only use this when the user explicitly requests a Linus-style review or explicitly asks for a rigorous evaluation of code changes/technical solutions (e.g., "review changes/code", "evaluate if the solution is appropriate", "check submission standards", "linus-tech-review").
Test suite audit coordinator (L2). Delegates to 5 workers (Business Logic, E2E, Value, Coverage, Isolation). Aggregates results, creates Linear task in Epic 0.
Comprehensive code review workflow - parallel specialized reviews → synthesis
Comprehensive CSV data analysis and visualization tool. Use this skill when analyzing CSV files, generating data summaries, creating visualizations from data, detecting outliers, finding correlations, assessing data quality, or creating data reports. Triggers on CSV analysis, data exploration, data visualization, data profiling, statistical analysis, or data quality assessment requests.
Is this token held by quality wallets or retail noise? SM holder ratio, flow breakdown by label, and recent buyer quality.