'quality' 검색 결과

Explains how PluginEval combines structural checks and experimental model assessments into quality scores. Helps interpret low scores, identify improvement areas, set marketplace thresholds, and explain what evaluation badges actually represent.

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• Investigating why a skill received a low score
• Improving descriptions that define when a skill should run
• Setting score thresholds for marketplace listings

Build data quality checks with Great Expectations, dbt tests, and data contracts, which define shared expectations between teams. Check missing values, duplicates, and freshness, then integrate validation into data pipelines and CI/CD.

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• Check data for missing values and duplicates
• Build a dbt test suite
• Define shared data contracts between teams

Analyze customer profitability and revenue durability for SaaS, subscription, and other recurring businesses. Examine acquisition costs, retention, and revenue trends by customer group, then produce an Excel workbook, summary slide, and issues for further investigation.

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• Assessing recurring revenue quality in an investment target
• Tracking revenue by customer acquisition year
• Comparing acquisition costs with customer lifetime value

Review an AI workflow across five areas: prompts, use of context, tools, system structure, and safety. Receive scores, specific findings, and prioritized actions to address quality and reliability problems.

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• Check an AI workflow before production use
• Audit an existing agent for quality and reliability
• Prioritize fixes for workflow problems

Evaluate LLM application quality using automated scores, human reviews, and another language model as a judge. Compare models or prompts, establish baseline results, and detect quality drops through repeatable tests and statistical comparisons.

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• Comparing models and prompts
• Checking quality before deployment
• Evaluating search quality in RAG applications

Prepare training datasets for large language models with GPU-assisted cleaning. Covers duplicate removal, quality filtering, and personal information redaction, with workflows for text, images, video, and audio using NeMo Curator.

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• Clean web data for model training
• Remove exact and near duplicates from large text collections
• Redact personal information from training text

Turn a feature into an agent skill or improve an existing one. Define purpose-specific quality criteria, review outputs with models from three providers, then add tests and check that user requests reach the intended skill.

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• Turn a reusable feature into an agent skill
• Audit an existing skill for missing parts
• Check quality after fixing or extending a skill

Audit a gbrain knowledge base for outdated pages, broken or missing links, inconsistent tags, and missing citations. Get issue counts and specific repair actions, with additional checks for search quality and maintenance status.

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• Audit knowledge base quality
• Find isolated pages and broken links
• Review citations and inconsistent tags

Review Playwright browser tests against 20 quality checks to find unreliable patterns and missing coverage. Get scores for each file, prioritized findings, and corrected code for critical issues.

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• Reviewing a specific Playwright test file
• Auditing test quality across a project
• Finding causes of unreliable test runs

Choose a web application stack, generate a starter project, and assess existing code quality. Uses team size, release frequency, audience, and budget to guide recommendations, with reports covering security, complexity, dependencies, and prioritized improvements.

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• Generating a starter project for a web application
• Choosing a technology stack within team and budget constraints
• Reviewing code security and complexity

Design evaluation systems that measure agent results across accuracy, completeness, citations, and tool efficiency. Build repeatable tests, compare changes against a baseline, and define quality checks that catch regressions before deployment and monitor production performance.

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• Compare agent configurations against a baseline
• Catch quality regressions before deployment
• Measure the effects of context strategies

Prepare training datasets for large language models with GPU-assisted cleaning. Covers duplicate removal, quality filtering, and personal information redaction, with workflows for text, images, video, and audio using NeMo Curator.

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• Clean web data for model training
• Remove exact and near duplicates from large text collections
• Redact personal information from training text

Review code changes and files for bugs, security risks, performance problems, design issues, and test coverage. Receive a structured report with prioritized findings, concrete improvement examples, positive feedback, and an overall review verdict.

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• Reviewing a pull request
• Auditing code quality and security
• Finding refactoring opportunities

Help an agent periodically review whether its work stays on task, remains thorough, avoids repetition, respects earlier decisions, and covers every item. Record assessments and revisit working notes when quality declines so the approach can be adjusted.

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• Check for drift during a long-running task
• Review repeated or contradictory output
• Track whether requested items have been dropped

Plan or run quality checks and peak calling, which identifies enriched genomic regions, for ChIP-seq, CUT&RUN, and CUT&Tag. The workflow accounts for controls and replicates and prepares signal tracks, quality reports, and differential binding designs.

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• Check data quality and enrichment signals
• Choose narrow or broad peaks for the biological target
• Create bigWig tracks and quality dashboards

Assess whether data is trustworthy enough for analysis, dashboards, experiments, or modeling. Check missing values, duplicates, consistency, freshness, and changes over time, then explain the evidence, downstream risks, likely causes, and practical fixes.

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• Check missing values and duplicate records
• Investigate sudden changes in data quality
• Reconcile conflicting sources and metric definitions

Comprehensive web quality audit covering performance, accessibility, SEO, and best practices in a single review. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website" across multiple areas at once. Orchestrates specialized skills for depth. Do NOT use for single-area audits — prefer core-web-vitals, web-accessibility, seo, or web-best-practices for focused work.

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VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check

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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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[omh] Deliverable demands premium polish: enforce superior content, design, layout, publishing, and visual QA gates. Use when the user says: design-quality-gate, design quality gate, ui ux pro max, design pro max, frontend pro max, visual qa pro, premium design, high quality design.

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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

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Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.

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Diagnostic-only test suite auditor. Classifies repo type, maps against 7-layer testing taxonomy (git hooks → static → unit → integration → system → E2E → acceptance), runs deterministic quality gates (coverage, mutation, CRAP, architecture, escape-scan), builds RTM / personas / journeys traceability, produces TEST_AUDIT.md, updates tests/TESTING.md, and mandatorily hands off to implement-tests when gaps are found. Use when auditing test quality, finding test gaps, or running the full 7-layer sweep. Trigger with "audit tests", "find gaps", "test audit", "check test quality", "full sweep", "7-layer audit", "rtm check".

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