「recommendation」の検索結果

Apply validated research paper insights to the current project codebase — improving architecture, code patterns, testing strategies, documentation, or workflows based on empirical findings. Load when learn-from-paper routes insights to the current project, or when the user asks to apply paper findings to this project, improve this codebase with research, use this paper to improve my project, or apply research to my code. Also triggers on "apply this to my project", "how can this paper help my codebase", "use these findings here", "implement paper recommendations", "use research to improve my code". Always called AFTER learn-from-paper has completed credibility and security checks — never ingests papers directly.

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Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.

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Comprehensive AWS cost analysis and optimization recommendations using AWS CLI and Cost Explorer

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Use this skill to design a vehicle preventive maintenance schedule. Covers manufacturer recommendations, industry-standard intervals, and how to set carrier-specific triggers.

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Use this skill when a driver is being screened for sleep apnea. Covers FMCSA Medical Review Board (MRB) recommendations, BMI thresholds, sleep study referrals, and continued certification.

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Use this skill when the user asks about driver fitness-for-duty programs — pre-trip readiness assessment, recognizing impairment from drugs/alcohol/medication/fatigue/mental health, refusing assignments when unfit, supervisor training on fitness assessment, FMCSA recommendations on duty status determination, and how to handle a driver who appears unfit. Reference 49 CFR 392.3 + 392.4.

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Use this skill when the user asks about cybersecurity for a trucking carrier — protecting ELD data, customer information, financial systems, EDI integrations, fleet telematics, ransomware risk, vendor / shipper data sharing, incident response, and FMCSA cyber-recommendations. Reference NIST + CISA cybersecurity frameworks.

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Delegate a read-only Coval evaluation, simulation, monitoring, product-how-to, or troubleshooting subtask to Sofia through the official Coval MCP consult_sofia tool. Use when the user needs Coval-specific FDE judgment, analysis of organization data, metric or test-set recommendations, or a diagnosis grounded in Coval runs and conversations.

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Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical. Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "service area", or "multi-location".

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Search domains, compare prices, find promo codes, get purchase recommendations. Use when user wants to buy a domain, check prices, or find domain deals.

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Detects code smells in PHP codebases. Identifies God Class, Feature Envy, Data Clumps, Long Parameter List, Long Method, Primitive Obsession, Message Chains, Inappropriate Intimacy. Generates actionable reports with refactoring recommendations.

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PHP Standards Recommendations (PSR) overview knowledge base. Provides comprehensive reference for all accepted PSRs including PSR-1,3,4,6,7,11,12,13,14,15,16,17,18,20. Use for PSR selection decisions and compliance audits.

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Detects test antipatterns and code smells in PHP test suites. Identifies 15 smells (Logic in Test, Mock Overuse, Fragile Tests, Mystery Guest, etc.) with fix recommendations and refactoring patterns for testability.

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Analyzes PHP codebase for test coverage gaps. Detects untested classes, methods, branches, exception paths, and edge cases. Provides actionable recommendations.

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Analyzes PHP codebase for SOLID principle violations. Detects God classes (SRP), type switches (OCP), broken contracts (LSP), fat interfaces (ISP), and concrete dependencies (DIP). Generates actionable reports with severity levels and remediation recommendations.

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Analyzes bounded context boundaries in DDD projects. Detects cross-context coupling, shared kernel violations, context mapping issues, and ubiquitous language inconsistencies. Generates context map diagrams and boundary recommendations.

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Comprehensive AWS cost analysis and optimization recommendations using AWS CLI and Cost Explorer

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Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets across 5 compute tiers, tournament evaluation, and telemetry-driven recommendations. Use when a user wants to uncensor, abliterate, or remove refusal from an LLM.

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Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.

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Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

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Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.

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Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

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Decision-making advisor using Tree of Thoughts for exploring options, analyzing trade-offs, and providing data-driven recommendations.

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。