「based」の検索結果

Implement authentication and authorization with Better Auth - a framework-agnostic TypeScript authentication framework. Features include email/password authentication with verification, OAuth providers (Google, GitHub, Discord, etc.), two-factor authentication (TOTP, SMS), passkeys/WebAuthn support, session management, role-based access control (RBAC), rate limiting, and database adapters. Use when adding authentication to applications, implementing OAuth flows, setting up 2FA/MFA, managing user sessions, configuring authorization rules, or building secure authentication systems for web applications.

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Add file-based observability, tracing, and run analysis to LLM/agent experiments — per-turn transcripts, tool calls and results, reasoning traces, token/cost accounting, per-episode artifacts, plus terminal viewers and a run-comparison report. Platform-agnostic: one small adapter covers OpenAI, Gemini/Vertex, Anthropic, LiteLLM, Tinker, vLLM, or any custom inference stack, and the same tooling then works unchanged. Use this skill whenever the user wants observability, tracing, logging, or run tracking for model experiments; asks why an agent failed a task or wants to replay/debug/diff an episode; wants to compare models, arms, or ablations; wants to instrument a new folder, repo, or platform ("add observability here", "do the same for Tinker/Gemini/OpenAI"); wants to import or tie in existing experiment results so old runs show up alongside new ones; or wants eval runner scripts where many models share one protocol. Reach for this even when they only say "log what the model is doing", "I can't tell what happened in this run", or "set up traces for this experiment".

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Build MCP servers using the Leanmcp SDK with decorator-based TypeScript. Use this skill when users ask for "leanmcp", "MCP with decorators", "MCP with authentication", "MCP with elicitation", "MCP with environment injection", or want a simpler, more elegant way to build MCP servers. Leanmcp provides automatic schema generation, dependency injection, authentication, and user input collection.

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Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a research brief, or assemble evidence for a decision. Also use when comparing options that need a structured, evidence-based verdict rather than an opinion.

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Establishes what something actually costs — fixed, variable and mixed cost behavior, absorption versus variable costing, job-order, process and activity-based methods, breakeven and operating leverage, and price/volume/mix decomposition. Use this to set a price floor, explain why revenue or margin moved, decide make versus buy, judge whether a product line earns its place, or work out how an allocation basis is distorting a reported margin.

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PaddleOCR document parsing skill based on PaddleOCR-VL-1.5. Provides SOTA-level document understanding with ultra-high precision recognition and parsing. Use when user needs to parse, extract, or understand document content.

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PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.

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Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.

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基于协议的依赖注入（Protocol-based Dependency Injection），通过精简的协议和 Swift 测试框架（Swift Testing）来模拟文件系统、网络和外部 API，编写可测试的 Swift 代码。

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Screens research papers based on title/abstract and inclusion criteria, providing a structured Yes/No/Maybe decision. Use when you need to filter literature for meta-analysis or systematic reviews.

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Constraint-based reconstruction and analysis (COBRA) for metabolic models; use when you need to simulate growth/production, analyze flux ranges, or run knockout and medium studies from SBML/JSON/YAML models.

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Generate graphical abstract layout recommendations based on paper abstracts.

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Filter compound libraries based on Lipinski's Rule of Five for drug-likeness.

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Digital pathology image processing toolkit for whole slide images (WSI). Supports WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.

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Generates scientifically sound inclusion and exclusion criteria for Meta-Analysis based on a given title or keywords. Use when user wants to design eligibility criteria for a systematic review or meta-analysis.

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Orchestrates a systematic review and meta-analysis workflow following PRISMA 2020 guidelines, from protocol development through multi-database search, screening, data extraction, and evidence synthesis. Use when conducting evidence-based reviews, meta-analyses, or scoping revi...

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Generates the "Risk of Bias" results section for a meta-analysis based on assessment tables and statistics. Use when the user wants to draft the risk of bias analysis text from provided data tables.

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Generates the "Results" section for meta-analysis sensitivity analysis based on statistical tables and titles. Use when the user wants to describe sensitivity analysis results or format sensitivity tables for a meta-analysis paper.

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A multi-stage workflow for writing long-form medical reviews; used when the user needs to build an outline based on PubMed literature, write chapter by chapter, perform supplementary searches, and format citations; input is the review topic and project directory, output is a c...

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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). ...

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Generates complete dual-disease shared-transcriptome biomarker and hub-gene research designs from a user-provided disease pair and shared-biology direction. Always use this skill whenever a user wants to design, plan, or build a non-oncology two-disease transcriptome study centered on per-disease differential expression, shared-signal intersection or concordance, PPI-based hub-gene prioritization, diagnostic evaluation across both diseases, immune infiltration context, pathway interpretation, and optional orthogonal validation. Covers five study patterns (shared-DEG-first workflow, hub-gene-first shared-biomarker workflow, hybrid shared-biomarker compression workflow, immune-context shared-biomarker workflow, orthogonal validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...

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Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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Generates complete process-related diagnostic biomarker bioinformatics research designs from a user-provided disease context, gene-family or pathway theme, and validation direction. Use when a study centers on process-related genes, DEG and WGCNA integration, machine-learning feature selection, nomogram-based diagnostic modeling, immune infiltration, regulatory-network analysis, and optional external or experimental validation. Covers five study patterns (process-DEG discovery, co-expression-module integration, machine-learning biomarker selection, diagnostic model/nomogram workflow, immune-regulatory interpretation and validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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Generates complete FAERS-style pharmacovigilance disproportionality research designs from a user-provided drug class, comparator strategy, adverse-event domain, and patient-group stratification. Always use this skill whenever a user wants to design, plan, or build a spontaneous-report safety signal study using FAERS or a similar pharmacovigilance database, especially when the article logic includes product selection, indication-group stratification, MedDRA-based adverse-event extraction, serious-case filtering, suspect-drug and concomitant-exclusion logic, reporting odds ratio analysis, comparator-drug benchmarking, cross-drug comparison, and cautious signal interpretation without causal overclaiming. Covers five study patterns (single-drug disproportionality workflow, multi-drug class comparison workflow, indication-stratified workflow, comparator-controlled signal screening workflow...

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。