Automate Brevo (formerly Sendinblue) email marketing operations through Composio's Brevo toolkit via Rube MCP.
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。
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Automate Brevo (formerly Sendinblue) email marketing operations through Composio's Brevo toolkit via Rube MCP.
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。
You are a browser automation expert who has debugged thousands of flaky tests and built scrapers that run for years without breaking. You've seen the evolution from Selenium to Puppeteer to Playwright and understand exactly when each tool shines.
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。
Execute comprehensive web application security testing using Burp Suite's integrated toolset, including HTTP traffic interception and modification, request analysis and replay, automated vulnerability scanning, and manual testing workflows.
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。
Automate Cal.com tasks via Rube MCP (Composio): manage bookings, check availability, configure webhooks, and handle teams. Always search tools first for current schemas.
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。
Automate Basecamp project management, to-dos, messages, people, and to-do list organization via Rube MCP (Composio). Always search tools first for current schemas.
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。
Automate BambooHR tasks via Rube MCP (Composio): employees, time-off, benefits, dependents, employee updates. Always search tools first for current schemas.
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。
Azure Identity SDK for Rust authentication. Use for DeveloperToolsCredential, ManagedIdentityCredential, ClientSecretCredential, and token-based authentication.
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。
Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
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。
Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
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。
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
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。
Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.
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。
Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.
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。
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
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。
Master API documentation with OpenAPI 3.1, AI-powered tools, and modern developer experience practices. Create interactive docs, generate SDKs, and build comprehensive developer portals.
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。
Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.
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。
Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.
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。
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
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。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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。
Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.
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。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
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。
Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
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。
Rank and prioritize neoantigen/epitope candidates by likely T-cell response using NeoFox feature annotation, PRIME2.0, BigMHC-IM, the Łuksza/Balachandran fitness model (agretopicity + foreignness), and pVACtools tiering. Encodes the field's hard truths that immunogenicity is the least-solved layer (dedicated scores ~AUROC 0.6-0.7, modest PPV), that scores are valid only for RANKING within one patient (never absolute go/no-go or cross-patient), that DAI has anchor-inflation and WT-denominator traps, and that stacking weak correlated scores into one number is a red flag. Use when ordering a candidate list for a vaccine. Binding lives in mhc-binding-prediction; calling in neoantigen-prediction.
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。
Predicts protein-coding gene structures (exons, introns, UTRs) in eukaryotic genomes with BRAKER3 (RNA-seq + protein evidence), BRAKER1/BRAKER2, GALBA (protein-only), Funannotate (fungi), GeMoMa (homology projection), or Helixer/Tiberius (deep-learning ab initio). Covers the evidence-first tool decision, mandatory soft-masking, the training-set-quality-dominates principle, OrthoDB clade-partition selection, the one-isoform-per-locus and missing-UTR traps, merge/split errors, and reference bias against orphan genes. Use when annotating a newly assembled eukaryotic genome, choosing a gene-prediction pipeline based on available evidence, or diagnosing a poor annotation.
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 tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.
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。