Create, update, or validate Storybook stories with comprehensive play functions
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Create, update, or validate Storybook stories with comprehensive play functions
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。
The NIST Cybersecurity Framework (CSF) 2.0, released in February 2024, provides a comprehensive taxonomy for managing cybersecurity risk through six core Functions - Govern, Identify, Protect, Detect, Respond, and Recover. bu skill covers conducting a maturity assessment against the CSF using Implementation Tiers to measure organizational cybersecurity posture and create improvement roadmaps.
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Tests APIs for Broken Function Level Authorization (BFLA) vulnerabilities where regular users can invoke administrative functions or access privileged API endpoints by directly calling them. The tester identifies admin and privileged endpoints, then attempts to access them with regular user credentials by manipulating HTTP methods, URL paths, and request parameters. Maps to OWASP API5:2023 Broken Function Level Authorization. Activates for requests involving BFLA testing, admin endpoint bypas...
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Apply Google-style docstrings and inline comments to Python .py files. Use when documenting new functions/classes/modules, incrementally documenting touched code, or flagging rename opportunities as TODOs.
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。
Create Azure cloud architecture diagrams in SVG format using official Microsoft Azure icons. Use when the user asks to create, generate, or draw an Azure architecture diagram, cloud diagram, infrastructure diagram, or any visual showing Azure services. Also trigger when user mentions creating diagrams for Azure Fabric, AKS, App Service, Functions, or any Azure service topology.
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Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
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Profile a running web application's CPU performance using Cursor's built-in browser profiler. Captures call stacks, identifies slow functions, and suggests optimizations. Use when a page feels slow or janky.
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。
Training patterns for autoregressive neural PDE solvers (FNO, DeepONet, CNO). Covers rollout training, noise injection for stability, multi-component loss functions (H1, frequency-sensitive, boundary-aware), per-channel normalization for coupled multi-variable systems, and the PDEBench nRMSE metric. Use when training any neural operator that predicts time-dependent PDE solutions.
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Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
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Zero-knowledge proofs and privacy patterns on Stellar. Covers Groth16 verification in smart contracts via BLS12-381 host functions (CAP-0059, available), the BN254 + Poseidon proposals (CAP-0074/0075, status-sensitive), and concrete toolchain walkthroughs for Circom (on-chain verifiable today), Noir, and RISC Zero (attestation pattern until BN254 lands). Use when building privacy-preserving applications, ZK-verifier contracts, or wiring a proving toolchain to Stellar.
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Guides systematic implementation of new sustainability metrics in OSS Sustain Guard using the plugin-based metric system. Use when adding metric functions to evaluate project health aspects like issue responsiveness, test coverage, or security response time.
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Detects per-caller special-cases (bandaids) bolted onto shared infrastructure/common functions, and when two or more same-kind special-cases exist proposes generalizing the lower-level mechanism instead.
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Sets up Convex auth, identity mapping, and access control. Use for login, auth providers, users tables, protected functions, or roles in a Convex app.
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Security review checklist for Convex functions, auth logic, public queries, admin routes, webhooks, uploads, and AI-generated code. Use when reviewing code that touches user data, PII, or access control.
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Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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Full-stack Convex development guidelines covering React, Vite, TypeScript, mutations, auth, design system, and documentation practices. Use when building features, writing Convex functions, or making code changes in this project.
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Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.
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Integrate Firebase Auth (authentication + domain restriction) into internal applications. Includes domain restriction via Blocking Functions and user registration to Firestore.
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。
Search Haskell APIs using Hoogle. Use when working with Haskell projects to look up function signatures, find functions by type, discover library documentation, or identify which module exports an item.
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Build real-time, reactive backend applications with Convex using TypeScript queries, mutations, and actions with automatic reactivity and optimistic updates. Use when building real-time collaborative applications, implementing reactive data synchronization, writing serverless backend functions, creating queries that auto-update, implementing mutations with transactional guarantees, handling file uploads with Convex storage, implementing authentication with Convex Auth, designing reactive database schemas, or building applications requiring instant data synchronization.
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Build reusable, composable, and maintainable React/Vue/Angular components following established design patterns like compound components, render props, custom hooks, and HOCs. Use when creating component libraries, implementing component composition, building reusable UI elements, designing prop APIs, managing component state patterns, implementing controlled vs uncontrolled components, creating compound components, using render props or children as functions, building custom hooks, or establishing component architecture standards.
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。
Create, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
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Modern .NET execution model with process isolation
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Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.
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。