「nct」の検索結果

Optimize a single Jetpack Compose @Composable function. Use when the user wants to improve, polish, animate, or refactor ONE Composable — keywords like "optimize this composable", "make this smoother", "add animation to this", "split this composable", "fix recomposition", "this composable is laggy", "polish this UI", or when user pastes/points to a single @Composable function. Analyzes the target for recomposition issues, missing animations, size/concern splits, and stability problems, then iterates with the user via AskUserQuestion to pick which optimizations to apply, then delegates implementation to the kta-compose-developer agent and summarizes changes. Input MUST be exactly one Composable (file path + function name, or function name alone).

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。

Use when working with Azure Functions Deep — deep Azure Functions analysis covering function app inventory, trigger types, execution metrics, scaling behavior, slot deployments, application insights integration, and consumption plan cost tracking. Provides optimization guidance for cold starts and memory usage.

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。

Write, configure, and deploy Netlify Edge Functions (Deno runtime at the network edge) in TypeScript/JavaScript. Use when adding request/response manipulation at the edge — auth middleware, geolocation redirects, A/B testing and personalization, content localization, redirects/rewrites, SSR at the edge, or transforming responses — or when configuring path routing, response caching, or edge error handling. Triggers on tasks like "add auth middleware", "geo-based redirect", "A/B testing at the edge", "rewrite requests", or editing files in netlify/edge-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。

Write, configure, and deploy Netlify serverless functions in TypeScript, JavaScript, or Go. Use this when adding an API endpoint or backend route, adding a contact form handler, wiring auth or Identity signup/login hooks, building streaming or AI-proxy responses, scheduling cron jobs, running long background jobs (batch processing/scraping), reacting to deploy or form events, setting up rate limiting or region/memory config, or reading environment variables and secrets inside a function. Covers file locations, the Request/Context/Response handler shape, path routing, config options, and local testing with netlify dev.

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。

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...

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。

Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.

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。

Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.

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。

Explores a CARLA map's road network through the Map/Waypoint API — a natural-language rundown of the whole map ("give me the topology"), drawing the topology to confirm the modelled map matches the visible one, enumerating junctions to resolve phrases like "the 4-way junction in the middle", nearest-waypoint lane facts, and next/previous lane navigation. Use when the user asks about the map's layout, lanes, junctions, topology, or to locate/navigate specific map elements.

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。

Analyzes smart contract codebases to identify state-changing entry points for security auditing. Detects externally callable functions that modify state, categorizes them by access level (public, admin, role-restricted, contract-only), and generates structured audit reports. Excludes view/pure/read-only functions. Use when auditing smart contracts (Solidity, Vyper, Solana/Rust, Move, TON, CosmWasm) or when asked to find entry points, audit flows, external functions, access control patterns, or privileged operations.

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 Shopify development reference covering Liquid templating, OS 2.0 themes, GraphQL APIs, Hydrogen, Functions, and performance optimization (API v2026-01). Use when working with .liquid files, building Shopify themes or apps, writing GraphQL queries for Shopify, debugging Liquid errors, creating app extensions, migrating from Scripts to Functions, or building headless storefronts. Triggers on "Shopify", "Liquid template", "Hydrogen", "Storefront API", "theme development", "Shopify Functions", "Polaris". Do NOT use for non-Shopify e-commerce platforms.

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。

Okta-as-IdP red-team attack chain — tenant discovery, user enumeration (multiple vectors), authentication flow analysis (factors enumeration, push-notification fatigue, SMS bypass), password spray with lockout discipline, Okta-specific phishing primitives (kits, FastPass abuse, OIDC redirect_uri tampering), MFA enumeration, post-compromise admin API surface. Many enterprise orgs use Okta instead of (or alongside) Entra ID. Distinct endpoints, distinct rate-limiting, distinct factor flows. Use when recon shows `<tenant>.okta.com`, `<tenant>.okta-emea.com`, `<tenant>.oktapreview.com`, or autodiscover-style records pointing at Okta IdP.

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。

Deploy serverless browser automation as cloud functions using Browserbase. Use when the user wants to deploy browser automation to run on a schedule or cron, create a webhook endpoint for browser tasks, run automation in the cloud instead of locally, or asks about Browserbase 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。

Functional programming helpers for Golang using samber/lo — 500+ type-safe generic functions for slices, maps, channels, strings, math, tuples, and concurrency (Map, Filter, Reduce, GroupBy, Chunk, Flatten, Find, Uniq, etc.). Core immutable package (lo), concurrent variants (lo/parallel aka lop), in-place mutations (lo/mutable aka lom), lazy iterators (lo/it aka loi for Go 1.23+), and experimental SIMD (lo/exp/simd). Apply when using or adopting samber/lo, when the codebase imports github.com/samber/lo, or when implementing functional-style data transformations in Go. Not for streaming pipelines (→ See `samber/cc-skills-golang@golang-samber-ro` skill).

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。

Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun metagenomics sequencing.

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。

Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic data.

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。

Creates and deploys Node.js HTTP web applications on AWS Lambda Web Functions. Guides users through building web apps and APIs with Express, Fastify, or Hono, packaging, deploying via the aws lambda-web CLI, and iterating. Triggers when user wants to deploy a website or web app to AWS as serverless, deploy a Node.js HTTP server to AWS, build a serverless website or API with Node.js, deploy Express/Hono/Fastify apps, set up multi-region HTTP endpoints, connect a Node.js web app to private VPC resources, or explicitly mentions Lambda Web Functions. Does NOT trigger for non-Node.js runtimes, event-driven patterns (SQS, Kinesis, S3 events), or container deployments.

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。

Debugs AWS Lambda function timeout failures by systematically analyzing function configuration, CloudWatch logs and metrics, VPC/networking, cold starts, memory constraints, and downstream dependencies to identify root causes with actionable fixes. Use when a Lambda function is timing out or approaching its timeout limit.

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。

Build Claude tool use (function calling) workflows with the Messages API. Use when implementing tool use, function calling, agent loops, or building AI assistants that interact with external systems. Trigger with phrases like "claude tool use", "anthropic function calling", "claude tools", "agent loop anthropic", "tool_use blocks".

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。

Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.

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。

LoongCollector E2E Testing Framework Development Guide. Use this rule when you need to understand E2E testing framework architecture, develop new test behavior functions, or extend testing capabilities. Contains detailed BDD testing framework usage, test behavior function development and registration workflows, and comprehensive reference of existing testing capabilities. Example: When adding custom test behaviors for new plugins, use this rule to understand how to write and register new test functions. Example: When developing E2E tests, use this rule to understand the e2e framework.

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。

Use this skill when the user asks about Ni Haisha / 倪海厦 TCM course material, especially Shang Han Lun / 伤寒论, Jingui / 金匮要略, Zhongjing Xinfa / 仲景心法, clinical cases / 临床案例 / 倪师医案, Bagang Bianzheng / 八纲辨证, Fuyang Forum / 扶阳论坛, Yijinjing / 易筋经, Liang Dong dialogue / 梁冬对话倪师, Stanford lecture / 斯坦福大学演讲, Tianji / 天纪 / 易经 / 阳宅 / 紫微斗数, Huangdi Neijing / 黄帝内经, Shennong Bencao / 神农本草, acupuncture / 针灸, meridians, acupoints, acupuncture depth safety / 危险进针深度 / 气胸风险, six-channel pattern identification, symptom-to-formula routing, formula comparison, lesson review, board/PPT screenshot evidence, or course-derived study notes. This skill is for educational distillation and study support only, not medical diagnosis, prescriptions, dosage, individualized treatment, or self-administered acupuncture.

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。

Use when wiring an existing DataFusion or datafusion-spark function into Comet for a Spark expression. Identifies the right wiring pattern (one-line passthrough, datafusion-spark UDF registration, or custom serde with input massaging / restrictions), applies the Scala serde, registers the UDF in jni_api when needed, and adds SQL file tests. Assumes the function already exists upstream — if not, switch to `implement-comet-expression`.

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。

Deploy serverless functions on Google Cloud Functions. Configure triggers and manage deployments. Use when implementing serverless workloads on GCP.

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。

Generate correct MATLAB code using the Symbolic Math Toolbox. Use when the user asks for symbolic computations, analytical solutions, symbolic differentiation/integration, equation solving, or converting symbolic results to numeric MATLAB functions. Also use when converting differential equations to transfer functions or state-space form, extracting PDE coefficients (pdeCoefficients), symbolic-to-C code generation (matlabFunction + codegen), symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine).

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。