「scaffold」の検索結果

This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

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Clean up after (or abandon) a Rails upgrade. Drop NextRails.next? and NextRails.current? branches and retire dual-boot scaffolding (Gemfile.next, Gemfile.next.lock, conditional Gemfile groups), keeping either the next or the current version. Trigger when the user says they are done with the upgrade, want to clean up dual-boot, want to drop NextRails branches, want to finish the upgrade, want to abandon or revert the upgrade attempt, want to roll back to the current Rails version, or want to pause this upgrade hop. Based on FastRuby.io's "Finishing an Upgrade" methodology, extended with an abandon/pause path.

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Build or audit Next.js 16 App Router apps using a next-beats-style React Server Components architecture. Use when scaffolding a new app, adding a feature, reviewing an existing app, refactoring route-loader-shaped pages into feature-owned async server components, deciding where queries/actions/components live, keeping pages synchronous with `params.then()`, placing Suspense boundaries, choosing the client/server boundary, designing skeletons, preventing CLS, or following Cache Components Instant Navigation. Also use when the user asks about RSC composition, components receiving IDs instead of route params, `'use cache'`, `cacheTag`, `updateTag`, static-shell prerendering, or making an app easier for AI agents to modify.

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Guides a one-question-at-a-time design interview, captures alignment in agent/EVE-BRIEF.md, then scaffolds and implements a runnable eve agent with verbose teaching comments. Use when the user wants to create a new eve agent, build an agent from scratch, or invokes /create-agent.

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Therapeutics Data Commons (TDC) AI-ready drug discovery datasets. Curated ADME, toxicity, DTI, DDI with scaffold/cold splits, standardized metrics, molecular oracles, and ADMET benchmarks for therapeutic ML and property prediction. For chemical database queries use chembl-database-bioactivity; for featurization use molfeat.

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Pythonic RDKit wrapper with sensible defaults for drug discovery. SMILES parsing, standardization, descriptors, fingerprints, similarity, clustering, diversity selection, scaffold analysis, BRICS/RECAP fragmentation, 3D conformers, and visualization. Returns native rdkit.Chem.Mol. Prefer datamol for standard workflows; use RDKit directly for advanced control.

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。

Structure-activity relationship (SAR) analysis guide for drug discovery including molecular descriptor analysis, scaffold analysis, and activity cliff detection.

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。

SST v4 (Ion) expert for managing AWS resources as code with the Pulumi-backed framework. Use when writing or editing sst.config.ts, building infra/ modules (sst.aws.Function/Bucket/Dynamo/Cron/Service/Router, sst.Secret, sst.Linkable, raw aws.* Pulumi resources), wiring resource links, scoping IAM, or running sst deploy/dev/diff/remove. Essential when the user mentions SST, sst.config.ts, $config, $transform, $interpolate, sst.aws.*, sst.Secret, Pulumi/Ion, "sst deploy", a failed SST deploy (ConflictException on a resource-type change, "Identifier '__filename' has already been declared", MalformedPolicyDocument on an Output<T>), or wants to scaffold/troubleshoot AWS infrastructure with SST. Also use when a request to "deploy my AWS stack" or "add a Lambda/bucket/table" is made in a repo that already contains an sst.config.ts (using $config) or an sst dependency. Do NOT use when the task is primarily AWS CDK, Terraform, raw CloudFormation, or SAM with no SST present — those have their own tooling.

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Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.

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Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.

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Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.

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Drive the agentkit CLI (aliases agentkit / ak) to scaffold, build, deploy, and manage agents on Volcengine AgentKit from the terminal — runtimes, knowledge bases, memory collections, tools, harnesses, invocation, SSO auth, sandboxes, and evaluation datasets. Use when a user wants to create/deploy an agent project, call or inspect a deployed runtime, manage AgentKit resources, or resolve a CLI/auth/deploy error. Does NOT handle non-AgentKit deployment, general Docker/k8s operations, Volcengine IAM management, or writing agent application code (use veadk-agent-development for that).

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。

Scaffolds new projects with git, CI/CD workflows, pre-commit hooks, and build config. Use when starting a new Python, Rust, or TypeScript project from scratch.

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。

Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.

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 REST API endpoints with proper structure, validation, error handling, and types. Use when creating new API routes, endpoints, or backend services.

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。

Scaffold, build, and package SwiftPM-based macOS apps without an Xcode project. Use when you need a from-scratch macOS app layout, SwiftPM targets/resources, a custom .app bundle assembly script, or signing/notarization/appcast steps outside Xcode.

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Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Scaffolds a 7-part skeleton with a scope and non-overlap statement, summary-table stubs and reporting-guideline wiring, without inventing citations. Original research is /write-paper.

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Use when you need a runnable PyTorch training repo for a medical-imaging task (segmentation, classification, detection, synthesis, self-supervised, or fine-tuning a pretrained backbone). Emits a patient-level seed-locked split, train/evaluate scripts, config and a Methods stub.

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Use when managing a manuscript project over time. Scaffolds the project structure, tracks writing progress across phases, maintains project memory files, and generates submission checklists and backwards timelines (commands init, status, sync-memory, checklist, timeline).

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Use when starting or inheriting a radiology research project and need to know what it is. Classifies the project type, summarizes its current state, lists missing inputs, recommends next steps and scaffolds lightweight project memory files.

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Vulnerability-research loop toward a novel CVE. Target triage -> attack-surface map -> ranked hypotheses -> investigate (RE / fuzz / audit) -> a finding deepens the loop, a dead-end pivots to a new approach. Uses the full wiki + hunt skillset. Scaffolds and persists state under raw/research/<project>/. Triggers - "research", "find a cve", "analyze this binary/library", "audit this code for vulns".

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Create and maintain one committed per-project memory file (PROJECT.md) so agents stop re-discovering the same facts every cold session. Stores only the stable, expensive-to-rediscover, not-in-the-code context — architecture + why, build/test/run commands, decisions and dead-ends — as human-readable markdown, versioned with the code so it can't silently rot. Use when asked to set up project memory/context, stop agents re-grepping the codebase, scaffold or refresh a PROJECT.md / CLAUDE.md memory section, or cut cold-start rediscovery cost. Prose context only — never code, config, or 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。

Create, generate, or scaffold Makefiles with .PHONY targets and build automation.

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Create, generate, or scaffold GitHub Actions workflows, action.yml, or .github/workflows CI/CD pipelines.

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。