「building」の検索結果

Use when building with Reka UI (headless Vue components) - provides component API, accessibility patterns, composition (asChild), controlled/uncontrolled state, virtualization, and styling integration. Formerly Radix Vue.

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Vite build tool configuration, plugin API, SSR, and Vite 8 Rolldown migration. Use when working with Vite projects, vite.config.ts, Vite plugins, or building libraries/SSR apps with Vite.

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Use when building styled UI with @nuxt/ui v4 components (Button, Modal, Form, Table, etc.) - provides ready-to-use components with Tailwind Variants theming. Use vue skill for raw component patterns, reka-ui for headless primitives.

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。

Comprehensive Cline SDK skill for building AI agents. Covers the direct Agent runtime, ClineCore sessions, custom tools, plugins, events, LLM providers, scheduling, multi-agent teams, and production deployment. Use for any task involving @cline/sdk or its sub-packages.

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Streamlit Web application development expert skill. Provides guidance on OIDC authentication (st.login/st.logout/st.user), secrets management, data visualization with Plotly/Altair, performance optimization with caching, and modern Streamlit features (v1.42-1.52+). Use this skill when building Streamlit apps, implementing user authentication, creating data dashboards, or optimizing app performance. Triggers include "streamlit app", "st.login", "data dashboard", "streamlit authentication", "streamlit visualization".

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Expert guidance for Salesforce Flow implementation from design through deployment. Use this skill when building Screen Flows, Record-Triggered Flows, Schedule-Triggered Flows, or Autolaunched Flows. Covers Flow design patterns, metadata XML generation, variable/element reference validation, governor limit optimization, and sf CLI deployment. Critical for preventing reference errors (undeclared variables, invalid element references) and deployment failures. Use when creating new Flows, debugging Flow errors, optimizing Flow performance, or deploying Flows to production.

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Correlate events across multiple log files from different sources, systems, or time periods. Build unified timelines, identify causal relationships between events, and highlight anomalies that span multiple data sources. Supports timezone normalization and gap detection. Use when analyzing logs from multiple systems (frontend, backend, database, infrastructure), investigating distributed system failures, or building event timelines across services. Triggers: "correlate these logs", "build timeline from multiple logs", "cross-system analysis", "find related events across logs", "multi-source log analysis", "distributed trace analysis"

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Comprehensive data science workflow skill for analyzing tabular and time series data. Use when conducting exploratory data analysis, building predictive models, performing feature engineering, or generating data-driven insights. Supports end-to-end analysis from data understanding through model deployment, following industry best practices for regression, classification, time series forecasting, and statistical analysis.

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。

Generic helpdesk first-response skill for creating KB-based response drafts. Use when handling support tickets, creating response templates, or building a structured helpdesk workflow. Supports error code detection, keyword matching, confidence scoring, multi-language templates, and escalation workflows. Customize by providing your own KB articles and configuration.

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Generate audit-ready internal control design documents from As-Is business process inventories. Produces control IDs, assertion mappings, procedures, SoD analysis, KPIs, materiality thresholds, and implementation roadmaps. Use when building internal controls for new audit engagements, SOX/J-SOX compliance, or process improvement initiatives.

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Terraform / OpenTofu / Nix / k8s manifest misconfiguration detection — open security groups, missing encryption, public S3/GCS, IAM wildcards, plaintext secrets, missing tags. Use when reviewing an IaC PR, gating `terraform apply` / `tofu apply`, auditing existing state for drift, or building a compliance report for cloud configuration.

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Package license analysis — detect copyleft conflicts against a permissive policy, surface AGPL / SSPL / GPL contaminants, output SPDX SBOM with per-package license findings. Use when auditing a release for license compliance, vetting a new dependency's license, building an OSS-attribution document, or producing a customer-facing license disclosure.

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Dockerfile / Containerfile / compose analysis plus optional Trivy / Grype / Syft composition when those binaries are present. Use when reviewing a Dockerfile PR, gating `docker build`, building an image SBOM, evaluating base-image risk, or auditing a registry image for CVEs.

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Domain knowledge for using PrintKK print-on-demand API tools effectively. PrintKK is a print-on-demand platform that lets sellers create custom products, manage designs, upload images, and fulfill orders via API. Use this skill whenever the user wants to interact with PrintKK — browsing products, creating designs, placing orders, managing images, or building integrations with the PrintKK API. Also trigger when the user mentions "PrintKK", "print on demand", "POD fulfillment", custom product design workflows, or wants to automate their PrintKK store operations.

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Use when building custom agent loops. Modify tool dispatch, history management, hooks, control flow.

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Use when building serverless AI SDK for Python endpoints, handling hook approvals, deferring hooks, or resuming runs across requests.

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 adding durable execution to AI SDK for Python, building durable agent loops, or serializing messages across workflow steps.

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 the user starts a non-trivial coding/building task in Claude Code (e.g. "帮我做个 X", "help me build Y", "add feature Z", "搭一个 Z"). Layers an AI-native pedagogical coat over normal coding work — surfaces implicit assumptions in user intent, annotates non-trivial design decisions inline with brief concept-scaffolding for terms the user may not know, and replaces "should I run it?" handoffs with rigorous AI self-verification plus a clean list of what only the user can verify. Skip for pure Q&A, single-line edits, read-only investigation, or refactoring along an existing pattern.

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Product-discovery coach for Fishbowl engineers — inspired by Marty Cagan's work (never impersonates him). Stage-routes between opportunity brief, research, PRD, ticket drafting, and outcome review. Triggers on "product coach", "help me with product", "I need to write a PRD", "I want to do discovery", "opportunity assessment", "who is this for", "why are we building this", or when an engineer is starting, resuming, or post-mortem-ing product-adjacent work. Invoke with a short description of what you want to do, or invoke bare to be surveyed and routed.

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Conduct a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.

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Load when building .NET ATProtocol applications with CarpaNet source generators, XRPC queries, Jetstream subscriptions, OAuth 2.0 DPoP, or Lexicon JSON models.

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Load when configuring GitBook documentation sites, authoring GitBook-flavored markdown pages and custom blocks, integrating OpenAPI/Swagger specs, driving GitBook Change Request workflows (create, review, comment, resolve), or building GitBook platform integrations. Do not use for general repository code reviews, general .NET OpenAPI schema generation, or non-GitBook markdown.

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Define one thin vertical slice with target behavior, risks, and acceptance criteria. Use when scoping the next piece of work before building, or when a slice from `memory/PLAN.md` needs precise definition.

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Knowledge base from the GAO Schedule Assessment Guide (GAO-16-89G, 2015). Use for building, assessing, or auditing a program's integrated master schedule (IMS): the ten best practices of a reliable schedule (capture, sequence, resource, duration, traceability, valid critical path, reasonable total float, schedule risk analysis, updating, baseline), the four characteristics (comprehensive, well-constructed, credible, controlled), critical path method arithmetic (forward/backward pass, total float), schedule risk analysis (Monte Carlo, contingency), statusing and baseline control, and the Appendix II audit triad. Scheduling/time-management oriented: it is the authority on schedule reliability, but it is NOT a cost-estimating guide, a full SE process model, an agile guide, or a risk-management framework — see sibling packs (gao-cost, dau-se-guidebook, nasa-schedule, nasa-risk) for those.

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。