“setup”的搜索结果

Find, build, evaluate, and improve systems using decision models. Use for bounded classification, routing, ranking, Choice/Score/Noul, decision-model composition, evaluation harnesses, prompt/program hill climbing, and Software 3.0 workflows across software, business, organizations, and life. Separate models, code, and human judgment. TypeSafe Jev is the default hosted exemplar. Not for straightforward arithmetic, prose rewriting, or provider setup alone.

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Initialize or repair the GEO-SEO Codex runtime for plugin and classic installer modes. Creates a Python virtual environment, installs requirements, verifies bundled scripts/templates, and explains optional PDF/browser dependencies.

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Shared setup and rules for the report-skills bundle (report-publisher, client-reporter, proposal-tracker, deck-publisher, report-designer). Loaded by the individual skills for the common ReportRoom MCP publish flow, account bootstrap, and safety gates. Not invoked directly — pick the specific skill for the job.

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Refactor test files to improve behavioral coverage, clarity, structure, assertions, fixture setup, mocking strategy, and remove implementation-detail or low-value tests. Use when asked to clean up, declutter, consolidate, or improve tests.

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Generate onboarding documentation for a codebase — architecture overview, key files, local setup, and common gotchas. Use this skill whenever someone asks to onboard onto a codebase, create onboarding docs, generate a codebase overview, explain a project's architecture to newcomers, or asks "how does this codebase work". Also trigger when users say things like "document this repo for new devs", "write a getting started guide", or "help me understand this project".

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Load Remotion best practices for React video creation, including animations, composition setup, assets, audio, captions, sequencing, transitions, media metadata, Three.js, Tailwind, and rendering patterns. Use when creating, editing, debugging, or reviewing Remotion code.

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Guie desenvolvedores na configuração de ambientes de desenvolvimento com ferramentas, dependências e configurações adequadas

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Quando o usuário quer planejar, projetar ou implementar um teste A/B ou experimento. Também use quando o usuário menciona "teste A/B", "split test", "experimento", "testar essa mudança", "copy variante", "teste multivariado" ou "hipótese". Para implementação de rastreamento, veja analytics-tracking.

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Quando o usuário quiser configurar, melhorar ou auditar rastreamento e medição de análises. Também use quando o usuário mencionar "configurar rastreamento", "GA4", "Google Analytics", "rastreamento de conversão", "rastreamento de eventos", "parâmetros UTM", "tag manager", "GTM", "implementação de análises" ou "plano de rastreamento". Para medição de testes A/B, consulte ab-test-setup.

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Load this skill when configuring or reviewing CI/CD pipelines, GitHub Actions workflows, or automated testing setups. Ensures accessibility regressions are caught before code reaches production by enforcing quality gates, structured reporting, and layered automated + manual testing across all pages and user preferences.

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EpisodicRAG初期セットアップ（対話的）

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WeChat Mini Program development skill for building, debugging, previewing, testing, publishing, and optimizing mini program projects. This skill should be used when users ask to create, develop, modify, debug, preview, test, deploy, publish, launch, review, or optimize WeChat Mini Programs, mini program pages, components, `tabBar`, routing, navigation, icon assets, project structure, project configuration, `project.config.json`, `appid` setup, device preview, real-device validation, WeChat Developer Tools Nightly workflows, `wechatide` CLI, WeChat IDE Skills/MCP, console/network debugging, `miniprogram-ci` preview/upload flows, or mini program release processes. It should also be used when users explicitly mention CloudBase, `wx.cloud`, Tencent CloudBase, 腾讯云开发, 微信云开发, or 云开发 in a mini program project.

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Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

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Use for Electron desktop application implementation, local packaging, and macOS Electron installer builds in GitHub Actions. Covers secure IPC, preload and multi-process architecture, electron-builder/Forge configuration, native modules, signing/notarization setup, DMG/ZIP packaging, mounted packaged smoke, and macOS qualification evidence. For cloud releases, this Skill owns macOS build and qualification; use github-desktop-release for Windows GitHub Actions qualification and for shared artifact promotion, GitHub Release publication, resume, or authoritative readback. Do not use this Skill to build or qualify Windows installers in GitHub Actions.

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Scaffold backend API, data models, ORM setup, and endpoint inventory with OpenAPI output.

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Integrate authentication and authorization flows with provider-specific setup and RBAC safeguards.

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Read-only first troubleshooting workflow for Python project deployments, including systemd startup failures, dependency issues, encoding problems, permissions, proxy setup, and readiness gates.

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GStack developer-experience plan review for setup, local commands, docs, test loops, onboarding friction, and maintainability before implementation.

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GStack developer-experience review for implemented repositories and workflows, focused on setup friction, command reliability, docs gaps, and maintainability.

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Produces a deep, honest peer-review of how someone uses Claude Code by statistically analyzing their local session data (~/.claude/usage-data/ and ~/.claude/projects/). Trigger whenever the user asks to review, analyze, audit, or critique their own Claude Code usage, workflow, habits, or skill level — including phrases like "analyze my cc usage", "review my cc sessions", "peer review my cc workflow", "deeper than /insights", or any ask for an honest audit of their AI workflow. Also covers portfolio/hiring-manager framings (e.g. "portfolio for Anthropic/OpenAI/xAI"), but ALWAYS ask the user in Step 0 which version to build (self / hr / both) before running — never silently produce an HR report, because that version goes to outsiders and needs explicit privacy setup. The HTML report is laid out ledger-first for SELF (opening band, output/team/leak/trend ledgers, then peer review, 9-dim scoring, try-this-week, case study, claim-indexed evidence). The HR variant is a recruiter version v1: identity card, earned badges (threshold-based, earned-only), allowlist-filtered output ledger, one case study, and a methodology & scope disclosure — no scores, no peer-review memo, no charts.

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Use when an OpenAI API request fails or the user asks what an error means, including blocked access to api.openai.com, 401 invalid_api_key, missing OPENAI_API_KEY, 429 insufficient_quota, 429 rate_limit_exceeded, or 403 model_not_found. Classify the failure, name the next step, route credential setup to openai-platform-api-key, and current guidance to openai-docs.

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When the user wants to set up, improve, or audit analytics tracking and measurement — "GA4," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "tracking plan," "attribution," "Mixpanel," "Segment," "are my events firing," or how to measure marketing results. For A/B test measurement, see ab-test-setup.

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When the user wants to plan, design, or implement an A/B test or experiment — "split test," "variant copy," "multivariate test," "hypothesis," "statistical significance," "how long should I run this test," or comparing two versions. For tracking implementation, see analytics-tracking. For page-level conversion optimization, see page-cro.

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Enable code intelligence (go-to-definition, find-references, hover, type info) for any programming language by installing and configuring an LSP server for Copilot CLI. Detects the OS, installs the right server, and generates the JSON configuration (user-level or repo-level). Use when you need deeper code understanding and no LSP server is configured, or when the user asks to set up, install, or configure an LSP server.

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