「backend」の検索結果

Start (or restart) a local Temps control plane built from this checkout, and the web dev server (`bun dev`) in `<checkout>/web`. Invoke when the user says "start temps", "restart temps", "launch the server", "kill and restart temps", or asks to bring the local server up after backend changes. Ports, database and data dir are allocated PER CHECKOUT (a "slot") so several worktrees/branches run side by side without killing each other or corrupting each other's schema — the first checkout you start in claims slot 0 (the familiar `:8080` / `:3000`); every other worktree gets its own slot and its own `temps_s<N>` database. Uses the `fast` cargo profile (release semantics, no debug symbols, parallel codegen) for quick rebuilds. Pass `split` (e.g. "start temps split", "/start-temps split") to launch the two-process proxy/console topology for testing that feature.

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Comprehensive code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.

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。

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

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。

Generates user-facing usage statistics, activity summaries, and personalized insights dashboards (weekly recaps, year-in-review, Spotify Wrapped-style). Use when user wants to show usage stats, activity insights, or shareable recap screens. Different from analytics-setup which sends data to a backend — this shows insights to the USER on-device.

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。

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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。

Expert knowledge for Azure Static Web Apps development including troubleshooting, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring SWA APIs to Azure DBs, configuring custom domains/backends, Entra auth, CI/CD, or plan limits, and other Azure Static Web Apps related development tasks. Not for Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Container Apps (use azure-container-apps), Azure Logic Apps (use azure-logic-apps).

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。

Expert knowledge for Azure Load Balancer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring backend pools/rules, SNAT/outbound, dual-stack IPv4/IPv6, health probes, or LB metrics/APIs, and other Azure Load Balancer related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Front Door (use azure-front-door), Azure Traffic Manager (use azure-traffic-manager), Azure Virtual Network (use azure-virtual-network).

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。

Expert knowledge for Azure Durable Task development including best practices, decision making, architecture & design patterns, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when choosing Durable storage backends, versioning orchestrations, using fan-out/fan-in, human approvals, or instance APIs, and other Azure Durable Task related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), Azure Service Fabric (use azure-service-fabric).

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和用户一起把一个功能「看不见的部分」敲定：数据存哪、谁写谁读、怎么加载、怎么保存、默认值和升级、核心执行规则、出问题时怎么办、旧东西怎么迁。每条规则带编号、案例和状态（已定 / 方案里有但你没拍板 / 待你定 / AI 定），用户只回答带案例的新选择题、过目没拍过板的规则；给用户看的是按「你会问的问题」分组的问答卡片（最绕的逻辑配可点的模拟器）；最后请另一家模型只读查边界，问题闭环后封成后端逻辑包，PRD、测试用例和代码审核按规则编号追溯。触发：前端交互已定、用户说「还有很多后端逻辑 / 加载 / 配置要讲清楚」「有没有遗漏的边界条件」「规则讲清楚」；或没有界面但规则复杂的功能（调度、同步、配置、额度、迁移）。分三档用：规则多且互相影响出完整包；少量清楚的变化只出规则表；行为不变的技术修复跳过。不适用于：页面长什么样、怎么排（用 page-solution-design）；写 PRD / 测试用例（本 skill 的规则包是它们的输入）；纯代码重构、性能调优、架构巡检报告。

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。

已有功能的需求变更闭环（门禁式七步）。触发硬条件：要改的功能已经实现并跑起来了。当用户说"改需求""需求变更""调整交互""改功能""重构流程"，或改动容易散到多个文件、碰到鉴权/存储/配置/权限、需要可靠验证 + 回滚方案时使用。流程：锁 scope 写 change brief → 从代码确认当前行为（不靠记忆和假设）→ 影响面与风险评估 + 回滚计划 → 提出新设计等用户批准（**未获批准绝不动代码**）→ 小而局部的 diff → 跑固定回归清单 → 更新文档和决策日志。产出：change brief + 代码 diff + 回归记录 + decision log。不适用于：全新功能从零做（走 issue-pool → page-solution-design（有界面时）→ backend-logic-design（有规则需讨论时）→ prd-test-writer）、只改视觉样式不动任何逻辑（按已有界面直接调整）、新想法还没定要不要做（先用 issue-pool 入池）、写 PRD/测试用例（用 prd-test-writer）、提交推送发版（用 git-push）。注意：本 skill 的七步流程通用于任何项目，但 scripts/impact_scan.sh 与 references/chrome-extension-regression-example.md 是 Chrome 扩展示例；通用回归使用 references/regression-checklist.md，按项目实际选择检查。

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。

User-facing entry point for the wp-rocket issue workflow. Invoke directly to start a delivery run from a GitHub issue number, URL, or raw description. Runs inline in your conversation context; spawns specialist agents (ticket-writer, grooming-agent, challenger, backend-agent, frontend-agent, release-agent, lead-reviewer, qa-engineer) as isolated sub-agents; invokes supporting skills (knowledge-graph, dod, docs, issue-workflow) inline. Routes based on structured JSON outputs from each agent, manages loop counters, handles escalations, and maintains a live HTML run log.

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Run the Definition of Done checklist for the current wp-rocket branch and report PASS/WARN/FAIL with evidence. Two modes: layer 1 (self-correction inside backend-agent / frontend-agent — resolves FAILs before handoff) and layer 2 (independent orchestrator gate — fresh perspective after handoff). Pass layer: "1" or layer: "2" when invoking.

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。

Update developer-facing documentation to reflect code changes on the current branch. Runs as an inline skill inside backend-agent and frontend-agent (step 2.5 of the internal sequence) after implementation and before DOD. Receives the explicit list of changed files from the implementation agent. No-op if no public API changes occurred.

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。

Audit and reorganize a Claude Code / Codex skill library — enforce a naming convention (prefix each skill by which backend or product it touches), rename skills consistently, fix the symlinks and cross-references a rename breaks, and report broken symlinks and stale name references. Use when the user says "organize my skills", "rename these skills", "clean up the skill library", "enforce a skill naming convention", or "fix broken skill symlinks".

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 implementing app attestation, configuring App Check providers, setting up debug tokens, enabling backend enforcement, or managing token refresh.

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。

Add and validate support for a Hugging Face model architecture in the Optimum Intel OpenVINO backend, including exporter configuration, patching, repository tests, 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。

Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI generation.

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。

Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying it.

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 says 'cognee', asks about knowledge graph or graph memory, wants to switch memory backends, or needs a status check, dataset init, or graph view. Covers Cognee endpoints plus the Brain fallback.

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。

Operately frontend data fetching with TanStack Query. Use when adding or changing page loaders, model hooks, Api.* calls, mutations, useLoadedData, Pages.useRefresh, or any web UI backend request. New code must use TanStack. When fixing or extending an existing surface, migrate that surface's API calls to TanStack in the same change.

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 Python backends with explicit dependency direction, ports/adapters, and runtime boundaries. Use when shaping project layout, clean architecture, service boundaries, dependency injection, report rendering boundaries, or transport separation in Python.

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。

Secure Go backend services against common vulnerabilities. Use when implementing input validation, crypto, or SQL injection prevention in Go.

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。

Standardize dynamic application security testing for backend APIs, frontend web apps, and mobile clients. Covers ZAP, Nuclei, Nikto, sqlmap, ffuf, browser automation, mobile proxy interception, and AI-driven curl probes. Use when advising on or running dynamic security scans on local/staging environments.

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Probe for hardcoded secrets, injection surfaces, unguarded routes, business logic flaws, and platform-specific weaknesses across backend (Node, Go, Java, Python, Rust), frontend (React, Angular, Vue), and mobile (iOS, Android, Flutter) codebases. Use when performing security audits, vulnerability scans, secrets detection, or penetration testing.

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。