「flow」の検索結果

Derive and implement first-principles audio-coupled haptic and kinetic UI feedback. Use when designing, reviewing, or coding haptics/audio for mobile apps, native iOS/Android, React Native/Expo, SwiftUI, games, detent pickers, toggles, sliders, page curls, scroll gestures, wallet/signature flows, Solana transactions, backend/realtime state changes, confirmations, settlements, and semantic UI events where feedback should follow signal math instead of ad hoc vibration calls.

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。

Bun runtime and modern JavaScript backend practices, including Bun-native tooling (bun run/test/build) and PostgreSQL usage guidance. Use when building or reviewing Bun-based services, APIs, scripts, or when Bun-specific workflow questions arise.

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。

GPT Image 2 image generation workflow for this repo MCP server. Use for gpt-image-2, OpenAI image generation, concept art, UCUF reference exploration, UI icon, badge, card art, prompt drafting, transparent-background asset drafts, and saving generated images to local files under artifacts/ui-source or other workspace 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。

Use when the user asks to switch AI role/mode/persona or uses role-trigger words such as Captain, Coordinator, 寫文章, 寫文章模式, 文章模式, 技術文章, 部落格, 出版, 預覽. Routes the request to Project Captain, Publishing Director, or Article Writing Mode, loads the matching keep memory when available, and applies the role's workflow without excessive roleplay.

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。

Local ComfyUI / Stable Diffusion SDXL partial-asset generation workflow. Use for ComfyUI, stable diffusion, SDXL, LoRA, badge, cap, plaque, panel fragment, UCUF partial asset exploration, and saving generated PNGs from the local 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。

UI 資產切件與候選收斂 SKILL — 從使用者提供的整頁 UI、2K 母圖、panel sheet 或單張素材，自動執行全切、auto-classify、auto-pick、temp/selected 分流、背景裁切、透明化與 post-process。USE FOR: 切出 panel / cap / badge / glyph / noise 候選、把未挑選切片集中到 temp 可一次清掃、把高信心候選升到 selected、再接 trim-png-by-background.js / postprocess-ui-asset.js。DO NOT USE FOR: runtime 畫面驗收（用 ui-runtime-verify）、純 icon 規格設計（用 UI-icon workflow）、單純修改 layout/skin JSON。

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。

DALL-E 3 image generation workflow for this repo MCP server. Use for dalle3, DALL-E 3, OpenAI image generation, concept art, UCUF reference exploration, UI icon, badge, card art, prompt drafting, and saving generated images to local files under artifacts/ui-source or other workspace 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。

USE FOR: MCQ, 整併疑問書, 規格整併, 疑點裁決, consolidation-manifest, scan-answers, rewrite-all, doc-id-registry, 討論來源整併。當任務涉及 docs/遊戲規格文件/討論來源/ 內容歸納、衝突轉 MCQ、人工填答後批次回寫相關規格文件時啟用。強制流程: generate -> 人工填答 -> scan-answers -> rewrite-all。DO NOT USE FOR: UI 視覺調整、一般程式除錯、非規格文件任務。

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 or revise AI-learning-notes article pages in "寫文章模式" when the user asks for articles, technical articles, blog posts, bilingual versions, article formatting consistency, shared article-base alignment, responsive layout, summary/TOC decisions, contrast, or publishing-flow compatibility.

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。

Strict routing mode for prompts prefixed with `(best)`. USE FOR: any turn where the user explicitly wants the safest, smallest-context, highest-discipline execution path. This skill must route into context-budget-guard first, then continue into the task-specific workflow.

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。

Deterministic external-evidence web validation workflow for Sanguo ETL/RAG. USE FOR: 外部證據網站檢查、來源健康度、allowlist 驗證、來源 seed 覆蓋、3kweb-check、external evidence source health、fetch/parse/hash first、LLM reviewer second。

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。

Sanguo RAG unresolved mention resolution loop. Use for: 三國 RAG, unresolved mentions, alias review, observed mentions, MCQ triage, manual roster seeds, false-positive exclusion, running run_resolution_loop.py, applying unresolved-triage answers, delegating 三國名詞查證 to a web-capable agent, or Pilot ETL chunk experiments with LangChain text splitters / LangGraph / LangFlow around 張飛長坂橋等小樣本流程。

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。

Agent context budget guard and artifact compression workflow. USE FOR: image-heavy QA, compare board review, screenshot batches, large keep/todo/task manifests, long notes handoff, and md/json diff summarization. Trigger this before reading or forwarding heavy artifacts when token growth is a risk.

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。

Design, build, validate, and ship cross-platform agent skills. Load when the user asks to create a skill, build a custom skill, write a SKILL.md, package a workflow as reusable agent capability, improve or audit a skill, publish a skill, or build a planned skill suite.

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。

Deliver multi-file changes in thin vertical slices — implement, test, verify, commit, repeat. Load when implementing a feature from a plan, building across more than one file, refactoring, or when tempted to land a large change in one pass. Also triggers on "incremental implementation", "vertical slice", "thin slice", "one slice at a time", "don't do it all at once". Routes single-file fixes to direct execution. Pairs with test-driven-development and git-workflow-and-versioning.

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。

Orchestrator for the learn-from suite - auto-detects source type (academic paper, GitHub repo, blog/web article, or in-conversation learnings) and routes to the correct sub-skill for credibility check, security scan, insight extraction, and application. Load when the user says "learn from", "learn from this", "extract insights from", "apply learnings from", "what can we learn from", or provides a URL, file path, or pasted content that should be ingested as knowledge. Single entry point for all learning workflows.

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。

Author pull requests with intent-separated commits, blast-radius disclosure, and verification evidence. Load when opening a PR, writing a PR description, separating refactor from feature commits, or summarizing a change set for review. Also triggers on "write the PR", "PR body", "intent-separated commits", "split refactor from feature", "pr summary", or after safe-change cycles complete. Extends git-workflow-and-versioning — does not replace 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。

Harden an application against common security risks — validate inputs at boundaries, least-privilege access, safe secrets handling, dependency hygiene, and secure defaults. Load when shipping user-facing code, adding auth/session flows, handling untrusted data, exposing APIs, or the user asks for "security hardening", "OWASP hardening", "secure this feature". Not for skill-library security gates (use secure-skill family).

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。

Design state-of-the-art multi-agent systems, orchestration patterns, and wiring from scratch. Load when the user asks to build an agent system from scratch, design agent orchestration patterns, choose between sequential/parallel/hierarchical workflows, or define how multiple agents should collaborate. Also triggers on "agent architecture", "multi-agent wiring", "agent orchestration pattern", "how to connect these agents", "design the communication structure". Called by agent-builder for complex topologies (>4 agents or hierarchical). For process-driven agent design, use agent-builder instead.

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。

Apply validated research paper insights to the current project codebase — improving architecture, code patterns, testing strategies, documentation, or workflows based on empirical findings. Load when learn-from-paper routes insights to the current project, or when the user asks to apply paper findings to this project, improve this codebase with research, use this paper to improve my project, or apply research to my code. Also triggers on "apply this to my project", "how can this paper help my codebase", "use these findings here", "implement paper recommendations", "use research to improve my code". Always called AFTER learn-from-paper has completed credibility and security checks — never ingests papers directly.

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。

Orchestrator for the eval-output skill suite — evaluate LLM and agent outputs for quality, accuracy, helpfulness, and safety using structured rubrics and LLM-as-judge techniques. Load when the user says "evaluate this output", "score this response", "run an eval", "LLM as judge", "evaluate agent output", "how good is this response", "rate this answer", "eval this", or provides an LLM output that should be assessed for quality. Single entry point for all output evaluation workflows.

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。

Quickly understand an unfamiliar codebase or project by mapping its architecture, identifying key components and data flows, and surfacing complexity hotspots. Load when the user asks to understand a repo, explain how something works, map the architecture, onboard to a codebase, or explore how components connect. Also triggers on "walk me through this codebase", "how does this project work", "explain the architecture", "what does this repo do", "show me the structure", "onboard me", or any request to build a mental model of a codebase before making changes.

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 with unified build/test/deploy intent across providers using .agent-loom/deploy.yml and per-provider adapters. Load when the user asks to deploy, ship to preview, release to production, or run a provider-agnostic deploy flow. Also triggers on "deploy anywhere", "deploy to Vercel", "deploy with GitHub Actions", "preview deploy", or "ship this". Runs preflight before any deploy — stops on missing secrets. Pairs with ci-cd-and-automation for pipeline design. Ships vercel and github-actions adapters; extensible adapter interface.

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。

Prisma ORM CLI commands reference covering init, generate, migrate, db, dev, complete, studio, validate, format, debug, and mcp. Use for ORM/database CLI workflows, not the Prisma Platform CLI. Triggers on "prisma init", "prisma generate", "prisma migrate", "prisma db", "prisma complete", "prisma studio", "prisma mcp".

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。