「owl」の検索結果

结果打包与下载。导航时机：修改压缩包生成、断点续传、Service Worker下载逻辑。

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。

Knowledge base from "Solving a Million-Step LLM Task with Zero Errors" (Meyerson, Paolo, Dailey, Shahrzad, Francon, Hayes, Qiu, Hodjat, Miikkulainen — arXiv:2511.09030). Use when designing long-horizon, multi-step agentic LLM pipelines that need very high reliability, applying Maximal Agentic Decomposition (MAD), first-to-ahead-by-k voting, or red-flagging error correction, estimating cost/reliability scaling laws for multi-agent systems, or studying Massively Decomposed Agentic Processes (MDAPs).

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。

All animation knowledge for HyperFrames — atomic motion rules, multi-phase scene blueprints, scene transitions, broader motion-design techniques, AND the seven runtime adapters (GSAP default, plus Lottie, Three.js, Anime.js, CSS keyframes, Web Animations API, TypeGPU). Use for any motion or animation task: pick 2-4 rules and compose, or load a blueprint, or look up runtime-specific API (e.g. GSAP eases / Lottie player / Three.js mixer). Also covers auditing an existing composition's choreography (animation map) and 24 named text-animation effects. HyperFrames-native: single paused timeline, seek-safe, deterministic.

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。

Use when the user says brain, project knowledge, what do we know about, open tasks, or recent decisions, or runs /brain or /brain-update. SQLite project_brain.db tracker for entities, relationships, tasks, threads, decisions, events.

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 recall', 'search memory', 'what do we know about', 'find related', or 'graph search'. Runs semantic, graph, and lexical search across the Cognee knowledge graph and injects results as agent context.

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 for a knowledge article, wiki page, or entity summary from the brain, or wants to search, list, or review merges across brain DB articles. Generates Wikipedia-style articles from entities, decisions, and emails.

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。

Progressive L1-L6 refactoring hierarchy, 22 code smell taxonomy, atomic transformations, test code smells, and Fowler refactoring catalog

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。

Deep knowledge for Outside-In TDD - double-loop architecture, ATDD integration, port-to-port testing, walking skeletons, and test doubles policy

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。

Gathers knowledge from web and files, cross-references across multiple sources, and produces cited research documents. Use when investigating technologies, patterns, or decisions that need evidence backing.

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。

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

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。

Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.

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。

Single Source of Truth detection — where truth lives in an nWave repo and how to avoid contradicting 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 a team wants to design, audit, or operate an AI Marketing OS — a Brand Hub source of truth, role-based AI projects for leader, content, design, performance, and knowledge, skill chains, ChatGPT plus Claude plus NotebookLM workflows, MCP connectors, a Notion or Drive second brain, ads data loops, SOPs, weekly reviews, and handoffs. Trigger on 'AI marketing OS', 'set up our marketing AI system', 'Brand Hub', 'AI workflow for the team', 'MCP for ads data', 'how do I make AI actually useful for marketing'. Not for — one campaign brief, see `02-campaign-brief-global`; the weekly report, see `07-marketing-report-global`; the brand visual rules, see `46-brand-guideline-global`; the product context file, see `product-marketing-context-global`.

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 working with color naming, color theory, color spaces, color definitions, or any task involving color knowledge - palettes, ramps, gradients, conversions, accessibility, perceptual matching, pigment mixing, print-vs-screen color, CSS color syntax, or historical color terminology. Use this skill whenever the user is choosing, comparing, generating, naming, converting, or explaining colors, even if they do not explicitly ask for "color theory."

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。

Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".

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。

Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."

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。

Intent-driven spec precipitation — state a constraint in natural language (加一条规范：禁止用 any / 记录架构约束：服务间走 gRPC / 质量规则：覆盖率≥80%) and the workflow infers the category and records a <spec-entry>. Spec = 项目约束规则（编码规范、架构约束、质量标准）；可复用知识文档走 /maestro-knowhow capture。Triggers on "maestro-spec add", "记录规范", "添加约束", "添加规则", "加一条规范", "spec add". Terminology：spec = project constraints/rules (<spec-entry>). Reusable knowledge documents use /maestro-knowhow capture. Learning discoveries from /maestro-learn use <learning-entry> tags in learnings.md (separate from spec entries).

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。

Intent-driven issue lifecycle management — describe what you want in natural language (报告一个 bug / 列出开放 issue / 关掉 ISS-xxx / 关联到 task / 扫描发现问题) and the workflow routes to the right operation. Operates on .workflow/issues/. 知识管理走 /maestro-knowledge；knowhow 沉淀走 /maestro-knowhow；约束规则走 /maestro-spec。Triggers on "issue 管理", "报 bug", "记录问题", "issue list", "关闭 issue", "issue discover", "发现问题".

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。

Manage a v3 Session — inspect status/resume-view, review knowledge candidates, complete, archive/unarchive

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。

Intent-driven knowhow precipitation — describe what you want to capture (记一个关于X的决策 / 保存这段代码模板 / 写个部署配方 / 存个调试技巧) and the workflow infers the type and records it into .workflow/knowhow/. Pure capture surface; knowhow 的管理/审计走 /maestro-knowledge；项目约束规则走 /maestro-spec add。Triggers on "knowhow capture", "知识沉淀", "沉淀经验", "记录模板", "记录决策", "adr", "存个技巧".

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。

Searchable Elixir/Phoenix/Ecto solution documentation system with YAML frontmatter. Builds institutional knowledge from solved problems. Use when consulting past solutions before investigating new issues.

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。

Adapts an existing K-12 lesson (math, ELA, science, or social studies) for students at different proficiency levels (below / at / above grade level). Load this skill BEFORE asking the teacher any clarifying question about the lesson, tiers, or student levels. Triggers on explicit asks to differentiate, tier, or scaffold a lesson, and on implicit signals like "my students are at different levels". Produces 1 teacher-facing differentiation plan + 3 student-ready tier documents as editable, printable documents in a single output turn (shared content is written once, so tiers cannot drift). Uses the Learning Commons Knowledge Graph when connected; works without it. This skill adapts a lesson the teacher brings or names. Not for creating a new lesson from scratch — a new-lesson request that asks for differentiated or leveled materials is k12-lesson-plan-creation's job, one package. Not for grading, rubrics, assessment feedback, or quizzes.

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。

Scans lyrics for phrases that may match existing songs using web search and LLM knowledge. Use before release to check for unintentional borrowing.

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。