「how to」の検索結果

Search the agent skills ecosystem to discover and install skills that extend AI coding agent capabilities. Use when user asks "how do I do X" (X being a common task), "find a skill for X", "is there a skill that can...", or expresses interest in extending agent capabilities. Triggers on "find a skill", "install a skill", "skill for [task]", "can you do X", "I need help with [domain]", "how do I [task]". Do NOT use when user has explicitly asked to proceed without a skill, or when the task is better handled by agent's built-in capabilities (file operations, git, basic coding).

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。

Revenue-Centric Design (RCD) — evidence-backed principles for making a SaaS or startup product convert, retain, and monetize. Use when the user works on a landing page or CRO ("my page isn't converting"), onboarding/activation ("users sign up but don't stick"), churn/retention ("customers keep canceling"), pricing/monetization ("how should I price this"), checkout/forms ("dropdowns kill conversion", "annotated checkout"), dashboards/data viz ("cognitive load", "KPI shortlists"), positioning/ICP/go-to-market, feature scope, A/B-test rigor, or AI-era differentiation — or asks for the behavioral-science mechanism behind a design choice. Also use when another skill needs the principle or evidence behind a conversion/retention/pricing/checkout move. Never apply to gambling, betting, or casino products.

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。

Show images in terminal using the Kitty image protocol. TRIGGER when show/view images in terminal, display plot results.

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。

Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"

Cross-cutting: when something breaks. Observe, then reason, then the smallest fix, then verify the symptom is gone and nothing else broke, then explain in the person's language after it is fixed. Never show a raw error to a beginner; never blame them.

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。

The judgment layer: when AutoCode acts on its own and when it stops and asks, and how it speaks about decisions and money. iLang v5.0: perception sets the 11 dimensions, the frozen reference function f_v5 sets the mode, the user sees one plain line. Runs before every consequential action.

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。

The methods a financial-ML result has to survive before it is evidence — purged cross-validation with an embargo, triple-barrier labelling, sample uniqueness under overlapping labels, fractional differentiation, meta-labelling, and multiple-testing correction. Written because the invariants were required of quant-researcher and nothing in the project explained how to satisfy them: a rule without a method produces either an invention or a block. Applied whenever a backtest, a feature or a label is being designed or judged.

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。

Cross-cutting: what AutoCode remembers and how every session starts. Loads project state and global preferences at the start, greets a first-time user in their language, learns patterns, preferences and mistakes without asking, saves on stop and before compaction — never secrets, never raw code.

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。

Explain a repository's architecture (modules, routes, storage, services), find risky hotspots, draw a Mermaid diagram of the code graph, or review how far a change reaches, from Cognee's code graph.

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。

Sync the current session from Cognee's session cache into the permanent knowledge graph now (Q&A turns, tool feedback, distilled lessons), so it becomes searchable and shows up in digests. Also runs at session end.

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 how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"

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。

This skill should be used when the user asks to "write a LinkedIn message", "draft a connection request", "help me reach out to someone on LinkedIn", "write an InMail", "message this person", or when the prospect-researcher skill identifies a high-value contact worth reaching out to. Also triggered by "how should I approach [person/company]" in a LinkedIn 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。

Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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。

Route ambiguous software-delivery requests to the smallest useful Ship workflow: one skill, a phase bundle, or /ship:auto. Use at session start, when the user asks how to use Ship, or when they say build/check/ship without a phase.

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。

Show AgentDB health — pattern count, embedder status, cache hit rate, learning gain since init. Use when the user asks "is agentdb working?", "how many memories?", "show agentdb stats", or after long-running sessions to confirm state.

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。

Research how to implement a phase (standalone - usually use /gsd:plan-phase 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。

Plan how to build with You.com. Use when adding web search, content extraction, or research to an app or agent: finds the right You.com API, MCP server, SDK, or docs path (for example Vercel AI SDK, LangChain, Python SDK, or REST) through the `you-discover` tool and Docs 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。

Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.

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。

Routes between five assessment pathways — formative, rubric/criteria, authentic/performance, peer/self, and diagnostic — with validity and equity checks. Use when a teacher needs help choosing how to assess.

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。

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

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。

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.

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。

Reconstruct an open-source project's growth channels, key content, and stage-by-stage attribution from GitHub history and public web evidence. Use this skill when asked to research GitHub star growth, identify launch and amplification channels, explain viral milestones, find representative posts or videos, compare Product Hunt/Show HN/Reddit/KOL impact, or produce an evidence-backed OSS growth attribution report.

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 auditing an agent codebase against the 12-Factor Agents methodology, reviewing LLM-powered system architecture, or assessing agentic app compliance. Triggers on "analyze agent architecture", "12-factor audit", "how compliant is this agent", or "evaluate this LLM app". Also applies when comparing frameworks or planning agent improvements. Not for quick checklists — this performs deep per-factor codebase analysis with file-level evidence.

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。

Drive CI with `odu` — one shared service, reached from a terminal (`odu surface`), from an agent (`odu mcp`), or from a browser. Trigger when the user asks to "run CI", "run the pipeline", "re-run a check", to run named lanes or recipes (e.g. "run fmt and nix", "just the e2e lane", bare selectors like `fmt`/`nix`/`e2e`), or names a recipe by `<recipe>@<platform>`. This skill — not a repo's local `just ci` / `just <recipe>` — is how an odu-run request is served, whichever face you are on.

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。