「exa」の検索結果

Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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。

LoongCollector E2E Testing Framework Development Guide. Use this rule when you need to understand E2E testing framework architecture, develop new test behavior functions, or extend testing capabilities. Contains detailed BDD testing framework usage, test behavior function development and registration workflows, and comprehensive reference of existing testing capabilities. Example: When adding custom test behaviors for new plugins, use this rule to understand how to write and register new test functions. Example: When developing E2E tests, use this rule to understand the e2e framework.

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 hands over a dsh plugin repository (or a real migration commit / version corridor) and wants its upgrade experience extracted into one auto-graded Harbor benchmark exam task — produce tasks/<id>/ (fixture + instruction.md + task.toml + judge.mjs + solution) that harbor run can grade 0–1 and that folds into the dsh-plugin-upgrade-skill benchmark suite; also applies to turning existing version cards (references/v*.md) into executable exam tasks. Not for writing upgrade cards; not for running the benchmark.

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 feature development using Outside-In TDD with Hexagonal Architecture. Design emerges through inline code, in-memory fakes, interface extraction, and deferred I/O. Use when building features, writing tests, or structuring backend services. Triggers on: TDD, outside-in, hexagonal, ports and adapters, emergent design, acceptance test, component test, walking skeleton, in-memory fakes, component, contract test, adapter, fast tests, sub-second feedback. Language-agnostic (Go, Rust, Python, TypeScript, Java, C#).

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。

Few-shot example generation and optimization for improved LLM performance

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。

Teaches how to reason from a transaction protocol’s rules to a working model. Use when analyzing a concurrency-control paper, spec, or algorithm to identify state, metadata, invariants, operation rules, examples, counterexamples, guarantees, false aborts, unsafe commits, or tradeoffs before inspecting concrete traces.

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。

Screenplay format, page craft, the writing process and adaptation (剧本格式/写作流程/改编) — merged from Wendy Henson (spec format rules), Richard Walter (page craft, revision), Neill Hicks (selling vs shooting script, draft chain), Syd Field (master shot, card method, adaptation as original work), Robert McKee (step outline → treatment → screenplay), Julian Hoxter (format elements, adaptation four questions), Diamond & Weissman (one-page nine-step) and Eric Bork — plus an exact typographic grid, element conventions (V.O./O.S., MORE/CONT'D, dual dialogue), a machine-writable output contract (Fountain, with forced markers for Chinese), and Asian industry formats (Chinese 场号制 影视剧本格式, Japanese 柱・ト書き・セリフ / 決定稿). Use when formatting a spec script, choosing the output file format, deciding what goes in action lines, planning drafts and outlines, cutting pages, adapting a novel, play or true story, writing a Chinese TV/film or Japanese-style script page, or preparing a submission-ready draft.

Stress-test a decision or claim through a sharp, fair Q&A — the questions a good lawyer or skeptical friend would ask before you commit. Use when asked to cross-examine me, ask me hard questions about this, interrogate my plan, or make me defend this. Produces a sequenced line of probing questions (from clarifying to challenging to the killer question), space to answer, and a debrief on where your answers were strong, evasive, or exposed a gap — so weaknesses surface in private before they surface in public.

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 preparation for the Chinese postgraduate entrance examination (考研): choosing target schools and programmes with realistic odds, a phased study plan for the national subjects and the specialist papers, and preparation for the re-examination (复试) and adjustment (调剂). Use when asked 考研怎么规划, 帮我做考研复习计划, 择校择专业, 考研时间线, 复试怎么准备, 调剂, or plan my kaoyan. Produces a school-and-programme shortlist method with the data to collect, a month-by-month study plan by subject, weekly templates, the key-date checklist to confirm against official notices, and a 复试 and 调剂 preparation guide.

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。

Practise the structured interview (结构化面试) for Chinese civil service and public institution posts (公务员面试 / 事业单位面试): the common question types, a clear answer structure for each, timed mock rounds and feedback on content, structure and delivery. Use when asked 公务员面试怎么准备, 结构化面试题, 帮我模拟面试, 综合分析题怎么答, 应急应变题, or practise the civil service interview. Produces a question-type guide, answer frameworks with worked examples, a timed mock interview asked one question at a time, scored feedback, and a practice plan up to the interview date.

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。

Build the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, my AI results are mediocre, or how do I get it right the first time. Produces the specific context this task needs (who/what/constraints/examples/format), a reusable primer you can paste ahead of the request, the difference between a starved prompt and a well-briefed one, and what to leave out — turning vague back-and-forth into a strong first result.

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。

Eval and improve a skill against golden cases — run the target skill blind in a fresh, context-free subagent on each example input, grade the artifact against the expected outcome, and let the gaps drive the edits. Use when the user wants to test/eval/improve/harden a skill, says "this skill keeps producing X / keeps missing Y", or hands a skill plus example input→expected-output pairs. Pairs with [write-skills](../write-skills/SKILL.md) (the authoring principles every fix obeys).

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。

Codex-native Amazon PPC setup workflow using Wilco's exact-match and analytics-first strategy. Use when the user wants stricter keyword control, exact-match campaigns, and a LaunchFast-driven bulk-sheet export.

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。

Record a decision, document existing code, or file a supplied research material. Modes: document decision (ADR, RFC, or rule), document code (spec, doc, guide, or scenario for existing behavior), document research (only when a finished report or one external material is already in hand). Use for 'we decided', 'record this decision', 'document why we chose X', 'make it our standard', 'draft an RFC', 'should we switch to Y' proposals, 'resolve the RFC', 'we accepted the proposal', 'document the auth module', 'capture how the payment system works', reference material, how-to instructions, or a user flow with examples over an existing spec. Name any document type inside the subject — journey, prd, idea, or cpat included — to get exactly that type. Planning a feature or an unnamed intended user journey → /archcore:plan. Checking docs against code or docs health → /archcore:review.

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。

Find, show, open, or identify shipped MathWorks example models that demonstrate a concept, block, or application domain, and return the command to open 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。

Use when generating or editing images with Ideogram models on Scenario via MCP: posters, logos, menus, packaging, or signage with exact in-image text, editing an image in place while keeping its exact size, transparent PNG generation, background removal that keeps hair and glass edges, editable text layers for localization, or one consistent character from a reference. Keywords: Ideogram 4.5, Precise Edit, V4, V3, typography, aspect ratio, layerize, character reference, inpainting.

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。

Run a comprehensive technical SEO audit covering crawlability, indexability, rendering, site architecture, structured data, page experience, security, and internationalization. Use this skill whenever the user asks about technical SEO, crawl issues, indexing problems, sitemaps, robots.txt, canonical tags, schema markup, page speed, Core Web Vitals, hreflang, redirects, or site-wide search performance. Triggers on technical SEO, site audit, crawlability, indexability, sitemap, robots.txt, canonical, redirect chain, schema, JSON-LD, Core Web Vitals, page speed, hreflang, mobile usability, HTTPS, security headers, render-blocking, JavaScript SEO. Also triggers when a site has indexing problems, traffic drops, or migration concerns, even if 'technical SEO' is not said explicitly.

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。

Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.

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 you want to integrate an external tool, API, MCP server, or service into a project — the wizard walks you through auth, config, env vars, client wrapper code, example usage, and an optional smoke test. Scoped to Next.js and Rails projects. Interactive Q&A — starts with the tool name, asks structured questions until the integration is specified, then scaffolds files. Examples — Stripe, Kit, Sanity, Notion, Neon, Supabase, Resend, Postmark, Twilio, Anthropic, OpenAI, Vercel Blob, custom internal APIs. For MCP servers, also handles the .mcp.json wiring. Triggers on "/toolify," "integrate X," "add X to this project," "wire up X," "set up the X integration," "hook up X," "connect X," "add MCP for X." Part of the -ify trifecta (skillify / toolify / loopify). NOT for adding new SKILL.md files — that's skillify. NOT for cron/agent loops — that's loopify.

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。

Create self-explanation prompts that deepen understanding of worked examples, texts, or diagrams. Use when students read material passively without engaging with underlying principles.

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。

Scaffold a ready-made AI agent harness in one command from the 19 published @metaharness/* example packages — 9 host integrations (Claude Code, Codex, Hermes, pi.dev, OpenClaw, RVM, Copilot, OpenCode, GitHub Actions) + 10 vertical pods (devops, research, trading, support, legal, coding, education, sales, gaming, repo-maintainer).

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 mandates for acceptance tests - hexagonal boundary, business language abstraction, user journey completeness, pure function extraction, 3 Pillars (domain language / chained narrative / production composition), and the layered ATD discipline (Universe-bound assertion, layer-dependent PBT mode, two-tier acceptance, example-based sad 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。

5-layer agent output validation, I/O contract specification, vertical slice development, and test doubles policy with per-layer examples

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。

Hexagonal architecture patterns with pure core and side-effect shell for functional codebases

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。