「writing」の検索結果

Migrate Databricks workloads from classic compute to serverless compute. Use when migrating notebooks, jobs, pipelines, or Scala JARs (`spark_jar_task`) from classic clusters to serverless, checking if existing code is serverless-compatible, or writing new serverless-compatible code. Provides concrete fixes for the serverless Spark Connect architecture and guides the full migration. Not for classic DBR version upgrades or cluster configuration changes within classic compute.

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Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

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MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimize_prompts() with GEPA for automated prompt improvement.

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Analyze test coverage gaps and generate tests to improve coverage. Use when improving test coverage, finding untested code, or writing missing tests.

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Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.

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A/B test subject line variations using proven copywriting frameworks. Predict open rates based on historical performance.

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Turn an RFP and a folder of your past proposals, case studies, and capability docs into a requirement-by-requirement compliance matrix and a drafted response. Flags disqualifiers and unanswerable requirements before you burn a week writing.

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Use before writing code against a library, SDK, API, or framework whose current version you are not certain of — especially fast-moving ones. Trigger when an import fails, a method does not exist, a config key is rejected, a deprecation warning appears, or the user says the code was written against an old version.

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Mine ALL past Claude conversations to build a living 'User Manual About You'. Extract writing style, business context, goals, preferences, and patterns. Make all other skills smarter with context.

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Use when an AI coding agent is writing or refactoring production code and its known failure modes need to be held in check — over-engineering, silent scope creep, invented APIs, claiming work is done without checking, deleting tests to make them pass. Trigger when the user asks for careful, production-grade, or reviewed code, or when a previous agent run produced confident output that turned out wrong.

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Drive the agentkit CLI (aliases agentkit / ak) to scaffold, build, deploy, and manage agents on Volcengine AgentKit from the terminal — runtimes, knowledge bases, memory collections, tools, harnesses, invocation, SSO auth, sandboxes, and evaluation datasets. Use when a user wants to create/deploy an agent project, call or inspect a deployed runtime, manage AgentKit resources, or resolve a CLI/auth/deploy error. Does NOT handle non-AgentKit deployment, general Docker/k8s operations, Volcengine IAM management, or writing agent application code (use veadk-agent-development for that).

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ランディングページ、ホームページ、料金ページ等のマーケティングコピーを作成・改善するスキル。 「コピーを書いて」「LPのコピー作成」「ヘッドライン考えて」等のリクエストで発動。 For email copy, see email-sequence. For popup copy, see popup-cro.

How to query a Well workspace correctly — discover the schema first, then query the right root. Use whenever the user asks about their invoices, companies, contacts, bank transactions, accounts, or accounting ledger in Well, or before writing any well_query_records call.

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Swift concurrency patterns — actors, structured concurrency, cancellation, async streams, GCD migration, strict-concurrency diagnostics, common bug patterns. Use when writing, reviewing, or debugging concurrent Swift code.

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Swift Testing patterns — structs over classes, async confirmations, parameterized tests, exit tests, attachments, common agent mistakes. Use when writing, reviewing, or migrating Swift Testing code.

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SwiftData patterns — autosave, relationships, dangerous predicates, CloudKit constraints, indexing, class inheritance. Use when writing, reviewing, or debugging SwiftData code.

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Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Scaffolds a 7-part skeleton with a scope and non-overlap statement, summary-table stubs and reporting-guideline wiring, without inventing citations. Original research is /write-paper.

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Use when a manuscript or response-to-reviewers letter reads as AI-written. Scans for 27 AI writing patterns and rewrites flagged passages, preserving technical accuracy and bounding how much text changes. Not general copy-editing; that is /polish-language.

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Use when turning a folder of research PDFs into Obsidian notes, even if Obsidian is not named. Writes one templated literature note per paper and extracts cross-linked atomic concept notes, never overwriting existing ones. A .bib or Zotero library is /lit-sync.

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Use when managing a manuscript project over time. Scaffolds the project structure, tracks writing progress across phases, maintains project memory files, and generates submission checklists and backwards timelines (commands init, status, sync-memory, checklist, timeline).

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Creates clear, testable specifications from feature descriptions with user stories. Use when starting a new feature and needing a spec before planning.

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。

Python testing patterns with pytest, fixtures, TDD, mocking, async and integration tests. Use when writing or auditing a Python test 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。

Extracts writing style patterns from exemplar text into a reusable profile. Use when creating a style guide or learning a specific author's voice.

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。

Updates documentation after code changes with quality gates, slop detection, and accuracy checks. Use when code changes require corresponding doc updates.

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。