「drive」の検索結果

Optimize content and site structure for AI-driven search experiences including AI overviews, large language model citations, generative answer engines, and AI assistants. Use this skill whenever the user wants to optimize for AI search, get cited by language models, appear in AI overviews, build llms.txt, structure content for AI extraction, or future-proof their SEO for the shift from blue links to AI answers. Triggers on AEO, GEO, AI search, AI SEO, AI overview, generative search, LLM optimization, llms.txt, AI citation, ChatGPT search, Perplexity, Gemini, Claude search, AI assistant optimization, answer engine. Also triggers when the user expresses concern about AI eating their organic traffic or wants to understand how to remain visible as search shifts.

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OKR design as actually shipped, not as conference-talk theory. Outcome statements that drive decisions, key results that measure the right thing, scoring discipline, mid-quarter recalibration, and the difference between sandbagged OKRs (always 100%) and aspirational OKRs (always 30%) and stretch OKRs (genuine ambition with quarterly accountability). Triggers on OKR design, OKR setting, key result design, OKR scoring, mid-quarter recalibration, OKR cascading, outcomes vs outputs, quarterly planning, goal setting. Also triggers when a team's OKRs are always hit and producing no learning, when OKRs are demoralizing because they were set as fantasy, or when the team uses OKR vocabulary but the practice has decayed.

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 conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B tests, audit a funnel, generate test hypotheses, design experiments, or analyze test results. Triggers on conversion optimization, CRO, A/B test, split test, multivariate test, hypothesis, conversion funnel, funnel audit, experiment design, statistical significance, lift, optimization. Also triggers when the user has a conversion problem and isn't sure where to start, or when test results are ambiguous and need interpretation.

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Designing interactive calculators (ROI calculators, pricing estimators, savings projections, mortgage calculators, custom assessments) that deliver real decision-support value while serving as lead magnets and qualified-traffic generators. Honest about vanity-calculator (no real value), lead-trap (hides the answer behind email), and transparent-decision-tool (gives the result and earns the email through tiered value) patterns. Triggers on calculator, ROI calculator, pricing estimator, savings calculator, custom calculator, interactive tool, decision tool, financial calculator. Also triggers when an audience needs a calculation-driven lead magnet, when a vanity calculator is producing leads but no qualified ones, or when a calculator is being scoped for the first time.

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。

odu MCP server launcher — drive CI from a coding agent. `bin/serve` resolves odu via Nix and runs `odu mcp` in the cwd. See the repo README for the tools/resources and override knobs.

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Iterative measurement-driven improvement loop. Measure, profile, mutate, re-measure, commit. Works for performance, bundle size, complexity, test coverage — anything quantifiable. Use when the user wants to systematically improve a metric through repeated cycles of profiling and targeted changes.

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Provision and drive a `pu` box — an Incus container used as a clean Linux host for CI, builds, and evidence capture. Use when you need to run something on a fresh remote box instead of the user's machine: `nix run` a build, run CI against a real host, capture screenshots/video off-machine, or reproduce on a pristine environment. Covers create/connect/scp/destroy, running remote commands, copying artifacts back, and the no-egress failure mode. Triggers on "pu box", "spin up a box", "run this on a box", "ephemeral host", "pu create/connect/destroy".

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Use this when adding Nix-based local runs for an existing Playwright e2e suite. Provides a self-contained `tests/shell.nix` that uses `nixpkgs-latest` for `playwright-driver.browsers`, plus a justfile entry — works on NixOS where `npx playwright install --with-deps` cannot.

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Configure Kubernetes autoscaling with HPA, VPA, and KEDA. Use for horizontal/vertical pod autoscaling, event-driven scaling, and capacity management.

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。

Search cloud drives for downloadable music resources (songs, albums, lossless audio). Use this skill when the user wants to download a specific song or album. Do NOT use for general music information, lyrics, or recommendations.

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。

Multi-style article creation skill. Supports 5 writing styles (deep analysis, practical guide, story-driven, opinion, news brief), including complete workflow: material collection → outline → content → formatting. Activated when users mention "write article", "write post", "create", or "draft".

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。

Search cloud drives for downloadable film and TV resources (movies, TV series, anime). Use this skill when the user wants to download a specific movie or TV show. Do NOT use for general movie information, schedules, reviews, or recommendations.

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。

Cavekit specification-driven development methodology — the Hunt lifecycle (Draft → Architect → Build → Inspect → Monitor) and how to apply it. Use when starting a Cavekit project, structuring an existing codebase as kits/plans, or routing between sub-skills.

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 data-driven scientific infographics and visual summaries

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Parses error messages, traces execution flow through stack traces, correlates log entries, and applies systematic hypothesis-driven methodology to isolate and resolve bugs.

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, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use deploy-on-aws plugin instead.

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Build, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend/resume, sandboxed or untrusted code execution, AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda skill 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。

Data-driven Scrum Master for sprint health scoring, Monte Carlo velocity forecasting, retrospective analysis, capacity planning, and Tuckman team coaching. Use when facilitating sprint planning, diagnosing velocity, or running retrospectives.

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。

Data-driven sprint retrospectives from git history — velocity, cycle/lead time, contributor insights, and churn hotspots. Use to run a retrospective, analyze team velocity or throughput, or generate a retro report from commit history.

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。

Programmatic page generation at scale using template-based SEO and data pipelines: keyword pattern mining, template architecture, and indexation for 100-100K+ pages. Use when building SEO pages at scale or scoping a programmatic SEO build.

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。

Guide red-green-refactor TDD with test generation, coverage-gap analysis, and multi- framework support. Use when writing tests first, analyzing coverage, generating test stubs, or converting tests between Jest, Pytest, JUnit, and Vitest.

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Run development from an executable specification with traceable requirement IDs and merge-time coverage gates. Use when starting a greenfield feature, reviving a stale spec, or gating merges on requirement coverage.

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Generate API test suites from route definitions across frameworks: auth, input validation, contract, k6 load testing, mocking, and OpenAPI-driven generation. Use when adding new APIs, auditing test coverage, or building regression suites.

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。

Chaos engineering: hypothesis-driven fault injection to surface weakness before users do. Use when designing a chaos experiment, planning a gameday, choosing what to inject, computing blast radius, or building a chaos maturity model.

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。