「engineer」の検索結果

Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations.

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。

Implements infrastructure as code with Terraform across AWS, Azure, or GCP including module development, state management, provider configuration, and multi-environment workflows.

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。

Creates Dockerfiles, configures CI/CD pipelines, writes Kubernetes manifests, and generates Terraform/Pulumi infrastructure templates for deployment automation and GitOps.

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。

Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems with runbooks, experiment manifests, and rollback procedures.

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。

Comprehensive technology stack evaluation and comparison tool with TCO analysis, security assessment, and intelligent recommendations for engineering teams

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。

Comprehensive Test Driven Development guide for engineering subagents with multi-framework support, coverage analysis, and intelligent test generation

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。

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.

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 has evaluation principles or a dataset but needs help choosing the right graders, designing evaluation metrics, creating LLM-as-judge prompts, combining multiple metrics into a composite score, or building an automated evaluation pipeline. Also use when the user mentions grader selection, metric design, judge prompt engineering, rubric design, evaluation pipeline code, or "how to evaluate [X] automatically." Outputs executable OpenJudge pipeline 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。

Design a learning sequence teaching prompt quality — comparing vague vs. refined prompts to show why specificity and context transform AI output. Use when students use AI without understanding why output quality varies.

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 create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'video pipeline,' 'copy this edit,' 'match this video style,' 'reverse-engineer this video,' 'edit like this reference,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.

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。

Restructure any rough build, research, or legal-drafting request into an IRAC-shaped prompt — Issue, Rule, Analysis, Conclusion — optimized for a frontier model. It's the bar-exam framework, repurposed as prompt engineering. The skill leads with the issue and ends with the conclusion (where models weight attention most), forces you to name your constraints and non-goals, and specifies what "good" looks like before a single token is generated. Use it before any non-trivial build, or whenever a vague ask deserves a precise brief.

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。

Android APK unpacking and resource extraction tool for reverse engineering. Use when you need to decode APK files, extract resources, examine AndroidManifest.xml, analyze smali code, or repackage modified APKs.

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 digital and analog captures from Saleae Logic MSO devices. Decode protocols like UART, SPI, I2C from exported binary files. Use when analyzing logic analyzer captures for CTF challenges, hardware reverse engineering, or protocol decoding.

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。

Expert-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.

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 starting Claude Code projects, writing CLAUDE.md/spec.md, dispatching subagents, or requesting Agent Teams parallel development. Covers Spec-Driven Development, Context Engineering, and post-dev workflow.

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。

Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.

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。

Expert-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.

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 runbooks, playbooks, and technical documentation for engineering teams. Use when the user wants to document a process, create a runbook, build operational docs, or formalize any repeatable technical procedure. Triggers on requests like "create a runbook for...", "document this process", "write a playbook", or any technical documentation request.

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。

Seller storefront analysis and competitive intelligence for Amazon. Analyzes seller revenue estimation, product portfolio strategy, growth trajectory, and market positioning. Reverse-engineer successful seller strategies and identify expansion opportunities. Use when the user asks about analyzing sellers, competitor seller analysis, seller revenue estimation, storefront analysis, seller strategy, or learning from successful Amazon sellers.

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。

User-facing entry point for the wp-rocket issue workflow. Invoke directly to start a delivery run from a GitHub issue number, URL, or raw description. Runs inline in your conversation context; spawns specialist agents (ticket-writer, grooming-agent, challenger, backend-agent, frontend-agent, release-agent, lead-reviewer, qa-engineer) as isolated sub-agents; invokes supporting skills (knowledge-graph, dod, docs, issue-workflow) inline. Routes based on structured JSON outputs from each agent, manages loop counters, handles escalations, and maintains a live HTML run log.

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 QA validation on a pull request — boots the local environment, tests acceptance criteria, and optionally posts the report as a PR comment. Standalone entry point for the qa-engineer agent.

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。

Reduce a change to the minimum that solves the problem. Use when code is over-engineered or a diff is bloated.

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。

Capture an architectural decision so the next session (or engineer) knows WHY. Use after any non-obvious technical choice.

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 detailed implementation plans with bite-sized tasks for engineers with zero codebase 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。