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概要と使いどころ
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
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。
Review code changes with GitNexus from a GitHub PR URL or number, a branch/ref or commit range, or local staged, unstaged, and untracked changes. Use when the user asks for a code review, merge-risk assessment, regression hunt, missing-test analysis, or a verdict on whether a PR, branch, commit range, or local diff is safe.
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。
Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
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。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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 in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.
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。
Replace the manual commit-by-commit classification step in `breeze release-management prepare-provider-documentation` with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by inspecting the actual diff, scope multi-provider PRs to the current provider's slice, ask the release manager when uncertain, and apply version bumps + changelog entries. Use during the regular provider release cycle as an alternative to the interactive breeze prompts.
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。
Runs a mock interview for a specific job description. Plays the interviewer in a chosen round (recruiter screen, hiring manager, behavioral, coding, system design, case, product sense, panel), persona and difficulty; asks one question at a time, probes vague answers, and gives quote-backed rubric scores after each answer (coach mode) or at the end (realistic). Model answers use only the user's real experience. Use when the user says "mock interview me", "interview me for this job", "practice interview", "pretend you're the interviewer", "grill me for this role", "run a behavioral round", "quick recruiter screen", "hiring-manager mock", "system design mock" or "case interview practice". With Reactive Resume MCP it reads the application and stories and logs the session. For a story bank, company brief, questions to ask or a real-interview debrief, interview-prep; for scheduling or thank-you notes, job-application-manager; for fixing the resume, resume-tailor; for negotiation practice, offer-negotiation.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for live container runtime analysis, mounted secrets, sidecars, namespaces, init containers, entrypoint drift, and route-to-container resolution. Use when the user asks why a live container differs from manifests, where a mounted secret is consumed, how a sidecar or init container changes runtime state, or which route resolves to which live container. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kubernetes API analysis, service-account trust, RBAC edges, admission and controller behavior, cluster secrets, workload mutation, and namespace-scoped drift. Use when the user asks to inspect kube API permissions, service-account tokens, RoleBinding or ClusterRoleBinding edges, admission webhooks, controller-created pods, secret exposure, or why live workloads differ from manifests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for browser cookies, localStorage, sessionStorage, IndexedDB, Cache Storage, service workers, offline caches, and client-side session persistence. Use when the user asks to inspect browser state, replay cached auth or session behavior, explain why a page behaves differently after load, or trace how stored client state changes requests, rendering, or access. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Cherry-pick commits from chatbox-pro repo to the open chatbox repo, handling mobile-only files, package name differences, and other repo-specific exclusions.
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。
翻译 Chatbox Pro 当前未提交改动、暂存改动或用户指定 commit/range 中新增或受影响的 i18n key。当用户要求翻译、补全与改动 UI 文案相关的翻译时使用。Agent 需要阅读 diff 和组件上下文，遵守 skill 内置 glossary，并直接写 locale JSON；脚本只用于最后校验。
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 competition, identify differentiation opportunities, and develop winning market positioning strategies using Porter's Five Forces, Blue Ocean Strategy, and positioning maps. Use this skill when evaluating competitors, assessing market positioning, identifying sustainable competitive advantages, or preparing competitive strategy analysis for a startup or investor pitch.
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。
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system simultaneously, when establishing file ownership to prevent merge conflicts in a shared codebase, when designing interface contracts so parallel implementers can build against each other's APIs before they are ready, or when deciding whether to use vertical slices versus horizontal layers for a full-stack feature.
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。
Mistake-proof code so misuse cannot be expressed, rather than warning against it. Use when designing an interface, schema, or state machine and the user wants it hard to get wrong ("make invalid states unrepresentable", "so callers cannot screw it up", "type-safe API", "pit of success"); when auditing existing code for footguns ("what could bite us here", "what is easy to misuse", "poka-yoke this repo", "review this diff for ways to get it wrong"); or when a bug has recurred and the fix must close the class rather than the case ("make sure this never happens again", "this is the third time"). Especially for money, auth, permissions, deletion, migrations, and pipelines where failure is silent. Classifies every finding by what happens when the mistake occurs and how the device notices, which is what keeps it from collapsing into generic code 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。
Migration and code evolution instructions generator for GitHub Copilot. Analyzes differences between two project versions (branches, commits, or releases) to create precise instructions allowing Copilot to maintain consistency during technology migrations, major refactoring, or framework version upgrades.
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。
Generates commit messages following the gitmoji convention (https://gitmoji.dev) — picks the right emoji for the intent of the change and writes a well-formed message. Use when asked to "write a gitmoji commit", "add an emoji to my commit message", "which gitmoji should I use", "gitmoji this change", or when a project uses gitmoji-style commit messages. Works from a git diff, staged changes, or a plain description of the change. Generates the message only — does not run git commands.
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。
Intelligent Git Flow branch creator that analyzes git status/diff and creates appropriate branches following the nvie Git Flow branching 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。
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
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 structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
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。
Diagnose OpenViking memory issues by tracing backward from a memory file to its archive memory_diff.json and, when needed, session messages. Read-only; use for incorrect content, wrong paths or owners, missing memories, and unexplained updates or deletes.
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。
Root-cause a reconciliation break to its source transaction or posting — follow the audit trail from the break row back to the originating entry on each side and state what differs and why. Use after gl-recon has classified a break.
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。
Evaluate FX carry trade opportunities by combining spot rates, forward points, interest rate differentials, volatility surface analysis, and historical price trends. Use when analyzing carry trades, comparing FX forward curves, assessing carry-to-vol ratios, or evaluating currency pair opportunities.
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 the smallest visual when prose must carry structure—control flow, call depth, module ownership, or change shape: pseudocode, call tree, component/file tree, Mermaid diagram, or diff. Skip it when prose already answers the question.
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。