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Skills to interact with your Dataproc clusters and jobs.

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。

Hand a sub-task to another agent, a specialist model, or a background job.

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 this skill whenever the user wants to create, improve, rewrite, review, tailor, or ATS-optimize a PRODUCT MANAGER resume or CV. Triggers include any mention of 'PM resume', 'product manager resume', 'product resume', 'PM CV', 'product management CV', plain-language asks like 'create my resume', 'build my CV', 'optimize my resume', 'review my resume', 'make it ATS-friendly', 'tailor my resume to this job description', 'help me get hired', the Spanish terms 'hoja de vida' or 'curriculum vitae', or a request to turn product/PM experience into a resume, quantify product impact, write PM bullet points, or prepare a resume for an APM, PM, Senior, Lead, Group, Director of Product, Head of Product, or CPO application. Also use for AI Product Manager, Growth PM, Platform/Technical PM, and Product Owner resumes. Do NOT use for engineering-only resumes, LinkedIn rewrites, portfolios, or cover letters unless the resume is the main deliverable.

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。

Work with the @upstash/box TypeScript/JavaScript SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.

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 the Upstash CLI (`upstash`) from a terminal, shell script, or CI job when no Upstash MCP tools are in the session. Do not load this skill when Upstash MCP tools are available (the Upstash plugin registers mcp.upstash.com) - they already cover creating, listing, renaming, and deleting Redis databases, running Redis commands, usage stats, backups, Vector and Search indexes, QStash schedules and messages, Blob buckets, and Box, so call them directly. Use this skill for shell work the MCP does not do - a CI step or provisioning script that needs `upstash` commands with JSON output, piping results into other commands, `upstash auth login` and API-key setup, team and member management, changing plans, regions, TLS, eviction, auto-upgrade, or budgets, minting temporary S3 credentials for a Blob bucket, connecting a coding agent to Upstash with `upstash setup` (the Upstash plugin, or the remote MCP server plus skills), or when the user explicitly asks for the CLI or for managing Upstash without the console.

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。

Work with any Upstash product, SDK, or tool, including serverless Redis (caching, sessions, leaderboards, key-value storage), Ratelimit (rate limiting and throttling), QStash (message queue, cron schedules, background jobs), Workflow (durable long-running functions), Vector (vector database for embeddings, semantic search, and RAG), Search (full-text and semantic search), Box (sandboxed cloud containers for AI agents, TypeScript/JavaScript and Python), Blob (serverless S3-compatible file storage with direct browser uploads), the Upstash CLI, and no-signup scratch Redis for agents. Use when the user mentions Upstash or needs any of these capabilities in a serverless, edge, or Node.js app.

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。

Work with the upstash-box Python SDK for sandboxed cloud containers with AI agents, shell, filesystem, git, cron schedules, snapshots, and a headless browser. Use when building with Upstash Box in Python, creating a sandbox or isolated environment to run untrusted or agent-generated code, running AI coding agents in containers, giving an agent a cloud dev environment with a shell and repository, browser automation from a box, scheduling recurring jobs inside a box, saving and restoring snapshots, or orchestrating parallel boxes.

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。

Work with the @upstash/workflow TypeScript/JavaScript SDK for durable, long-running workflows in serverless functions, multi-step processes that survive timeouts, retries, and restarts (built on QStash). Use when defining a workflow endpoint with serve(), running steps with context.run, sleeping for minutes to days without holding a function open, calling external APIs with context.call, waiting for an external event or webhook, invoking other workflows, configuring retries, failure callbacks, and a DLQ, controlling concurrency, rate, and parallelism, triggering, cancelling, or inspecting runs with the Workflow client, building AI agents and orchestrators, human-in-the-loop approvals, realtime updates, local development with the QStash dev server, adding middleware, or migrating workflows safely. Also use when the user asks for durable execution, step functions, saga or orchestration patterns, background jobs with checkpoints, or long-running tasks on Vercel, Next.js, Cloudflare Workers, or other serverless platforms.

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。

Write and improve prompts for Kling AI video generation, and pick the right Kling model for the job. Covers image-to-video, text-to-video, multi-shot storyboards, talking avatars from one photo plus audio, motion transfer, video editing of an existing clip, Element Reference for character consistency, Voice Control and voice cloning, native audio and dialogue, first/last frame control, credit and API costs, and troubleshooting failed generations.

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 adding durable execution to a TypeScript project — building retry-safe webhook handlers, background jobs that survive crashes, scheduled tasks, or long-running workflows that outlive a single request. Covers Inngest SDK installation, client config, environment variables, serve endpoints (Next.js, Express, Hono, Fastify), connect-as-worker mode, and the local dev server.

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 streaming durable workflow updates to a UI in real time — live order status pages that animate as steps complete, AI agent token streaming from a function to the browser, log tailing for long-running jobs, or human-in-the-loop approval flows that publish a prompt and wait for a user reply. Covers Inngest v4 native realtime: defining typed channels, publishing from inside step.run, minting subscription tokens via server actions, and consuming the stream from React/Next.js client components.

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 value propositions for candidate customer segments and help the user choose the strongest one. Use when Codex needs to explain jobs, pains, and gains when needed, check niche-positioning prerequisites, ask one question at a time, present multiple value-proposition options, and write user-confirmed outputs into `opc-doc/`.

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。

Turn a feature into well-defined, independently shippable slices — whether it's an epic that needs breaking apart or a single story that needs sharpening into a job story

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。

"Implement Gale-Shapley stable matching algorithm for two-sided matching problems. Use this skill when the user needs to match candidates to positions, assign students to schools, or solve any two-sided preference matching — even if they say 'optimal job matching', 'stable assignment', or 'candidate-position pairing'.".

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 structured behavioral interview guides using the STAR method. Map job competencies to interview questions, provide scoring rubrics (1–5), and include follow-up probes and red/green flag indicators. Use when preparing for hiring interviews or standardizing interview practices.

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 a Flutter feature Product Requirements Document through a structured clarify-plan-draft workflow. Outputs a PRD using the repository template under `.claude/tasks/<feature-name>/prd.md`. Use when the user says "create a PRD", "write requirements", "define the feature", "start a feature spec", or wants to specify a feature before techspec/tasks/start-job.

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。

Implement a single Flutter task following this repository's Riverpod, Freezed, AutoRoute, DTO/entity, codegen, and verification conventions. Reads the task definition, PRD, and tech spec, then executes the implementation. When invoked standalone, verifies the change; when invoked by implement-tasks-sequence, writes code only and leaves verification to start-job/build-verify. Use when the user says "implement task X", "work on task X", or wants to execute a specific task from the task list.

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。

Orchestrates implementation of all tasks for a feature using an agent team. Respects task dependencies, runs tasks in correct order, parallelizes independent tasks. Does NOT build, run tests, or commit at any point — verification is delegated to the caller (typically `/start-job`, which runs `build-verify` and `pr-review uncommitted` afterwards). Use when the user says "implement all tasks", "run the task sequence", "implement the feature", or wants to execute multiple tasks from a task list end-to-end.

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。

Task Breakdown Command. Breaks a feature into discrete, dependency-ordered implementation tasks from a PRD and tech spec. Creates a task list and individual task files with no approval prompt. When run inside the `/start-job` pipeline, return control to that orchestrator so it can invoke the implementation phase. When invoked standalone, stop after generating tasks and prompting for the next step. Use when the user says "break this down into tasks", "create tasks", "task breakdown", or after the tech spec is complete and the user wants to plan implementation.

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。

Open the warm channel for a role the pipeline already assessed. Finds who the user already knows at the company, researches named targets from public professional presence when they know nobody, grades each path honestly, drafts the ask through the voice agent, and writes the contacts into the Referrals table in job_search.md.

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。

Read every application.yaml in the workspace and report the state of the search — the ranked queue, what is waiting on you, what has gone quiet, and the regression of the pipeline's own predictions against actual outcomes. Writes the calibration findings back into job_search.md and preferences.yaml.

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 a targeted resume and cover letter for a role folder that already has a job description and role analysis. Runs iterative adversarial review rounds until the materials stabilize, then hands off for human review before submission.

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 writing or reviewing request handlers, RPCs, or background jobs for production; adding tracing, metrics, or structured-log calls; or making diagnosability decisions

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。

说明如何读取 IELTS Buddy 模考与已提交练习的事实数据；不定义模考解读、诊断或训练优先级。

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。