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工場の設備・人員・材料・納期を踏まえて生産順序を組み、段取り替えや工程間の負荷を調整し、設備故障や材料不足時の計画見直しを支援するスキル。

• 限られた設備での生産順序の検討
• 設備故障後に計画を組み直したいとき
• ロット量と段取り替え費用の比較

ECC ToolsのGitHub Appで起きるPRの過剰作成や利用上限の抜け、高額モデルの意図しない使用をコードから追い、費用増加の原因と修正を検証するスキル。

• PRの過剰作成の原因調査
• 利用上限を超える同時処理の点検
• 無料枠での高額モデル利用の確認

定期ジョブ、フック、MCPサーバー、外部連携などの設定と稼働状況を証拠付きで棚卸しし、故障や重複、不足を整理して、維持・統合・廃止・修正の優先順位を示すスキル。

• 実際に動いている自動化を確認したいとき
• 故障したジョブや認証切れを探したいとき
• フック・スクリプト・外部連携の重複整理

Microsoft Teamsの会議を要約し、対応事項を抽出します。要約が届かない原因の確認や、保存済み処理の再実行、会議通知の購読管理も支援するスキル。

• 会議の要約と対応事項の抽出
• 会議要約が届かない原因調査
• 失敗した会議処理の再実行

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。

Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.

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。

Find people, companies, posts, jobs, service providers and groups on LinkedIn with the Curviate CLI. Covers `search people|companies|posts|jobs|services|groups`, running a pasted LinkedIn search URL directly, the `group` read commands, pagination with `--all`, and the filter traps that silently return unfiltered results. Use when sourcing prospects or candidates, qualifying companies, finding posts or job postings to engage with, or resolving a group.

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。

BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.

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 job postings, calculate match scores, identify gaps, and create an application strategy. Use when the user shares a job description or asks to evaluate fit, match score, or gaps against a posting.

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。

Unified Minions skill for both deterministic shell jobs and LLM subagent orchestration. Replaces the older `gbrain-jobs` routing intent. Use when: submitting gbrain jobs, shell/background tasks, spawning subagents, checking progress, steering running work, pausing/resuming, parallel fan-out. One durable, observable, steerable queue interface. Also carries the durable-execution doctrine for any operation expected to exceed ~2 minutes: capability ladder, deadman checks that verify the result was reported, and content-addressed stage checkpoints for expensive pipelines.

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。

Turns whatever came out of a discovery conversation — a call transcript, a voice memo, jobsite photos, an RFP document, a set of drawings, or scrappy notes — into a branded, costed proposal, estimate, or statement of work built on the owner's own templates and historical pricing. Routes it for signature and triggers the deposit invoice once it's accepted. Works entirely from uploaded files when no connector is available, producing DOCX and PDF the owner can send themselves. Use this whenever a quote, bid, estimate, proposal, or SOW is the deliverable — including phrasings like "write this up for them," "put together a quote," "I need to bid this job," "turn my notes into a proposal," "respond to this RFP," or "price this out." Reach for it when the owner describes a job they just looked at, even without saying the word quote.

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 job stories using the 'When [situation], I want to [motivation], so I can [outcome]' format with detailed acceptance criteria. Use when writing job stories, creating JTBD-style backlog items, or expressing user situations and motivations.

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 batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding 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。

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

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 — invoked headlessly by the peon eval server; humans should run `peon eval <pack>` instead. Execute one PeonPing reroll job — invoked headlessly by the peon eval server as: "Use the peon-ping-remix skill to execute the reroll job at <path>". Reads the job JSON (scope, category, index, caption), rewrites the affected sound prompt(s) to honor the caption, re-renders via scripts/pack-render.py, and logs the change to eval-log.json.

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 asks why a reported NVFLARE job failure signal occurred: the job failed, stalled, timed out, lost clients, ended with EXECUTION_EXCEPTION, or produced suspicious errors. Diagnose in simulation, POC, or production by collecting bounded evidence and mapping failure patterns to recovery actions.

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 LinkedIn for financial research through opencli: the user's feed, and job search with location, seniority, job type, remote, company, and date filters. Use this skill whenever the user wants to check their LinkedIn feed, see what professionals or analysts are posting about a company, market, or earnings, gauge professional sentiment, or search finance and trading jobs on LinkedIn. Read-only: it cannot post, like, comment, connect, message, or apply.

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。

Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes. Triggers: "BatchClient java", "azure batch java", "batch pool java", "batch job java", "HPC java", "parallel computing java".

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。

Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSITIONING.md, IMPROVE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a clunky product, cut UX friction, sharpen in-app copy, or says 'the app works but feels rough'. Not for code, tests, or hardening - use improve-code-quality (fresh prototype) or remove-technical-debt (aged); no app yet, create-app; needs growth loops, grow-app; marketing-site friction, improve-website; one leaking flow, conversion-optimization. For one framework in isolation, invoke that skill directly.

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 a CV for someone moving into a new field, leading with transferable evidence instead of job titles that do not match. Use when asked to write a CV for a career change, I'm moving from teaching into product, how do I present my experience for a new industry, or my job titles don't fit the jobs I want. Produces a hybrid CV with a targeted summary and a relevant-skills section backed by achievements, a translation table from old-field language to new-field language, and an honest list of gaps with how to close them.

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。

Set up and keep a job application tracker: one master CV, every tailored version, where each was sent, its status, next action and follow-up date, plus a weekly review of what is working. Use when asked to track my job applications, organise my job search, which CV did I send to which company, or what should I follow up on this week. Produces a tracker table (markdown or CSV) with one row per application, a version log linking each to its tailored CV, this week's actions, and a short weekly review of response rates by source.

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-only MusedIn data: open roles and job posts for AI agents, member profiles, the public feed, verification records. No key needed. Trigger phrases: musedin, agent jobs, jobs for my agent, find an agent, agent profile.

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 Descript projects and async Underlord/agent jobs: list projects, submit publish jobs, poll job status. Trigger phrases: descript, video editing, publish video, descript project.

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。

Ports existing Databricks notebooks and jobs to Fabric, covering dbutils to notebookutils, secret scopes to Key Vault, DBFS to OneLake, Unity Catalog mapping to schema-enabled Lakehouses, Jobs and Delta Live Tables to Spark Job Definitions and Pipelines, and Photon to the Native Execution Engine. Use whenever Databricks code has to be converted. For Fabric notebook code that is not being migrated, use spark-cli.

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。