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概要と使いどころ
This skill should be used when the user asks to "batch LLM requests", "should I use the batch API", "estimate batch vs realtime cost", "design a bulk LLM job", or "process thousands of prompts cheaply".
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 conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
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 you want to monitor known sources on a schedule and feed the good stuff into your second brain. Configure sources once (YouTube, RSS/newsletters, subreddits, Hacker News, Bluesky, Mastodon, X, LinkedIn, keyword searches); each run fetches only what's new, scores it against your stated focus, writes one digest to the vault, and auto-captures high-signal items into raw/. Everything else waits in the digest until you promote it. Modes — run, digest, promote, add / sources / pause, doctor, schedule (daily launchd or systemd job). Triggers on "/radar," "run my radar," "check my sources," "what's new from my sources," "add a source," "monitor this channel," "watch this subreddit," "track this account," "daily digest," "promote item 4," "radar doctor." Complements second-brain (radar fills raw/, second-brain compiles it) and deep-research (standing surveillance vs a one-off dive).
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 native WebMCP tools to edit the project open in Timeline Studio. Inspect clips and available assets, preview and apply multi-track, caption style/position and project framing edits; sample rendered media; run local voiceover, transcription, relighting analysis and depth-video jobs; insert media; undo; save; or export video with progress and cancellation. Use for the live browser editor, not local project-file editing.
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 knowledge for Azure Translator development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using translate/detect/dictionary APIs, Custom Translator, glossaries, document jobs, or Docker containers, and other Azure Translator related development tasks. Not for Azure AI Language (use azure-language-service), Azure Speech in Foundry Tools (use azure-speech), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Immersive Reader (use azure-immersive-reader).
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 knowledge for Azure Sentinel development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring data connectors, KQL analytics rules, Logic Apps playbooks, data lake jobs, or SAP integration, and other Azure Sentinel related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Security (use azure-security), Azure Monitor (use azure-monitor), Azure External Attack Surface Management (use azure-external-attack-surface-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。
Expert knowledge for Azure Stream Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building ASA jobs with Event Hubs/Kafka, Cosmos/SQL outputs, ML/UDF queries, autoscale, or IoT Edge clusters, and other Azure Stream Analytics related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Event Hubs (use azure-event-hubs), Azure Functions (use azure-functions).
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 knowledge for Azure Microsoft Discovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Discovery shared sessions, Bookshelf indexes, secure RBAC/CMK setups, REST jobs, or Docker-based tools, and other Azure Microsoft Discovery related development tasks. Not for Azure Portal (use azure-portal), Azure Resource Graph (use azure-resource-graph), Azure Monitor (use azure-monitor), Azure Cost Management (use azure-cost-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。
Expert knowledge for Azure Import Export development including troubleshooting, limits & quotas, and security. Use when setting CMK via Key Vault, checking drive limits, validating prerequisites, or debugging Import/Export job failures, and other Azure Import Export related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files).
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 knowledge for Azure Batch development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Batch pools, autoscale, private networking, CMK encryption, or CI/CD for HPC/render jobs, and other Azure Batch related development tasks. Not for Azure Container Instances (use azure-container-instances), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Functions (use azure-functions), Azure Virtual Machines (use azure-virtual-machines).
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 creating tailored resumes for job applications - researches company/role, creates optimized templates, conducts branching experience discovery to surface undocumented skills, and generates professional multi-format resumes from user's resume library while maintaining factual integrity
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。
This skill should be used when searching for people/leads using the Prospeo Search Person API. It provides the correct API format, filter types, rate limiting patterns, and state-by-state crawling techniques to overcome the 25K result limit. Use when building lead lists, searching by job title/industry/location, or integrating with Prospeo.
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。
Parallelize independent sub-jobs across fresh-context subagents instead of one bloated context. Use when a goal branches into many independent pieces.
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 economics paper writing assistant synthesizing advice from 50+ top guides by Cochrane, McCloskey, Shapiro, Head, Bellemare, Goldin, Glaeser, Kremer, and other leading economists. USE THIS SKILL whenever the user writes, edits, reviews, rewrites, or structures any economics paper, thesis, job market paper, abstract, introduction, conclusion, results section, literature review, or referee response. Also handles LaTeX formatting, presentations, and paper audits. Covers all paper types (applied, theory, structural, mixed) and all sections.
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 taste evaluation framework — DVF primary filter, Apple/Google/Jobs design principles as explicit scoring criteria, weighted decision matrix, and option ranking for the DIVERGE wave
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。
Opportunity Solution Trees, opportunity scoring, Lean Canvas, JTBD job mapping, and technique selection guide
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。
JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes
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。
Structured persona creation and JTBD analysis methodology - persona templates, ODI job step tables, pain point mapping, success metric quantification, and multi-persona segmentation
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。
JTBD discovery techniques adapted for AI product owner context. Four Forces extraction, job dimension probing, question banks, and anti-patterns for interactive feature discovery conversations.
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。
Conducts Jobs-to-be-Done analysis, UX journey design, and requirements gathering through interactive discovery. Use when starting feature analysis, defining user stories, or creating acceptance criteria.
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。
Monthly, and on its first run it is the whole setup, launched by hand. It discovers what the member actually runs by walking their code roots and reading the registrar, the host, and the hosted database, then writes the inventory, the domains file, the starting budgets, and the opening safe fix rules, seeds the board, builds the dashboard, and registers one scheduled job per routine. It creates no account, buys nothing, and provisions nothing.
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。
Monthly, browser conditional. On its first run it discovers the member's properties from the sites they name, writes the three strategy files, creates every ledger and folder the kit reads, files the opening cards, and registers the eight scheduled jobs. Every month after that it re-reads the evidence rather than its own previous conclusions, rebuilds the topic map and the internal link map, corrects any property fact it can prove wrong, and records every change with the path of the evidence that forced it. It holds publishing and spending unless you released the channel, and it never touches a credential.
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 once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces, reads the member's own already published posts, and builds the voice file from real samples rather than from an idea of a voice, then writes the plan, creates the proof inventory, seeds the opening slots, and registers the recurring jobs. On every monthly run it re reads the evidence the kit produced and rebuilds only what the evidence contradicts. It publishes only where you released the channel, never replies, spends only where you released it, and it never enters a credential.
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 once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces before asking anything, reads the account structure once, writes the plan folder, seeds the board, creates the creative doctrine, builds the dashboard, and registers the recurring jobs. It asks about exactly two things, the monthly ceiling and the daily cap, because those are the two numbers that decide how much money can leave. On every monthly run it re reads the evidence, corrects what the ledgers prove wrong, and reconciles drift.
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。