Configures ExDoc for Elixir projects including mix.exs setup, extras, groups, cheatsheets, and livebooks. Use when setting up or modifying ExDoc documentation 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。
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Configures ExDoc for Elixir projects including mix.exs setup, extras, groups, cheatsheets, and livebooks. Use when setting up or modifying ExDoc documentation 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。
Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatStatus, streamText, toUIMessageStreamResponse, addToolOutput, onToolCall, sendMessage.
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。
Quellenbasierte Profile einzelner Wettbewerber aus öffentlichen Informationen erstellen. Nutze diesen Skill, wenn Positionierung, Zielgruppe, Produkt, Preise, Organisation und Belegbehauptungen eines Anbieters zusammengetragen werden sollen, als Kurzbrief, fokussiertes Profil oder vertiefte Recherche. Trennt Tatsache, Anbieterangabe, Schätzung und Hypothese in einem Claim-Ledger, hält Quellen mit Datum fest und beachtet Datenschutz, Datenbankrechte, Urheberrecht und Geschäftsgeheimnisse. Kein Scraping über das Freigegebene hinaus, keine Personendossiers. Für vergleichende Seiten: competitors.
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。
Organische Social-Media-Inhalte für Deutschland und den DACH-Raum planen, verfassen, wiederverwenden, prüfen und messen. Nutze diesen Skill, wenn Posts, Redaktionspläne, Content-Serien oder Kanalstrategien für LinkedIn, X, Instagram, TikTok, Facebook, YouTube oder Mastodon entstehen sollen, wenn vorhandene Inhalte für Social wiederverwendet werden, oder wenn ein Beitrag auf Werbekennzeichnung, Persönlichkeits- und Markenrechte, Alt-Texte und aktuelle Plattformregeln geprüft werden soll. Deckt Briefing, Evidenz, Formatwahl, Interaktion und Messung ab. Nicht für bezahlte Kampagnen und nicht für das tatsächliche Veröffentlichen.
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。
Validate data quality in CSV/Excel files for vehicle insurance platform. Use when checking required fields, validating data formats, detecting quality issues, or generating quality reports. Mentions "validate", "check fields", "data quality", "missing values", or "quality score".
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。
Analyzes and describes vulnerabilities for specific assets and threats within an insurance company risk register context. The output must be highly professional, eloquent, and grammatically impressive, utilizing labelled headings and subheadings.
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。
Generate a state document (context transfer) that allows any fresh AI instance to resume work without conversation history. Use this skill whenever the user asks to checkpoint, create a state transfer, save state, generate a handoff document, create compaction insurance, or says anything like 'snapshot this', 'create a context transfer', 'checkpoint', 'save state for handoff', 'write a recovery doc', or 'transfer context'. Also trigger when the user mentions compaction concerns, session handoff, multi-session continuity, or wants to preserve the current conversation's state. Works for any conversation type: projects, research, debugging, investigations, design sessions, or long-running chats. This skill produces a structured markdown document optimized for AI cold-start recovery, not human notes.
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。
Clean and standardize vehicle insurance CSV/Excel data. Use when handling missing values, fixing data formats, removing duplicates, or standardizing fields. Mentions "clean data", "handle nulls", "standardize", "duplicates", or "normalize".
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。
Manage month-end and year-end close (Monats-/Jahresabschluss) with checklists, task sequencing, and status tracking. Adapted for Swiss OR requirements including MWST and social insurance.
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。
Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.
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。
API endpoint design and testing for vehicle insurance data platform. Use when designing new API endpoints, testing existing ones, validating response formats, or debugging API issues. Covers 11 core endpoints including 3 new pie chart distribution endpoints, parameter validation, error handling, and integration patterns.
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。
Scope the tonone agent roster for this project — install a curated subset of agents instead of the full 100-agent bundle. Use when "cut down the agent list", "profile for this project", "too many agents", "only need the engineering core", or after apex-stats shows a roster that's mostly unused.
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。
Field observation, data collection, and research methods for geographic inquiry. Covers site selection and sampling strategies, field observation techniques (landscape reading, transects, quadrats), survey and interview methods for human geography, GPS and field mapping, environmental monitoring and instrumentation, data recording and field notebooks, ethical considerations in fieldwork, and the integration of field data with GIS analysis. Use when planning geographic field research, designing data collection protocols, evaluating field evidence, or connecting field observations to broader geographic analysis.
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。
Household-scale nutrition planning that treats meals as a weekly system, not a series of independent decisions. Covers macronutrient balance, the plate method, weekly rotation, leftover architecture, pantry-to-plate translation, and the food-safety floor that every meal plan must meet. Use when building a weekly menu, adapting a diet to a new household member, planning for a week of predictable meals on a budget, or teaching a learner how a kitchen feeds people over time.
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。
Designing the household as an operating system. Covers room-function mapping, work-triangle analysis, storage topology, utility flow, and the Richards/Beecher lineage that treats the home as an engineered environment rather than a stage set. Use when planning a new kitchen, reorganizing a room, diagnosing friction in a daily routine, or teaching a learner to see the house as a system with inputs, flows, and outputs.
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。
Media literacy and critical analysis of media messages across platforms and formats. Covers media ecology (McLuhan), encoding/decoding (Hall), news literacy, digital media analysis, propaganda techniques, algorithmic curation, visual rhetoric, and ethical media consumption. Use when analyzing media messages, evaluating news sources, understanding how media technology shapes communication, detecting propaganda, or studying the relationship between medium and message.
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。
Core programming concepts from variables through recursion. Covers data types (integers, floats, strings, booleans, arrays, objects), variables and scope (lexical, dynamic, block, function, global), control flow (conditionals, loops, pattern matching), functions (parameters, return values, closures, higher-order functions), recursion (base cases, call stack, tail recursion, mutual recursion), type systems (static vs dynamic, strong vs weak, type inference, generics), and error handling (exceptions, Result types, defensive programming). Use when teaching, reviewing, or diagnosing issues with fundamental programming constructs.
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。
Techniques for generating novel ideas, reframing problems, and escaping fixed mental models. Covers lateral thinking (de Bono), Six Thinking Hats, random stimulation, provocation operators (PO), analogical transfer, assumption challenging, and divergent-then-convergent thinking cycles. Use when the goal is to produce new options or perspectives rather than evaluate existing ones.
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。
OpenStack Glance image service skill for deploying, configuring, operating, and troubleshooting the VM image registry. Covers image upload/download, format management (qcow2, raw, vmdk, vhd, iso), backend storage selection (file, swift, ceph), image import methods (web-download, glance-direct, copy-image), metadata management, property protections, image sharing between projects, snapshot lifecycle, image caching, and storage usage monitoring. Use when deploying Glance via Kolla-Ansible, managing VM images, converting image formats, or troubleshooting image upload failures.
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 Hierarchical Agent Memory (HAM) — scoped CLAUDE.md files per directory that reduce token spend. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop", "ham metrics clear", "HAM savings", "HAM stats", "HAM dashboard", "HAM sandwich", "HAM insights", "HAM carbon", or "ham sync".
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 maintain Hierarchical Agent Memory (HAM) for Codex using scoped local memory files. Trigger on "go ham", "set up HAM", "ham commands", "ham help", "ham route", "ham remove", "ham update", "ham status", "ham benchmark", "ham baseline start", "ham baseline stop", "ham metrics clear", "HAM savings", "HAM stats", "HAM dashboard", "HAM sandwich", "HAM insights", "HAM carbon", or "HAM audit".
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。
Cat# Skill (ERGODIC 0)
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 professional PyPI-compliant README files in Markdown or reStructuredText. Use when creating a Python package README for PyPI publication, converting between README.md and README.rst formats, validating markup with twine check before publishing, configuring the readme field in pyproject.toml, integrating sphinx-readme to generate PyPI-compatible RST from Sphinx docs, troubleshooting rendering errors on PyPI, or previewing README rendering locally with grip or docutils.
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 exploring unknown structured data files with dasel v3 — discover schema, list keys, find nested values, sample arrays, identify data types across JSON, YAML, TOML, XML, CSV, HCL, INI formats
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。