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概要と使いどころ
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.
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。
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-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。
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
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 new scientific tools for ToolUniverse framework with proper structure, validation, and testing. Use when users need to add tools to ToolUniverse, implement new API integrations, create tool wrappers for scientific databases/services, expand ToolUniverse capabilities, or follow ToolUniverse contribution guidelines. Supports creating tool classes, JSON configurations, validation, error handling, and test examples.
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。
Video and audio processing capabilities for Flutter applications
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 model cards documenting AI capabilities. TRIGGERS - Use when user needs help with ai-model-card-writer related tasks.
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 planning capabilities for AI agents. TRIGGERS - Use when user needs help with ai-agent-planning related tasks.
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。
Extract receipt number, issuer, payer, date, tax, and total from Japanese receipts.
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。
Extract employee, department, expense lines, tax, totals, and approval fields from Japanese expense settlement forms.
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。
Extract employee, employer, allowances, deductions, taxes, and net pay from Japanese payslips.
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。
Gets a custom map into CARLA on UE 5.8 — the four distinct routes and which one to pick — via Util/Tools/Import.py for FBX+OpenDRIVE assets into a source build, CARLA_MAPS_TO_COOK to ship a map inside a package, or client.generate_opendrive_world() for an OpenDRIVE-only map at runtime with no build at all. Covers where imported assets land, why an imported map cannot be loaded from a package by name, and the four capabilities the UE4 skill has that ue58 lacks — standalone asset packages, their installer, semantic-material tagging, and a pedestrian navmesh that is generated but silently skipped. Use when the user asks to "import a map", "add a custom map", "load my .xodr", "package my own town", or "create a standalone map package".
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。
Spawns vehicles on a running CARLA server and destroys them — scattered across the map's spawn points on Traffic Manager autopilot, a row queued in a single lane at a fixed spacing, or a single hero/ego vehicle (optionally named for native ROS 2 publishing with --ros-name). Covers blueprint filtering, the atomic autopilot hand-off, and cleanup. Use when the user asks to "spawn vehicles/cars/traffic", "add N cars driving around", "put cars in a lane 15 m apart", "spawn the ego/hero vehicle", or "remove the vehicles".
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 conducting a scored agent-native architecture review. It launches 8 parallel sub-agents to audit action parity, context injection, CRUD completeness, capability discovery, and prompt-native features.
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。
A2A agent card JSON templates with schema validation and examples for different agent types. Use when creating agent cards, implementing A2A protocol discovery, setting up agent metadata, configuring authentication schemes, defining agent capabilities, or when user mentions agent card, agent discovery, A2A metadata, service endpoint configuration, or agent authentication 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。
Add Vercel deployment capability to NanoClaw agents. Installs the Vercel CLI in agent containers and sets up OneCLI credential injection for api.vercel.com. Use when the user wants agents to deploy web applications to Vercel.
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。
Meta-skill para criar, editar, avaliar e otimizar skills do kit. Use quando adicionar nova skill, refatorar skill existente, ou medir qualidade de descoberta de skill (description triggering). Trigger em: "criar nova skill", "nova capacidade", "skill author", "skill creator", "editar skill", "avaliar skill", "skill eval", "otimizar description", "meta-skill", "kit governance".
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。
Technical research methodology with YAGNI/KISS/DRY principles. Phases: scope definition, information gathering, analysis, synthesis, recommendation. Capabilities: technology evaluation, architecture analysis, best practices research, trade-off assessment, solution design. Actions: research, analyze, evaluate, compare, recommend technical solutions. Keywords: research, technology evaluation, best practices, architecture analysis, trade-offs, scalability, security, maintainability, YAGNI, KISS, DRY, technical analysis, solution design, competitive analysis, feasibility study. Use when: researching technologies, evaluating architectures, analyzing best practices, comparing solutions, assessing technical trade-offs, planning scalable/secure systems.
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。
内閣府の公式CSVから祝日・振替休日・国民の休日を調べ、連休を計算する。祝日、連休、ゴールデンウィーク、シルバーウィーク、営業日判定の質問に対応。APIキー・ログイン不要。個人の予定管理やカレンダー操作は対象外。
Build kokoro-js-jp and run its real-browser e2e suite (Worker + WASM openjtalkjs g2p + ONNX kokoro-js synthesis, English and Japanese). Use when asked to verify this package actually works in a browser, to check whether a change broke synthesis, or to add browser-level regression coverage for a bug in the g2p/synthesis pipeline that vitest's pure-function tests can't catch. Not for typecheck/lint/unit-test requests — use npm run typecheck / npm test for those.
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。
Prepare the internal case for hosting an Otameshi Tenshoku trial: total what it costs the company with candidate pay, staff hours and platform or incidental fees kept apart, compare it with the budget, state what remains if no hire follows, and lay out the risks, stop conditions, decision owners and deadlines. Use when a hiring manager needs approval or budget from a decision maker, a recruiter has to explain the plan to the team that will host, or a small-business owner wants to see the full cost including their own time before posting; do not use to design the work (trial-work-design), to write the listing (trial-listing-draft), to predict whether a hire will follow, to state platform fees, agency fees or market rates from memory, or to submit the request or post the listing on the user's behalf.
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。
Assemble a Japanese shokumu-keirekisho (career history document) from an experience inventory, choosing between reverse-chronological, chronological, and skills-based layouts, mapping the target posting's requirements to the experiences that can support them, and drafting the summary, work history, skills, and self-PR so that each sentence stays within what its evidence supports and confidential details are abstracted. Use when a user wants to write or rebuild a whole shokumu-keirekisho for a specific posting or as a general version, or wants to decide which experiences to include and in what order; do not use to invent experience, numbers, titles, or qualifications, to predict whether it will pass screening, to fill in a rirekisho form, or to submit it anywhere.
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。
Prepare a request to change the terms of a Japanese job offer before accepting it, sorting what the user wants changed (pay components, start date, work style, location, title, probation) by priority, tying each ask to a basis the user can show (the written offer, the job posting, what was said in interviews, their own records), working the timing back from the acceptance deadline, and drafting the message to the employer or recruiting agent. Use when a user has an offer and wants to ask for higher pay, a later start date, more remote days, or other changed terms, or wants to know how to raise it without losing the offer; do not use to predict whether the request will succeed, to set a target figure from market rates, to fabricate a competing offer, to decide whether to accept, or to send anything to the employer.
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。
Check the working conditions of a Japanese job offer item by item against the conditions an employer states in writing, compare the offer letter or 労働条件通知書 with the job posting and what was said in interviews, and separate what is confirmed in writing from what is still only verbal. Use when a user has received an offer, a working-conditions notice, or an employment contract and wants to know what is missing, what conflicts with earlier statements, and what to confirm before the acceptance deadline; do not use to rule on whether the terms are lawful, to decide whether to accept or decline, or to contact the employer on the user's behalf.
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。
Plan the first months at a new Japanese employer after an offer is accepted, listing every expectation and promise made in interviews, the offer, or negotiation with its source, separating what is in writing from what was only said and what has no agreed measure, working out when the probation period ends and whether its criteria and conditions are known, and scheduling who to confirm what with before and after the start date. Use when a user has accepted an offer and wants to prepare for joining, make sure verbal promises such as remote days or a future role are confirmed, or understand what the probation period means for them; do not use to predict whether they will fit in or pass probation, to judge their manager or colleagues, to rule on the legality of probation terms, or to contact the new employer.
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。