7,594 件 ・ 人気順
概要と使いどころ
Create, inspect, validate, explain, and improve Ralph hat collections. Use this skill whenever the user asks to make or refine a `.ralph/hats/*.yml` workflow, debug hat routing, explain event topology, or tune a multi-hat Ralph run.
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。
Lists all code tasks in the repository with their status, dates, and metadata. Useful for getting an overview of pending work or finding specific 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。
Generates structured .code-task.md files from descriptions or PDD implementation plans. Auto-detects input type, creates properly formatted tasks with Given-When-Then 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。
Add one bounded feature to an existing app while preserving current behavior. Do not restart the full new-project workflow.
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。
Select the appropriate planning, implementation, or debugging workflow for an app 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。
Generate personalized cold email sequences (7-14 emails) with A/B test subject lines, follow-up timing recommendations, and integrated social proof. Creates multi-touch campaigns optimized for response rates. Use when users need outbound email campaigns, sales sequences, or lead generation emails.
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 create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-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。
Quickly assemble a temporary AI agent team for a task. Automatically select the most suitable members from .claude/agents/.
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。
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
Sub-skill of microsoft-365-agents-toolkit. Routed expert system with 100+ micro-expert files for migrating Slack bots to Teams, cross-platform bridging, and dual-platform bot development. USE FOR: migrating Slack bot to Teams, adding Teams support to Slack bot, building dual-platform bots, converting Block Kit to Adaptive Cards, identity/OAuth bridging, deploying bots to Azure or AWS, configuring AI model providers. DO NOT USE FOR: general web development, non-bot projects, standalone Teams development without Slack (use parent skill 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。
POST Aegis events to webhook URLs
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。
Fire Aegis detection events in Home Assistant
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。
Publish Aegis events to MQTT broker
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。
All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.
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。
QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or working within QIIME2 ecosystem.
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。
Variant calling with GATK HaplotypeCaller following best practices. Covers germline SNP/indel calling, GVCF workflow for cohorts, joint genotyping, and variant quality score recalibration (VQSR). Use when calling variants with GATK HaplotypeCaller.
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。
Recommend a model and a scoped handoff for a task in Claude Code or Codex. Use when choosing who should handle a task, seeking a second opinion, getting unstuck, or delegating focused work; execute one handoff when requested.
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。
Recommend the right trading workflow, skillset, API profile, and setup path from a natural-language goal. Use this as the on-ramp when a user expresses a trading or investing goal and needs to know which skill/workflow to use, where to start, or whether something works without paid API keys — e.g. "where do I start", "which skill should I use", "I want to swing trade only when the market is favorable", "what works without API keys", "どれを使えばいい", "API キー無しで 使えるものは". Routes and explains only; it never executes trades or auto-runs other skills, and it is honest when no workflow has shipped yet.
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key 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。
Fetch upcoming economic events and data releases using FMP API. Retrieve scheduled central bank decisions, employment reports, inflation data, GDP releases, and other market-moving economic indicators for specified date ranges (default: next 7 days). The script outputs raw JSON or text; the assistant filters, assesses impact, and generates the Markdown report.
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。
Fetch official FXMacroData macro release-calendar events for trade planning, macro regime checks, and event-risk filters. Use before CPI, NFP, GDP, PCE, retail sales, PMI, and central-bank decision windows.
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。
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
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。
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
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。
Delegate planning and execution workflows to gajae-code via the coordinator MCP 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。