Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Comprehensive cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, etc.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides comprehensive cryptocurrency research by orchestrating multiple specialized AI agents that analyze different aspects of the crypto market in parallel.
Invoke this skill when the user:
Coordinates 4-12 specialized agents running in parallel:
Research results are saved in timestamped directories:
outputs/
└── YYYY-MM-DD_HH-MM-SS/
├── crypto_market/
├── crypto_analysis/
├── crypto_macro/
├── crypto_plays/
└── crypto_news/
Based on user request or context:
date command to get timestampscripts/setup-output-dir.shAgents are defined in agent-prompts/ directory:
coin-analyzer.md - Receives ticker symbol parametermarket-agent.md - General market analysismacro-correlation-scanner.md - Correlation analysisinvestment-plays.md - Investment opportunitiesnews-scanner.md - News aggregationprice-check.md - Current pricing datamovers.md - Top movers analysisEach agent prompt includes:
See workflows/lightweight.md for implementation details.
When: User asks quick question about crypto Agents: 4 haiku agents Duration: ~30-60 seconds
See workflows/comprehensive.md for implementation details.
When: User needs deep analysis or multiple perspectives Agents: 12 agents (haiku, sonnet, opus variations) Duration: ~2-5 minutes
See workflows/output-only.md for implementation details.
When: Background research or automated workflows Agents: Configurable Output: Files only, no interactive output
Example 1: Specific Coin Analysis
User: "What's happening with Bitcoin?"
Action: Launch lightweight mode with BTC as ticker
Agents: 4 haiku agents analyzing Bitcoin specifically
Output: Quick analysis in ~30 seconds
Example 2: Market Overview
User: "How are crypto markets doing today?"
Action: Launch market-focused agents
Agents: Market agent + movers + macro correlation
Output: Market overview with key movers
Example 3: Investment Research
User: "I'm looking for good crypto investment opportunities"
Action: Launch comprehensive mode
Agents: All 12 agents for multi-perspective analysis
Output: Comprehensive report with opportunities
Coin analyzer agents accept a ticker symbol:
If agents fail or timeout:
For detailed information, see:
reference/agent-design.md - How agents are structuredreference/usage-guide.md - Detailed usage instructionsworkflows/*.md - Specific workflow implementationsまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub 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。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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 unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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 the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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。