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概要と使いどころ
Best practices for creating GitHub pull requests including conventional commits, PR formatting, and multi-language support (en/ja). Use when creating PRs, writing PR descriptions, or formatting commit messages.
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。
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
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 for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex.
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。
DeFi yield evaluation including fee APR, real vs nominal yield, net APY after costs, and yield sustainability 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。
Professional trading charts including candlesticks, equity curves, drawdowns, correlation heatmaps, and return distributions
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。
Solana transaction construction including instruction building, account resolution, compute budget, priority fees, and versioned transactions
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。
[STUB] Regulatory report generation including IRS Form 8949, Schedule D, FinCEN FBAR, and state-specific crypto reporting requirements
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。
AMM liquidity provision mathematics including constant-product, concentrated liquidity, price impact, and LP share calculations
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。
Multi-method cost basis computation including specific identification, FIFO, LIFO, HIFO, and proportional average cost with partial sell handling
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。
[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options
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。
Trade sizing methods including fixed fractional, volatility-adjusted, Kelly criterion, and liquidity-constrained sizing
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。
Market sentiment extraction from social media, news, and on-chain data including mention velocity, fear and greed indices, and influencer tracking
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。
Solana DEX swap execution via Jupiter aggregator including quoting, transaction building, signing, and confirmation
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。
Feature construction from market data for ML trading models including price, volume, on-chain, and microstructure 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。
Mean-reversion strategy tools including Hurst exponent, half-life estimation, z-score signals, ADF testing, and Ornstein-Uhlenbeck modeling
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。
Crypto-native indicators including NVT ratio, exchange flow, funding rate signals, holder momentum, and smart money flow
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。
Portfolio-level performance measurement including return metrics, risk metrics, risk-adjusted ratios, rolling analysis, and HTML reports
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。
Cross-asset correlation analysis including rolling correlation, hierarchical clustering, tail dependence, and regime-dependent correlation
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。
AMM pool mechanics comparison across Raydium, Orca, and Meteora including fee structures, pool types, creation patterns, and volume efficiency
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。
Reinforcement learning for trade execution optimization including order splitting, adaptive timing, and impact minimization
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。
Market data preparation including OHLCV resampling, gap handling, anomaly detection, normalization, and multi-source merging
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。
Read from a UModel object-graph semantic layer with the `umctl` CLI (MCP alternative noted). Three kinds of read: (1) entities & relationships / topology (`.entity`, `.topo`) and (2) the model itself (`.umodel`, and `.entity_set` methods, including entity-linked `list_skills`) return real rows; (3) metrics & logs (`get_metrics` / `get_logs`) return an executable *plan* — PromQL / Elasticsearch DSL with the entity id pre-substituted — that you run against the backend. Against a PaaS endpoint the same calls return data rows instead of a plan. Use to query or read UModel entities, relations, topology, or model metadata; to read a service's metrics or logs; to look up services and dependencies; or to discover what objects, datasets, and methods exist. For root-cause analysis on top of these reads, see the `umodel-rca` skill. Triggers: UModel, object graph, .entity / .topo / .umodel / .entity_set, query entities, read topology, read metrics / logs, get_metrics / get_logs, list services / dependencies / datasets / skills, 实体查询, 关系/拓扑查询, 读模型, 读指标, 读日志, 查指标, 查日志, 查服务依赖.
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。
Run the post-implementation quality assurance workflow including tests, code polishing, review, and commit. Use when the user asks to "finalize implementation", "finalize changes", "wrap up implementation", "finish up", "ready to commit", or "run QA 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。
Transfer full task ownership to a fresh agent with a verified brief and explicit release. Use for replacing the current executor, including a directly assigned task with no work card; not for supervising a helper.
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。