agent-god-mode

Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.

Optimize strategy parameters using VectorBT. Tests parameter combinations and generates heatmaps.

Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.

ニュースヘッドラインを入力として18ヶ月シナリオを分析するスキル。 scenario-analystエージェントで主分析を実行し、 strategy-reviewerエージェントでセカンドオピニオンを取得。 1次・2次・3次影響、推奨銘柄、レビューを含む包括的レポートを日本語で生成。 使用例: /scenario-analyzer "Fed raises rates by 50bp" トリガー: ニュース分析、シナリオ分析、18ヶ月展望、中長期投資戦略

Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.

Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets. Use when you have a structured input bundle and want ranked hypothesis cards with experiment designs, kill criteria, and optional strategy.yaml export compatible with edge-finder-candidate/v1.

VectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analysis. Also triggers for openalgo.ta helpers (exrem, crossover, crossunder, flip, donchian, supertrend).

Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.

Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.

Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.

Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.

Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when deciding whether to maintain or sunset existing code.

Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

Builds production-quality UIs. Use when building or modifying user-facing interfaces. Use when creating components, implementing layouts, managing state, or when the output needs to look and feel production-quality rather than AI-generated.

Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.

Refines ideas iteratively. Refine ideas through structured divergent and convergent thinking. Use "idea-refine" or "ideate" to trigger.

Delivers changes incrementally. Use when implementing any feature or change that touches more than one file. Use when you're about to write a large amount of code at once, or when a task feels too big to land in one step.

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.

Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.

Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

Grounds every implementation decision in official documentation. Use when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.

Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.

Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.

Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.

Changelog Generator

This skill should be used when conducting comprehensive research on any topic using the OpenAI Deep Research API. It automates prompt enhancement through interactive clarifying questions, saves research parameters, and executes deep research with web search capabilities. Use when the user asks for in-depth analysis, investigation, research summaries, or topic exploration.

Guide for implementing 1Password secrets management - CLI operations, service accounts, Developer Environments, and Kubernetes integration. Use when retrieving secrets, managing vaults, configuring CI/CD pipelines, integrating with External Secrets Operator, managing Developer Environments, or automating secrets workflows with 1Password.

Mine the highest-converting ad angles from customer reviews, Reddit complaints, support tickets, and competitor ads. Extracts actual pain language, competitor weaknesses, and outcome phrases that real buyers use. Outputs a ranked angle bank with proof quotes and recommended ad formats per angle.

Scrape competitor ads from Meta and Google ad libraries, cluster by hook/angle/format, and surface new creative directions your team hasn't tested. Chains meta-ad-scraper and google-ad-scraper. Use when a marketing team wants to understand the competitive ad landscape before launching a campaign, or wants fresh creative inspiration from what's already working in the market.

Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.

Run recurring AEO (Answer Engine Optimization) visibility checks across ChatGPT, Perplexity, Gemini, and Claude. Compares each run to the previous one to surface visibility changes, competitor movements, and missed query opportunities. Wraps aeo-visibility with delta analysis and trend tracking. Use when a marketing team wants to know whether their brand is winning (or losing) in AI search over time.

Check how visible your company is across AI answer engines (ChatGPT, Claude, Gemini, Perplexity). Profiles a company, generates test queries, runs visibility checks, and tracks trends over time.

End-to-end pipeline for publishing Claude Code lab meetings. Automatically finds/creates Fathom transcript, downloads video, uploads to YouTube, generates fact-checked Russian summary, creates MDX documentation, and pushes to agency-docs for Vercel deployment. Single invocation replaces 5+ manual steps.

Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use for writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing backlog.

Understand the PM-to-Director transition through altitude and horizon thinking. Use when diagnosing scope, time-horizon, or leadership-level gaps.

Deploy Azure Landing Zones using the ALZ Accelerator with AVM (Azure Verified Modules). Use this skill whenever the user mentions Azure Landing Zones, ALZ, Azure landing zone accelerator, AVM modules for landing zones, deploying management groups, hub-and-spoke networking, Virtual WAN, platform landing zones, or asks about Bicep vs Terraform for Azure infrastructure. Also trigger when the user wants to bootstrap CI/CD for Azure platform deployment, set up management groups hierarchy, or deploy connectivity/identity/management platform subscriptions.