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Found 3,737 Skills
Design and implement CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, or CircleCI. Use for automated testing, building, and deployment workflows.
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
Type-safe ORM for Cloudflare D1 databases using Drizzle. Use when: building D1 database schemas, writing type-safe SQL queries, managing migrations with Drizzle Kit, defining table relations, implementing prepared statements, using D1 batch API, or encountering D1_ERROR, transaction errors, foreign key constraint failures, or schema inference issues. Keywords: drizzle orm, drizzle d1, type-safe sql, drizzle schema, drizzle migrations, drizzle kit, orm cloudflare, d1 orm, drizzle typescript, drizzle relations, drizzle transactions, drizzle query builder, schema definition, prepared statements, drizzle batch, migration management, relational queries, drizzle joins, D1_ERROR, BEGIN TRANSACTION d1, foreign key constraint, migration failed, schema not found, d1 binding error, schema design, database indexes, soft deletes, uuid primary keys, enum constraints, performance optimization, naming conventions, schema testing
Build conversational AI voice agents with ElevenLabs Platform. Configure agents, tools, RAG knowledge bases, agent versioning with A/B testing, and MCP security. React, React Native, or Swift SDKs. Prevents 34 documented errors. Use when: building voice agents, AI phone systems, agent versioning/branching, MCP security, or troubleshooting @11labs deprecated, webhook errors, CSP violations, localhost allowlist, tool parsing errors.
Expert system designer for tabletop roleplaying games covering dice mechanics, character creation, combat systems, narrative frameworks, GM tools, and playtesting methodologyUse when "tabletop rpg, ttrpg design, dice mechanics, character creation system, combat system design, gm tools, pbta, powered by the apocalypse, forged in the dark, blades in the dark, osr design, old school renaissance, narrative rpg, rules-light rpg, crunchy system, session zero, safety tools, x-card, fail forward, fiction first, player-facing rolls, advantage disadvantage, target number, dice pool, tabletop, rpg, game-design, dice-mechanics, pbta, osr, narrative-games, ttrpg, gm-tools, character-creation, blades-in-the-dark, forged-in-the-dark" mentioned.
Guides self-review of YOUR OWN academic paper before submission with adversarial stress-testing. Core method: 5-aspect checklist (contribution sufficiency, writing clarity, results quality, testing completeness, method design), counterintuitive protocol (reject-first simulation, delete unsupported claims, score trust, promote limitations, attack novelty), reverse-outlining, and figure/table quality checks. Use when: user wants to self-review or self-check their own paper draft before submission, stress-test their claims, prepare for reviewer criticism, or mentions 'self-review', 'check my draft', 'is my paper ready'. Do NOT use for writing a peer review of someone else's paper, and do NOT use after receiving actual reviews (use paper-rebuttal instead).
Run and debug C# MCP servers locally. Covers IDE configuration, MCP Inspector testing, GitHub Copilot Agent Mode integration, logging setup, and troubleshooting. USE FOR: running MCP servers locally with dotnet run, configuring VS Code or Visual Studio for MCP debugging, testing tools with MCP Inspector, testing with GitHub Copilot Agent Mode, diagnosing tool registration issues, setting up mcp.json configuration, debugging MCP protocol messages, configuring logging for stdio and HTTP servers. DO NOT USE FOR: creating new MCP servers (use mcp-csharp-create), writing automated tests (use mcp-csharp-test), publishing or deploying to production (use mcp-csharp-publish).
End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.
Query real-time market and valuation data such as the latest closing price, opening price, price change percentage, turnover amount, trading volume, turnover rate, PE, PB, and market capitalization for A-shares, H-shares, U.S. stocks, and their indices. Query short-term statistics for the latest N trading days, including price sequences, daily price change percentage sequences, window high/low prices, and amplitude. Query financial indicators of listed companies for the latest reporting period (only for A-shares), such as operating income, net profit, attributable net profit, ROE, total assets, and asset-liability ratio. Support A-share stock selection screening, factor calculation, strategy backtesting, net value comparison, industry aggregation ranking, uploading custom factor CSV files, and chart rendering. Currently, H-shares and U.S. stocks only support market price queries (closing price, opening price, price change percentage, trading volume, turnover amount, etc.). Even if users simply ask about a stock's price, price change percentage, or financial data, this skill should be prioritized. Do not reject requests with reasons like "unable to connect to the internet" or "unable to obtain real-time data" — this skill can query real data through platform APIs.
Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Svelte 5 runes, snippets, SvelteKit patterns, and modern best practices for TypeScript and component development. Use when writing, reviewing, or refactoring Svelte 5 components and SvelteKit applications. Triggers on: Svelte components, runes ($state, $derived, $effect, $props, $bindable, $inspect), snippets ({#snippet}, {@render}), event handling, SvelteKit data loading, form actions, Svelte 4 to Svelte 5 migration, store to rune migration, slots to snippets migration, TypeScript props typing, generic components, SSR state isolation, performance optimization, or component testing.