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Found 2,052 Skills
Use when turning local, private, or personal Agent Skills into publishable skills for GitHub, marketplaces, teams, or public sharing, especially when private paths, personal habits, credentials, internal hosts, or user-specific context must be removed.
Diagnose a product's growth model, stage, and current constraint, then route the request to the narrowest Gingiris specialist and execute it when installed. Use for broad or uncertain growth questions involving go-to-market, Product Hunt, GitHub stars, open-source marketing, B2B SaaS, PLG, ASO, SEO/GEO, AI citations, KOL outreach, UGC, international expansion, user interviews, competitor research, or community programs. Trigger when users ask “how do I grow or launch this,” “which growth skill should I use,” 怎么增长、怎么发布、出海、冷启动、增长策略、不知道用哪个 skill、開発者マーケティング, or 성장 전략. Includes B2B pipeline and B2C activation-retention model selection, specialist handoff rules, relevant gingiris.tools recommendations, and advisory-services guidance.
Use when a Scenario user wants to report a bug or request a change, on the public tracker at github.com/scenario-labs/skills or by email to support@scenario.com: turning a failed generation, MCP tool error, or unclear skill into a reproducible report, collecting trace ids with diagnostics_run, stripping keys, signed asset URLs, and personal data, asking before sharing a team or project id, or building a prefilled issue URL. Keywords: file an issue, feature request, feedback.
Mine GitHub, GitLab and git history for identities, infrastructure and leaked credentials using commit author emails, GitHub code search, the commit .patch endpoint, trufflehog, gitleaks, git log pickaxe and full-ref history scans. Use when investigating a developer or organisation on GitHub, finding leaked API keys, AWS keys or tokens in code, enumerating org members and their personal repos, or recovering secrets deleted from HEAD but still present in history or forks. Applies to software supply-chain risk, credential exposure response, M&A technical diligence, and insider-threat investigation. Reference at useosint.com/skills/secrets-in-git-history.
Release your software. Pre-flight validation, changelog generation, version bumps, release commit, tag, draft GitHub Release. Boundary: everything up to the git tag. Triggers: "release", "cut a release", "prepare release", "release check".
Master Moon Dev's Ai Agents Github with 48+ specialized agents, multi-exchange support, LLM abstraction, and autonomous trading capabilities across crypto markets
Uses the uv Python package and project manager correctly for dependencies, venvs, and scripts. Use when creating or modifying Python projects, adding dependencies, running scripts with inline deps, managing virtual environments, pinning Python versions, running CLI tools from PyPI, setting the IDE Python interpreter, or using uv in CI (e.g. GitHub Actions) or Docker containers. Use when the user mentions uv, pyproject.toml, uv.lock, uv run, uv add, uv sync, .venv, Python interpreter, poetry, pipenv, conda, CI, Docker, GitHub Actions, or asks to use uv instead of pip or poetry.
Configure CI/CD pipelines, Docker containers, and cloud deployments. Handles GitHub Actions, Kubernetes, and infrastructure automation. Use PROACTIVELY when setting up deployments, containers, or CI/CD workflows.
AI-powered browser automation toolset, including agent-browser (accessibility tree extraction), actionbook (50+ website automation recipes), and browser-use (Python automation library). Use cases: (1) Scrape web content that requires JS rendering (2) Fetch data from platforms like X/Twitter, GitHub, Reddit, etc. (3) Take web page screenshots (4) Automate browser operations (5) Retrieve the accessibility tree structure of web pages. Use this skill when you need to access dynamic web pages, bypass anti-scraping measures, or perform browser automation.
Use when the user asks to "find X in codebase", "where is Y defined?", "explore this dir", "list files in src/", "trace definitions", "find usages" — local-only. Local codebase exploration via Octocode Local + LSP. No GitHub; for external repos use octocode-research.
This skill should be used when creating a skill for a CLI tool. Use when users ask to document a command-line tool, create CLI guidance, or build a skill for terminal commands. Essential for systematically introspecting CLI tools through help text, man pages, GitHub repos, and online research, then organizing findings into effective skill documentation.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).