আপনার এজেন্টের জন্য উপযুক্ত সক্ষমতা খুঁজে নিন।
Expert Debian package builder specializing in git-buildpackage, debhelper, and Debian Policy compliance. Use for .deb packaging, debian/ directory work, dpkg operations, and package maintenance. Triggers on "Debian", ".deb", "dpkg", "debhelper", "gbp", "pbuilder", "lintian", "dch".
Create, test, and maintain Homebrew formulas. Use when adding packages to a Homebrew tap, debugging formula issues, running brew audit/test, or automating version updates with livecheck.
Maintain project documentation including CHANGELOG.md, FILETREE.md, and FAILURELOG.md. Use this skill when making code changes, adding features, fixing bugs, restructuring files/directories, or when initial solutions fail. This skill ensures consistent documentation of all changes using Keep a Changelog format with semantic versioning.
Auto-detects project language and framework from package.json, pyproject.toml, etc.
Manage project dependencies across all apps. Use when installing, updating, or managing dependencies, or when user asks to install packages.
Comprehensive guide for conda-forge recipe development. Handles legacy (meta.yaml) and modern (recipe.yaml) formats, linting, CI troubleshooting, and feedstock maintenance. Enhanced with patterns from real conda-forge feedstocks (2025). USE THIS SKILL WHEN: creating conda recipes, packaging Python/Rust/Go/C++ software, fixing conda-forge build failures, updating feedstocks, migrating to recipe.yaml format, setting up private channels, or troubleshooting conda-forge CI.
Best practices for structuring prpm.json package manifests with required fields, tags, organization, and multi-package management
Python import best practices for avoiding CI failures. Use when writing imports, dealing with optional dependencies, or fixing import-time errors.
This skill provides commands for managing Python projects using `uv`, a fast Python package installer and resolver.
Python virtual environment management using uv for fast and reliable environment setup. Create, maintain, and manage Python virtual environments with dependency management. Use uv for environment creation, package installation, dependency resolution, and project configuration. Use when setting up new Python projects, managing dependencies, troubleshooting environment issues, or ensuring reproducible development environments.
Advanced usage of uv, the extremely fast Python package and project manager from Astral. Use this skill when working with uv for project management (uv init, uv add, uv run, uv lock, uv sync), workspaces and monorepos, dependency resolution strategies (universal, platform-specific, constraints, overrides), Docker containerization, PEP 723 inline script metadata, uvx tool execution, Python version management, pip interface migration, pyproject.toml configuration, or any advanced uv workflow. Covers workspaces, resolution strategies, Docker best practices, CI/CD integration, and migration from pip/poetry/pipenv.
Write and maintain Sphinx documentation and reStructuredText files, including configuring Sphinx (conf.py, extensions, toctrees) and updating CI/deployment workflows so documentation builds as part of deployment or release pipelines.
Guides npm package maintenance tasks. Use when user mentions outdated packages, npm audit, security vulnerabilities, dependency updates, package optimization, unused dependencies, or devDependencies categorization. Recommends the lt-dev:npm-package-maintainer agent via /maintain commands.
Create distributable Python packages with pyproject.toml, setup.py, and PyPI publishing. WHEN: Packaging Python libraries, creating pyproject.toml/setup.py, building CLI tools with entry points, publishing to PyPI, configuring package metadata. WHEN NOT: Managing dependencies (use python-uv-package-manager), writing application code, creating virtual environments.
How to use the natscli tool when not directly available
Orchestrate an end-to-end process mining engagement by chaining phase skills with decision checkpoints and reproducibility safeguards.
Implement pipeline orchestration with step-based structure. Use when: building training/prediction pipelines, orchestrating multiple components. Triggers: "pipeline", "trainer", "predictor", "パイプライン", "ワークフロー", "オーケストレーション".
Creates and optimizes CI/CD pipelines for GitHub Actions, GitLab CI, and Jenkins. Use when setting up new pipelines, improving build times, or implementing security scanning.
Wraps shell commands to resolve secret references in environment variables to their actual values. Always use when invoking synu, crush, gh, hut, etc. Ask whether to use if an invocation fails due to missing credentials.
