317 skills · sorted by relevance
Configure Kotlin build and quality tooling, including Gradle Kotlin DSL, Version Catalogs, KMP, ktlint, Detekt, MockK, coverage, and quality plugins. Use for Kotlin-specific build, lint, test-tool, or coverage setup; defer Java-only tooling and Spring test behavior.
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Outlines the monorepo structure and tooling conventions, emphasizing the use of Taskfile.yml, and proper handling of environment variables.
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.NET SDK and NuGet tooling conventions: dotnet CLI commands (new/build/run/test/publish/restore/format), NuGet package management (PackageReference, Directory.Packages.props central package management, packages.lock.json), project file conventions (.csproj, .sln, global.json, Directory.Build.props), multi-targeting, and dotnet format. Stack-agnostic — referenced by every .NET plugin in the marketplace. Use this skill to: - Detect the .NET SDK version and run all commands via the dotnet CLI. - Manage NuGet dependencies safely (central package management, no floating versions). - Configure project files and solution-wide properties in Directory.Build.props. - Format code consistently with dotnet format. Do NOT use this skill for: - Framework-specific tooling (dotnet ef migrations, aspnet-codegenerator — those are in aspnet-core-plugin:aspnet-conventions). - Testing patterns — see csharp-foundation:dotnet-testing. - C# language idioms — see csharp-foundation:csharp-conventions.
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Python project tooling: pyproject.toml as the single source of truth, package managers (pip, Poetry, uv, pipenv), virtual environments, lockfiles, ruff (lint + format), mypy (type checking), and console scripts / entry points. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Read pyproject.toml (or requirements.txt / Pipfile) to learn which package manager and Python version the project uses. - Install, add, and remove dependencies with the project's package manager. - Run ruff for formatting and linting, mypy for type checking. - Define console scripts and entry points for CLI applications. Do NOT use this skill for: - Language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing. - Framework-specific tooling (django management commands, flask CLI) — see framework plugin skills.
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Scan a project to detect configured quality and testing tools across JVM (Gradle/Maven), Android (AGP/Compose/KMP), Node.js/TypeScript, and Python ecosystems. Cross-reference against research-backed recommendations and assist with setup. Auto-detects project type(s) including monorepos with mixed ecosystems. Use when user asks to "audit tooling", "recommend tools", "quality stack", "what tools am I missing", "setup eslint", "setup detekt", "add coverage", "add ruff", "configure CI quality pipeline", "scan project tools", "tooling audit", "android tooling", "android quality", "compose testing", "kmp testing", or "screenshot testing".
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Git operations, shell scripting, CI/CD pipelines, and terminal automation. Use for conventional commits, PowerShell/Bash scripting, configuring GitHub Actions, or automating development tooling workflows.
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Review part designs for sheet metal, CNC machining, or injection molding. Compare geometry measurements with applicable supplier or tooling limits, then document manufacturing concerns, suggested changes, and checks that still need evidence.
Share the current coding session transcript with the Convex team, with explicit consent, for an AI review that identifies unclear setup instructions, tooling failures, and successful patterns to help improve the quickstart system.
Sets up new projects or improves existing projects with development best practices, tooling, documentation, and workflow automation. Use when user wants to start a new project, improve project structure, add development tooling, or establish professional workflows.
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Configure debugging, bundle analysis, and ecosystem tools for React applications. Use when setting up Vite/webpack build tooling, analyzing bundle size, debugging re-renders with React DevTools, or configuring ESLint and StrictMode for React projects.
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Configure Python tooling, dependency surfaces, static analysis, and verification gates. Use when editing `pyproject.toml`, `requirements.txt`, `pytest.ini`, `ruff`, `pyright`, CI, or Python release checks.
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Configure Next.js build tooling, deployment, and developer workflow. Use when setting up Turbopack, standalone Docker output, bundle analysis, CI caching, environment variable validation, or ESLint integration for Next.js projects.
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Configure PHP ecosystem tooling, dependency management, and static analysis. Use when managing Composer dependencies, running PHPStan, or configuring PHP build tools.
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Configure Maven, Gradle, and static analysis for Java projects. Use for Java-only build and quality tooling such as Spotless, Checkstyle, SpotBugs, SonarLint, JDK versions, and Java service Dockerfiles; defer Kotlin, Android, Flutter, and GitHub Actions-specific configuration.
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Go developer toolchain — gopls LSP diagnostics, linting, formatting, and vet. Use when setting up Go tooling, running linters, or integrating gopls with Claude Code.
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Configure Android static analysis with Detekt, Ktlint, and Android Lint for CI/CD quality gates. Use for Android-specific lint and quality tooling; defer generic Java Checkstyle, SonarQube, and standalone CI configuration.
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Real-world Active Directory environment constraints that silently break attacks when ignored: NTLM disabled (Kerberos fallback), AES-only KDCs (RC4 blocked by GPO), LDAP signing and channel binding requiring LDAPS on 636, Kerberos clock skew (KRB_AP_ERR_SKEW), SPNs that must be FQDNs never short names or IPs (the misleading invalidCredentials), Protected Users / LAPS / gMSA / MachineAccountQuota, LDAP 1000-object paging, and VPN latency. Use this whenever a bind, TGT request, LDAP query, or SMB negotiation fails in a way that looks like bad credentials but is really hardening, or before running any AD tooling against a domain you have not fingerprinted. Standard-tooling knowledge (netexec, impacket, certipy, bloodyAD, kerbrute), no vendor-specific engine.
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Review trust before frontend tooling adoption.
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Use when starting a Python data or ML project, adding its first tooling, or changing pyproject.toml, the lockfile, the package layout or the lint/type/test configuration — detect the repo's tooling first, then uv, ruff, mypy, pytest and a src layout
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Expert guide for Biome (Rust-based linter + formatter), ESLint/Prettier migration, and code quality tooling / Panduan ahli Biome (linter + formatter berbasis Rust), migrasi dari ESLint/Prettier, dan tooling kualitas kode.
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Expert guide for multi-pass autonomous AI code self-review — syntax validation, logic correctness, architectural conformance, security audit, and performance analysis without external tooling — enabling the agent to catch its own errors before presenting code / Panduan ahli review kode otonom multi-pass oleh AI — validasi sintaks, kebenaran logika, konformitas arsitektur, audit keamanan, dan analisis performa tanpa tooling eksternal — memungkinkan agen menangkap errornya sendiri sebelum menampilkan kode.
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Modern Python tooling best practices using uv, ruff, ty, and pytest. Mandates the Trail of Bits Python coding standards for project setup, dependency management, linting, type checking, and testing. Based on patterns from trailofbits/cookiecutter-python.
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Application and library conventions for plain Python projects (no web framework): src/ package layout, CLI tooling (argparse/click/typer), configuration management (pydantic-settings), logging setup, module design, entry points, and packaging conventions. Activated automatically by python-plugin/stack.md as a convention skill for the development phase. Use this skill to: - Organise Python application code in a src/ layout with proper package structure. - Build CLI tools with argparse, click, or typer and register them as console scripts. - Manage configuration from environment variables using pydantic-settings. - Set up structured logging for production-grade applications. - Package a Python project correctly with pyproject.toml. Do NOT use this skill for: - Language idioms (type hints, dataclasses, enums, match/case) — see python-foundation:python-conventions. - Package manager commands (ruff, mypy, pip/poetry/uv) — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing. - Web framework patterns (Django/FastAPI/Flask) — see those framework plugin skills.
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Modern Java idioms for any JVM project (Java 17+): records, sealed types, text blocks, pattern matching, Optional discipline, streams, immutability, null safety, package layout, var usage, and code organisation. Apply when the project is a Java 17+ project. Stack-agnostic — referenced by every Java plugin in the marketplace. Use this skill to: - Write self-documenting, immutable-by-default value types with records. - Model closed type hierarchies with sealed classes and interfaces. - Handle optionality explicitly with Optional instead of returning null. - Write expressive pipelines with Stream API without performance footguns. - Lay out packages consistently (feature-first or layer-first) and keep class responsibilities tight. Do NOT use this skill for: - Framework-specific idioms (Spring annotations, JPA mappings — those live in framework plugin skills). - Build tooling (Maven/Gradle) — see java-foundation:build-tooling. - Testing patterns — see java-foundation:jvm-testing.
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