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Claude Skills by Jamie-BitFlight
github.com/Jamie-BitFlight284 skills0 installs362 views
- ReferencesThis skill helps you build sophisticated Text User Interfaces (TUIs) using Textual, a Python framework for creating terminal and browser-based applications with a modern web-inspired API. It includes reference documentation, a card game template, and best practices for Textual development.Votes: 0GitHub stars: 67
- ReferencesBuild production-quality terminal user interfaces using Textual, a modern Python framework for creating interactive TUI applications.Votes: 0GitHub stars: 67
- HatchlingProvides Hatchling build backend guidance for Python packaging — use when configuring pyproject.toml metadata, build targets (wheel, sdist, binary), file selection with git-style globs, build hooks, metadata hooks, version management (code/regex/env sources), editable installs, the hatch-vcs plugin, plugin development, build environment setup (UV/pip/Cython), setuptools migration, or troubleshooting Hatchling errors. Covers PEP 517/518/621/660 standards and context variable interpolation.Votes: 0GitHub stars: 67
- LintRuns deterministic Python quality checks against a path or scope — formatting, linting, type checking, and typing-boundary policy. Use when checking or fixing code quality via prek, ruff, ty, pytest, or the check-typing-boundaries policy script. Reports results grouped by category; fixes only when explicitly requested.Votes: 0GitHub stars: 67
- MkdocsMkDocs documentation project reference covering CLI commands, mkdocs.yml configuration, Material theme setup, and plugin integration. Bundled references include complete CLI parameters, all mkdocs.yml settings with valid values, Material theme customization options, and plugin configs for mkdocstrings, mermaid2, mkdocs-gen-files, mkdocs-literate-nav, and mkdocs-typer2. Use when initializing a MkDocs site, configuring mkdocs.yml, customizing the Material theme, integrating plugins, building st...Votes: 0GitHub stars: 67
- ModernpythonApplies and teaches Python 3.11+ modernization patterns with PEP citations. Use when reviewing or writing Python code to apply built-in generics (PEP 585), pipe unions (PEP 604), walrus operator (PEP 572), match-case (PEP 634), Self type (PEP 673), exception notes (PEP 678), StrEnum, tomllib, pytest-mock fixtures, Typer Annotated syntax, or Rich terminal output — or when refactoring legacy typing imports or elif chains to modern equivalents.Votes: 0GitHub stars: 67
- OrchestrateUse when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python...Votes: 0GitHub stars: 67
- Orchestrating Python DevelopmentProvides agent selection criteria, workflow patterns (TDD, feature addition, code review, refactoring, debugging), quality gates, and python-cli-architect vs stdlib-scripting routing for Python engineering tasks. Activated by python-engineering:orchestrate at Step 1 before any task is routed. Also activates when an orchestrator needs to select the correct Python specialist agent or chain agents across a multi-step Python workflow.Votes: 0GitHub stars: 67
- Pre CommitConfigures and runs git hooks with prek (or the pre-commit it replaces — same `.pre-commit-config.yaml`). Use when adding or troubleshooting git hooks, writing a `prepare-commit-msg` or `commit-msg` stage hook, or authoring `.pre-commit-hooks.yaml` for hook distribution.Votes: 0GitHub stars: 67
- Pypi Readme CreatorGenerates professional PyPI-compliant README files in Markdown or reStructuredText. Use when creating a Python package README for PyPI publication, converting between README.md and README.rst formats, validating markup with twine check before publishing, configuring the readme field in pyproject.toml, integrating sphinx-readme to generate PyPI-compatible RST from Sphinx docs, troubleshooting rendering errors on PyPI, or previewing README rendering locally with grip or docutils.Votes: 0GitHub stars: 67
- Python Cross Platform SmoothingUse when writing Python scripts that must run on Windows, Linux, and macOS — especially when Rich or Typer output breaks on Windows, when dealing with Unicode/encoding errors, ANSI escape handling, terminal detection, path separators, or console color support. Provides verified cross-platform patterns covering stdout/stderr encoding guards, Windows console quirks, terminal capability detection, and portable I/O for CLI, TUI (Rich/Textual), and GUI environments.Votes: 0GitHub stars: 67
- Python3 Add FeatureExecutes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.Votes: 0GitHub stars: 67
- Python3 CliUse when building CLI applications with Typer and Rich — creating commands with Annotated parameter syntax, defining arguments and options, composing subcommands, async concurrent CLI tasks with semaphores, testing with CliRunner, PEP 723 shebang scripts, progress bars, Rich terminal output, or non-TTY display width handling.Votes: 0GitHub stars: 67
- Python3 CoreActivates on any Python task involving *.py files, uv, ruff, ty, pytest, or pyproject.toml — loads the shared Python 3.11+ standards and routes the task to the specialist skill that applies them: TDD, CLI, web, data, async, typing, packaging, publishing, documentation sites, test design, test-failure analysis, or stdlib-only constrained environments.Votes: 0GitHub stars: 67
- Python3 DataSpecialist skill for Python data engineering — pandas, polars, DuckDB, numpy, ETL pipelines, tabular data ingestion, and notebook-to-module extraction. Use when working with dataframes, data validation at ingress boundaries, merge/join operations, typed column contracts, or choosing between pandas vs polars vs DuckDB for a data task.Votes: 0GitHub stars: 67
- Python3 PackagingConfigures pyproject.toml and Python packaging using PEP 517/518/621/660/723 standards. Use when creating or updating pyproject.toml, selecting a build backend (hatchling/setuptools/flit), configuring ruff, ty, mypy, pytest, or coverage tool sections, setting up dependency constraints or optional extras, defining CLI entry points, configuring pre-commit hooks, establishing src-layout directory structure, or preparing a package for PyPI publishing.Votes: 0GitHub stars: 67
- Python3 Publish Release PipelineConfigures CI/CD pipelines for automated Python package publishing to PyPI or GitLab Package Registry. Use when creating GitHub Actions or GitLab CI release workflows, setting up trusted publishing or API token-based PyPI authentication, configuring version management with git tags and hatch-vcs, writing pyproject.toml publishing metadata, testing packages against TestPyPI, or documenting the release process for a Python project.Votes: 0GitHub stars: 67
- Python3 Stdlib OnlyUse when building dependency-free Python 3.11+ scripts for airgapped, stdlib-only, or restricted environments where third-party package installation is prohibited — triggers on "stdlib-only", "airgapped", "no dependencies", "no internet", "restricted environment", or confirmed environments where external packages cannot be installed.Votes: 0GitHub stars: 67
- Python3 TddUse when a Python task explicitly requires test-driven development, tests-first implementation, or a red-green-refactor workflow.Votes: 0GitHub stars: 67
- Python3 Test DesignGuides pytest test architecture for Python 3.11+ using behavioral contracts, risk, and maintenance-adjusted value. Use when choosing unit/integration/property/e2e boundaries, fixture strategy, coverage measurement, or mutation testing. Preserves existing project gates but does not invent test-pyramid ratios, coverage percentages, mutation-score targets, or tests for implementation detail.Votes: 0GitHub stars: 67
- Python3 TestingPytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based strategies.Votes: 0GitHub stars: 67
- Python3 ToolsUse when working with Python tooling — uv package management, Hatchling build backend, ty or mypy type checker configuration, ruff linting, pre-commit hook setup, TOML read-write with tomlkit or tomllib, or PyPI packaging and release workflows. Routes to standalone specialist skills for deep dives on any single tool.Votes: 0GitHub stars: 67
- Python3 TypingAuto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 64...Votes: 0GitHub stars: 67
- Python3 WebPython web and API development enforcing strict route/domain/data layer separation, Pydantic v2 strict request-response models, edge-resolved auth, and async-safe HTTP clients. Use when working with FastAPI, Starlette, Django, Flask, HTTP endpoints, request models, authentication flows, async handlers, or any Python web framework task.Votes: 0GitHub stars: 67
- ReviewReviews Python code across type safety, error handling, security, performance, modern patterns, design clarity, typed-boundary compliance, test quality, and documentation. Use when performing code review, PR review, pre-merge quality checks, or assessing Python for security vulnerabilities, bare except clauses, Any usage outside boundaries, or missing input validation at system boundaries.Votes: 0GitHub stars: 67
- RuffUse when working with ruff — this skill's ruff policy and required overrides to Astral's official guidance. Pair with `astral:ruff` (if installed) for general usage.Votes: 0GitHub stars: 67
- ShebangpythonValidates and corrects Python shebangs and PEP 723 inline script metadata by applying four shebang-selection rules. Use when auditing or fixing shebangs in Python files — choosing between plain python3 and the uv shebang for standalone scripts with external dependencies, adding or removing PEP 723 metadata blocks to match actual import requirements, checking execute bit presence, or avoiding redundant transitive dependencies when typer is declared.Votes: 0GitHub stars: 67
- SnakepolishUse when independently assessing how bounded Python code could accomplish the same behavior with less maintained code, more Pythonic design, newer language/stdlib capabilities, or well-maintained ecosystem libraries.Votes: 0GitHub stars: 67
- Specialist Skill RoutingRoutes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only...Votes: 0GitHub stars: 67
- Standards For Python DevelopmentShared Python 3.11+ development rules — type safety and the boundary policy for `Any` (ty, native generics, Protocol, TypeIs, Pydantic), layered architecture and SOLID, error handling, security, performance, identifier naming, PEP 723 script dependencies, Rich/Typer output, tooling defaults (uv, ruff, ty, hatchling, pytest), and testing requirements (behavioral coverage, TDD). Activates when any Python skill or agent needs the shared rules for implementation, code review, refactoring, or test...Votes: 0GitHub stars: 67
- StinkysnakeUse when independently hunting Python code smells, deviations from engineering standards, maintenance hazards, or suspicious design choices in a bounded review surface.Votes: 0GitHub stars: 67
- Test Failure MindsetInvestigate pytest failures without treating tests or implementation as automatic authority. Use when diagnosing regressions, debugging test errors, or deciding whether to fix a test or code; trace the contract, product, fixture, and observation before choosing an evidence-backed correction.Votes: 0GitHub stars: 67
- TextualUse when building terminal UI apps with the Textual framework — creating widgets, screens, layouts, handling events, managing reactive attributes, testing with Pilot, snapshot testing with pytest-textual-snapshot, or running background workers. Covers App lifecycle, CSS styling, screen stack, custom messages, actions, bindings, and the Worker API.Votes: 0GitHub stars: 67
- Toml PythonHandles TOML configuration file operations in Python using tomlkit for comment-preserving read-modify-write cycles. Use when reading or writing pyproject.toml or any .toml config file, selecting between tomlkit and tomllib, modifying TOML while preserving comments and whitespace, implementing atomic config file updates, integrating TOML with Python dataclasses, handling TOML parse errors, or applying XDG base directory patterns for config file locations.Votes: 0GitHub stars: 67
- TyUse when working with ty — this skill's ty policy and required overrides to Astral's official guidance. Pair with `astral:ty` (if installed) for general usage.Votes: 0GitHub stars: 67
- Typer And RichUse when building or debugging Typer/Rich CLI applications. Activates on Rich table rendering, console output in non-TTY environments, CliRunner testing with Rich output, snapshot testing, Typer command wiring, exception chain prevention with AppExit/AppExitRich patterns, table width at 80-column wrapping, Progress/Live in non-interactive contexts, stderr/stdout separation, or force_terminal vs width configuration. Grounds AI-generated CLI code in verified correctness patterns and prevents kn...Votes: 0GitHub stars: 67
- TyperUse when building CLI applications with Typer — creating commands, defining arguments and options with enum restrictions, path validation, date and UUID types, composing subcommands, testing with CliRunner, or using advanced features like colored output, progress bars, shell autocompletion, and version callbacks.Votes: 0GitHub stars: 67
- UvUse when working with uv — this skill's uv policy and required overrides to Astral's official guidance. Pair with `astral:uv` (if installed) for general usage.Votes: 0GitHub stars: 67
- RtfpScan Claude Code session transcripts to find the strongest user reactions to assistant instruction-following failures, reconstruct the triggering assistant output, and render a shareable terminal-style PNG artifact. Use when you want to surface and share a moment where the assistant completely missed what was asked — captures what they were doing, what Claude said, and how the user reacted. Triggers on: "rtfp", "read the fucking prompt", "find my worst AI moment", "make a rage screenshot from...Votes: 0GitHub stars: 67
- Evidence First DebuggingUse when debugging software, investigating incidents, diagnosing flaky tests, or analyzing performance regressions — enforces structured observation recording with evidence IDs, causality validation, and verification gates to prevent correlation-causation pollution. Use when an agent might otherwise summarize or speculate instead of reporting observed evidence.Votes: 0GitHub stars: 67
- Experiment ProtocolDesign and run controlled experiments using the experiment-registry MCP server — domain-agnostic, pluggable, mechanically enforced. Use when you need evidence that a change actually improves behaviour.Votes: 0GitHub stars: 67
- Scientific ThinkingUse when facing unknowns, debugging without a clear cause, or making architecture decisions — enforces hypothesis-driven scientific reasoning through observation, hypothesis formulation, prediction, experiment design, and evidence-based conclusion. Use when previous attempts have failed or the problem space involves uncertainty.Votes: 0GitHub stars: 67
- Agent Result RelayRelay agent results without corrupting exact counts, failure reasons, source scope or status. Use when receiving agent output or handing results to another actor; distinguish observations from attributed conclusions and reference complete artifacts.Votes: 0GitHub stars: 67
- File SummarizationSummarize files or a requested directory scope from actual contents. Extract code, config, data and document evidence, preserve exact counts and source locations, and disclose incomplete or unsupported acquisition. Use for file summaries, code explanations and configuration overviews.Votes: 0GitHub stars: 67
- Image SummarizationDescribe images, screenshots, diagrams and charts from visual inspection. Preserve visible text, counts, labels, directions and uncertainty; distinguish observation from interpretation. Use for image summaries, screenshot explanations and diagram descriptions.Votes: 0GitHub stars: 67
- Multi Source SynthesisIntegrate multiple source findings into an attributed synthesis or comparison. Use for combine these summaries, synthesize results, merge findings or multi-source analysis. Preserve claim-level provenance, coverage, qualifiers, conflicts and uncertainty rather than repeatedly compressing narrative summaries.Votes: 0GitHub stars: 67
- SummarizerRoute requests to summarize files, URLs, images, inline text, or multiple sources. Select the requested format and preserve evidence, exact counts, uncertainty and source coverage through summarization, synthesis and agent-result relay.Votes: 0GitHub stars: 67
- Url SummarizationSummarize a supplied URL from fetched content with source locations, acquisition coverage and explicit access failures. Use for articles, documentation, API references and web pages; preserve version, author attribution and uncertainty in the requested output format.Votes: 0GitHub stars: 67
- AuditUse when the primary outcome is comparing documentation claims with implementation evidence, synchronizing docs from verified changes, or freshness review, including drift, missing coverage, stale claims, and post-change updates.Votes: 0GitHub stars: 67
- AuthorUse when the primary outcome is authoring, rewriting, summarizing, or validating user-facing documentation without implementation comparison or required source attribution, including READMEs, tutorials, API docs, GitLab Markdown, source-faithful summaries, and audience-specific prose.Votes: 0GitHub stars: 67