Generates Makefiles with testing, linting, formatting, and automation targets. Use when starting a project or standardizing build automation.
npx skills add https://github.com/athola/claude-night-market --skill makefile-generation
Generate a Makefile with standard development targets for Python, Rust, or TypeScript projects.
/attune:upgrade-project instead for updating existing MakefilesCommon targets:
help - Show available targetsinstall - Install dependencies with uvlint - Run ruff lintingformat - Format code with rufftypecheck - Run mypy type checkingtest - Run pytesttest-coverage - Run tests with coverage reportcheck-all - Run all quality checksclean - Remove generated files and cachesbuild - Build distribution packagespublish - Publish to PyPICommon targets:
help - Show available targetsfmt - Format with rustfmtlint - Run clippycheck - Cargo checktest - Run testsbuild - Build release binaryclean - Clean build artifactsCommon targets:
help - Show available targetsinstall - Install npm dependencieslint - Run ESLintformat - Format with Prettiertypecheck - Run tsc type checkingtest - Run Jest testsbuild - Build for productiondev - Start development server# Check for language indicators
if [ -f "pyproject.toml" ]; then
LANGUAGE="python"
elif [ -f "Cargo.toml" ]; then
LANGUAGE="rust"
elif [ -f "package.json" ]; then
LANGUAGE="typescript"
fi
Verification: Run the command with --help flag to verify availability.
from pathlib import Path
template_path = Path("plugins/attune/templates") / language / "Makefile.template"
Verification: Run the command with --help flag to verify availability.
metadata = {
"PROJECT_NAME": "my-project",
"PROJECT_MODULE": "my_project",
"PYTHON_VERSION": "3.10",
}
Verification: Run the command with --help flag to verify availability.
from template_engine import TemplateEngine
engine = TemplateEngine(metadata)
engine.render_file(template_path, Path("Makefile"))
Verification: Run the command with --help flag to verify availability.
make help
Verification: Run make --dry-run to verify build configuration.
Users can add custom targets after the generated ones:
# ============================================================================
# CUSTOM TARGETS
# ============================================================================
deploy: build ## Deploy to production
./scripts/deploy.sh
Verification: Run the command with --help flag to verify availability.
Skill(attune:project-init) - Full project initialization/abstract:make-dogfood command - Makefile testing and validationMakefile is created at the project root containing at minimum a help target andall standard targets for the detected language (Python: install/lint/format/typecheck/test;
Rust: fmt/lint/check/test/build; TypeScript: install/lint/format/typecheck/test/build).
make help runs without error and lists all generated targets with descriptions.make --dry-run <target> exits 0 for each standard target, confirming recipe syntaxis valid.
pyproject.toml, Cargo.toml, or package.json), theskill reports the detection failure and stops rather than generating a blank Makefile.
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when implementing any feature or bugfix, before writing implementation code
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Take athola/makefile-generation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.