What problem does it solve? When editing a Python project that depends on the nclutils package, agents often hand-roll filesystem copies, subprocess calls, console output, or git automation that the library already provides, or import symbols from the wrong module. This Skill supplies the correct import patterns, task-to-module lookup tables, and API gotchas so generated code uses nclutils correctly. ## Core Features & Use Cases - Import pattern enforcement: Only pp is re-exported from the top-level namespace; everything else comes from submodules like nclutils.fs, nclutils.sh, nclutils.git, nclutils.strings, and nclutils.utils. Deprecated modules (nclutils.questions, nclutils.network, nclutils.text_processing) are flagged. - Task-to-helper lookup: A table maps common tasks (copy a file with backup, run a shell command, sync a git branch, convert case, generate ISO timestamps) to the exact helper to call. - Gotcha documentation: Covers pp vs stdlib logging separation, run_command returning a CompletedCommand object and raising typed errors, non-nesting pp.step(), and independent verbosity/quiet gates. - Deep references on demand: references/ holds full API docs for pp, sh, git, fs, strings, and the smaller ask/net/text/utils modules. - Use Case: While adding a cleanup command to a CLI that depends on nclutils, the agent uses nclutils.git.prunable_branches() and delete_branches() with correct dataclass handling instead of writing raw subprocess git calls. ## Quick Start Ask the agent to write or edit Python code in this project using the nclutils helpers, for example to run a shell command or sync a git branch, and it will apply the correct imports and APIs.