django-spike-despike-workflow

name	django-spike-despike-workflow
description	Manage Django spikes and de-spiking with tests: branch experiments, exploratory code, learning capture, functional tests against spiked behavior, revert-and-rebuild, custom auth flows, email/token models, and dependency seams. Use when a Django feature was prototyped quickly and needs to be turned into production-quality tested code.
license	MIT
compatibility	Codex, Claude Code, and other Agent Skills-compatible clients.
metadata	{"version":"0.1.0","displayName":"Django Spike De-Spike Workflow","category":"Django","tags":"django,tdd,spikes,auth,testing"}

Django Spike De-Spike Workflow

Use this skill when exploratory Django code has answered a question but is not yet fit to keep. Preserve the learning, throw away accidental design, and rebuild the feature with tests that express the real behavior.

Source Traceability

Primary source: Harry Percival, Test-Driven Development with Python, 3rd ed. Guidance is transformed and paraphrased from chapters 19 and 20, especially passwordless authentication, branch-based spikes, de-spiking, custom user/token models, email flow tests, and introducing mocks only at external boundaries.

Workflow

1. Label the spike.

   • Identify what question it answered.