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Module Checkpoints

Guide Fit

flowchart TD
  family["Reproducible Research"] --> program["Deep Dive Snakemake"]
  program --> pressure["A concrete learner or reviewer question"]
  pressure --> guide["Module Checkpoints"]
  guide --> next["Modules, capstone, and reference surfaces"]
flowchart TD
  question["Name the exact question you need answered"] --> skim["Skim only the sections that match that pressure"]
  skim --> crosscheck["Open the linked module, proof surface, or capstone route"]
  crosscheck --> next_move["Leave with one next decision, page, or command"]

Read the first diagram as a timing map: this guide is for a named pressure, not for wandering the whole course-book. Read the second diagram as the guide loop: arrive with a concrete question, use only the matching sections, then leave with one smaller and more honest next move.

This page is the missing study contract at the end of each module. It gives a human bar for readiness instead of assuming that reading the prose once means the concept is stable.

Use it when you are about to move on and want to know whether you are ready, what you are still fuzzy on, and which proof route should settle the question.

How To Use The Checkpoints

For each module:

  1. read the module overview and main lessons
  2. answer the checkpoint questions without looking at the text
  3. run the smallest honest proof route
  4. only advance when the concept feels explainable, not merely recognizable

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Checkpoint Table

Module You are ready when you can explain You should be able to do Useful proof route
01 why rules and targets form a file-driven DAG explain a dry-run without hand-waving capstone-walkthrough
02 why checkpoints need explicit, durable discovery artifacts describe what discovery is allowed to change and what must stay stable test
03 why profiles and retries are policy, not workflow meaning distinguish execution context from workflow semantics capstone-tour
04 how modularity and interfaces keep larger workflows reviewable name which file boundary should absorb one scaling change capstone-tour
05 why scripts, wrappers, and envs must stay reviewable explain which logic belongs in rules versus helper code proof
06 what makes a publish surface trustworthy downstream explain the difference between internal state and public outputs capstone-verify-report
07 how repository architecture protects workflow meaning review ownership without guessing where the contract lives proof
08 what may change across local, CI, and cluster contexts explain which differences are policy and which would be semantic drift capstone-profile-audit
09 how to move from workflow symptom to evidence-backed diagnosis choose the right observability or incident surface first proof
10 when Snakemake should stop owning a concern review a workflow as a long-lived product with migration judgment capstone-confirm

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Failure Signals

Do not advance yet if any of these are still true:

  • you recognize the term but cannot explain the invariant it protects
  • you know the strongest proof command but not the smallest honest one
  • you can follow the capstone mechanically but cannot name the owning boundary
  • you can repeat the repair pattern but cannot say what failure it prevents

These are not small study gaps. They are signals that the next module will feel more arbitrary than it should.

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Best Companion Pages

Use these with the checkpoints:

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