Skills

Architecture Survey

Ranks module-level deepening candidates such as shallow modules and wrong seams.

Install

npx skills add Yeachan-Heo/oh-my-claudecode --skill architecture-survey -g -a claude-code -y
Category
Engineering
Updated
3d ago
License
MIT
Context cost
Lightabout 1,186 tokens
Runs scripts
No, instructions only

What it does

Periodic architecture survey, walks the module graph and reports ranked deepening candidates (shallow modules, hypothetical seams, logic behind the wrong seam). Survey, not rescue: it finds candidates and hands them to the captain; it never refactors on its own.

A surveyor charts the reef; the captain decides whether to dredge. The survey reads the water, reports what it found with evidence, and stops. It is the maintenance twin of the loft: where the loft answers one design question before building, the survey answers "where is this repo getting harder to change, and what would deepen it" after building.

When to survey

  • Periodically, every few days of active building, or after a batch of tickets lands.
  • Out of turn, when the repo starts feeling harder to change than it was last week: edits touching more files than they should, interfaces growing to satisfy one caller, tests that must be updated in lockstep for unrelated reasons.

Optional argument narrows the survey to a directory or area; with no argument, survey the whole repo.

The survey

  1. Read the repo's architecture principles (CLAUDE.md, ADRs) and the seeded seam vocabulary in docs/standards/architecture.md, the definitions of seam and deep module.
  2. Walk the module graph of the target area, and when no direction was given, weight the walk toward the yard's busy water: read a good stretch of the commit history first and let the areas that keep coming up pull the survey, because deepening pays off where future edits will land. A scattered history with no hot spot widens the net.
  3. Look for three finding classes:
    • Shallow modules, wide interface, thin behavior; callers know more than the module hides.
    • Hypothetical seams, a boundary crossed by exactly one adapter with no second caller; checkable by counting callers.
    • Logic behind the wrong seam, behavior living on the far side of a boundary that does not own its data.

Apply the demolition test to every suspect: if the module were removed, would its complexity vanish (a pass-through wearing a uniform) or reappear across its callers (load-bearing)? Only load-bearing shallowness is a finding.

The report

Read the whole SKILL.md on GitHub

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