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Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Passed 3 of 11 test cases with the skill, and 3 of 11 without it.
and 5 more in the full report
5 fixed2 passed either way12 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
Before spawning sub-agents to scan the codebase for friction in the billing subsystem, what local project documentation files should be inspected first?
| Checked | Without skill | With skill |
|---|---|---|
| Reads CONTEXT.md to load domain terms before commencing codebase exploration. | Missed | Passed |
| Reads architecture decision records in docs/adr/ prior to scanning code paths. | Passed | Passed |
The instructions your model reads when the skill loads.
Surface architectural friction and propose deepening opportunities — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
This command is informed by the project's domain model and built on a shared design vocabulary:
CONTEXT.md gives names to good seams; ADRs in docs/adr/ record decisions this command should not re-litigate.Scope before you scan — YAGNI. Deepening a module pays off by making future changes to it easier, so put extra weight on the parts of the codebase that have recently changed. Decide where to look before you look:
git log --oneline) to find the codebase's hot spots — the files and areas that keep coming up — and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net.Read the project's domain glossary (CONTEXT.md) and any ADRs in the area you're touching first.
Then spawn a sub-agent to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
Apply the deletion test to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.
Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from $TMPDIR, falling back to /tmp (or %TEMP% on Windows), and write to <tmpdir>/architecture-review-<timestamp>.html so each run gets a fresh file. Open it for the user — xdg-open <path> on Linux, open <path> on macOS, start <path> on Windows — and tell them the absolute path.
The report uses Tailwind via CDN for layout and styling, and Mermaid via CDN for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a before/after visualisation. Be visual.
For each candidate, render a card with:
test cases passed, vs 3 / 11 without
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