<< All versions

Skill v1.0.0

currentAutomated scan100/100
iusztinpaul/squid/squid-architecture-review
──Details
PublishedOctober 29, 2026 at 05:36 AM
Content Hashsha256:00ef48b465f980ef...
Git SHA6e6f77c30605
──Files
Files (1 file, 10.2 KB)
SKILL.md10.2 KBactive
SKILL.md · 206 lines · 10.2 KB

name: squid-architecture-review description: >- Periodic architectural sweep — reads existing ADRs, maps modules/dependencies/layering, and reports up to 10 prioritised findings shaped as refactor proposals /squid-refactor can consume directly. disable-model-invocation: true argument-hint: "[scope-path or component name; default = whole repo]" metadata: version: "1.0.0"


Architecture review — periodic structural audit

The team's day-to-day pipeline (/squid-implement-task, /squid-implement-night) operates at task grain. Long-horizon codebase health — drift, unintended coupling, dead modules, layering violations — accumulates between tasks and never gets addressed unless someone deliberately looks. This skill is that deliberate look.

The output is not a single PR. It's a prioritised backlog of refactor proposals, each shaped so /squid-refactor can pick one up and turn it into a Tasks Plan.

You are the auditor — you delegate exploration to sub-agents, you read the target repo's docs/adr/ to avoid re-proposing settled questions, and you produce a written report. You do NOT write code, do NOT start refactors, and do NOT decide priority for the team — you propose, the human prioritises.

$ARGUMENTS:

  • Empty → audit the whole repo.
  • A path (packages/backend/) → audit only that subtree.
  • A component name (backend, frontend-web) → audit only that component.

When NOT to use

  • During active feature delivery — review when the team has bandwidth to act on findings, not as theatre.
  • On a codebase < 6 months old. There isn't yet enough crystallised pattern to review against.
  • When the team has clear architectural anxieties already named — go straight to /squid-refactor with the named target.
  • As a substitute for code review on a specific PR — open or update the PR with gh and review it there instead.
  • On infra-only repos (Terraform, CI tooling). The shape doesn't fit; this skill assumes application code with modules, layers, dependencies.

Step 1 — Frame the scope

Resolve $ARGUMENTS. If empty, ask the user one question via AskUserQuestion:

Whole repo, one component, or a specific subtree?

Echo the resolved scope back as a one-line confirmation. Don't block.

Step 2 — Read prior decisions

Read the repo's docs/adr/ end-to-end if it exists. Build a mental model of:

  • What decisions are Accepted and still in force.
  • What decisions are Superseded (and by what).
  • What constraints (technical, business, team-shape) the ADRs cite.

Never re-propose what an ADR already settled. If ADRs don't exist, the hand-off's ADR action (Step 7) says so.

Also read, if present:

  • docs/glossary.md (spec: squid-scaffold/specs/ubiquitous-language.md) — to know whether the team already names concepts consistently.
  • The root CLAUDE.md and any per-component CLAUDE.md — for stated rules.

Step 3 — Map the current architecture

Spawn 2–3 Explore agents in parallel:

Agent(
subagent_type="Explore",
prompt="""Architecture mapping pass on {scope}.
Produce four artefacts:
(1) Module / package list with one-line responsibility per module (file:line for the canonical entry point).
(2) Dependency graph — who imports whom. Flag any cycles. Flag any "junk drawer" modules imported by everyone.
(3) Layering — name the de-facto layers (e.g., handlers → services → repositories → models) and list any layer-skipping imports.
(4) Public surface — what's exported / consumed by other components or external callers. Mark anything intended-internal that's leaked.
Be exhaustive on the dependency graph; missing an edge produces a wrong recommendation. Report as four sections."""
)
Agent(
subagent_type="Explore",
prompt="""Hot-spot scan on {scope}.
Find:
(1) Files with > 500 lines.
(2) Files / modules touched by > 30% of commits in the last 6 months — `git log --since='6 months ago' --name-only | sort | uniq -c | sort -rn | head -20`.
(3) Tests with > 100 setup lines or > 5 fixtures — usually a smell that the system-under-test is too coupled.
(4) `# TODO` / `# FIXME` / `# HACK` markers — count and cluster.
(5) Any `# type: ignore` / `eslint-disable` / `nolint` clusters — places where the team is fighting their own static analysis.
Report as five sections with file:line."""
)

When agents return, read the top-3 most-implicated files yourself. Don't rely on summaries on the load-bearing modules — you need firsthand familiarity to call findings credibly.

Step 4 — Identify smells

Walk these dimensions. For each, form 0 or more findings. Don't manufacture findings to pad the report — empty dimensions are fine and signal health; say so explicitly in the report ("Layer violations: none observed").

DimensionWhat to look for
CyclesImport cycles between modules / packages. Always a smell.
Layer violationsLower layers (e.g., models) importing higher layers (e.g., HTTP handlers).
God modulesOne module that everything imports; usually means responsibilities accreted.
Junk drawersutils/, common/, helpers/ modules with > 10 unrelated functions.
Hidden couplingTwo modules that should be independent but share a hidden contract (a shape, a magic string, an env var).
Test smellsHigh setup-to-assert ratio; brittle tests on private internals; flaky tests. Usually rooted in a structural problem in the SUT.
API leakageInternal types reaching public surface; public surface that should be private (e.g., a route that no caller uses).
Dead codeUnused exports, unreachable branches, modules with zero importers.
Over-engineeringAbstraction the code doesn't earn: a single-implementation interface / factory / wrapper that only forwards, a layer with one caller, config nobody sets, hand-rolled logic the stdlib ships, or a dependency duplicating a platform/framework feature. Tag each with the same delete/stdlib/native/yagni/shrink vocabulary the PR-Reviewer uses (Dimension F).
Drift from CLAUDE.mdStated rules the codebase no longer follows. The rule is right; the code drifted.
ADR driftDecisions ADRs describe that the code no longer reflects (silently superseded). Either update the ADR or fix the code.
Performance shapeSync I/O in async handlers; N+1 patterns; in-memory aggregation that should be a query.
Observability gapsCritical paths without logs / metrics / traces; logs that don't include correlation IDs.

Step 5 — Score and prioritise

For each finding, assign:

  • Severity: S1 (active risk — security, data loss, ongoing pain) / S2 (significant friction) / S3 (technical debt without acute symptom) / S4 (cosmetic, defer).
  • Effort: S (small, ≤ half a day) / M (medium, 1–3 days) / L (large, > 3 days; probably needs to split).
  • Confidence: High (you've read the code yourself) / Medium (one sub-agent finding, you spot-checked) / Low (sub-agent finding, you haven't verified).

Prioritise by severity / effort ratio, with confidence as a tiebreaker — a High-confidence S2 beats a Low-confidence S1; don't recommend a refactor on a finding you haven't personally read. Do not propose more than 10 findings. Cluster related findings into one if they share a root cause.

Step 6 — Write the report

Path:

  • File mode: docs/architecture-review-{YYYY-MM-DD}.md (a report, not a task — it doesn't enter tasks/; each accepted finding becomes a task via /squid-refactor).
  • gh mode: a single issue, label squid-architecture-review.

Template:

markdown
# Architecture review — {scope}, {YYYY-MM-DD}
**Scope:** {whole repo / component / path}
**ADRs read:** {N} ({list, e.g. "0001–0007"})
**Findings:** {N total — by severity: S1×N, S2×N, S3×N, S4×N}
## Summary
{2–3 sentences. The headline shape: "Three module cycles between auth/ and core/, all introduced in the last 4 months, blocking the planned auth-extraction work. Tests on the affected modules have grown 2× in setup size. No ADR governs the boundary. Recommend ADR + extraction refactor."}
## Findings
### F1 — {one-line title} (S{1–4}, effort: {S/M/L}, confidence: {H/M/L})
**Where:** `path/to/a.py:42`, `path/to/b.py:117`
**Symptom:** {what is concretely wrong, observable}
**Root cause hypothesis:** {your best read on why}
**Proposed refactor:** {one paragraph; the shape of the fix, not the fix itself}
**ADR exposure:** {does an ADR govern this? if yes, cite. If no, an ADR should accompany the refactor.}
**Out of scope (explicit):** {what this finding is NOT recommending}
### F2 — ...
(Repeat for each finding, top to bottom by priority.)
## Not recommended
{Smells you found but are deliberately NOT proposing. State why — e.g., "F-skip-1: The `utils/strings.py` module has 12 unrelated functions and looks like a junk drawer. Skipping because every function is < 10 lines and the cost of splitting exceeds the reading cost."}
## Pre-existing decisions (from ADRs) you should NOT undo
{One-bullet-each summary of ADRs that explain *why* something looks weird but is intentional. This protects the next reader from re-litigating.}
## Suggested order of operations
1.F{best-first} — {why it goes first}
2.F{next} — {why}
...
Pick up a finding with `/squid-refactor F{N}`; run the top 1–3 first, not all at once.

Step 7 — Hand off

Single block:

markdown
## Architecture review complete — {scope}
**Report:** {path or issue URL}
**Findings:** {N} ({severity breakdown})
**Top recommendation:** F1 — {title}
### Recommended next step
`/squid-refactor F1` (or paste the F1 body into a fresh `/squid-refactor` invocation). The first finding is the highest leverage by severity-over-effort.
### Open question (if applicable)
{Anything you found but couldn't conclude on without team input — e.g., "F4 hinges on whether the auth/billing boundary should be a hard-coded contract or a feature-flag-toggled split. Surfacing for team decision before refactoring."}
### ADR action
{One of:}
-"Recommend ADR-{NNNN} to record the resolution of F{X} when its refactor lands."
-"No ADRs in `docs/adr/` — recommend bootstrapping with the `adr` spec (`squid-scaffold/specs/adr.md`) before proceeding so this review's findings stay durable."
All versions