architecture-review
Use when the user wants an architecture review, a design health check, a staff-level read on architectural risk, or an assessment of coupling and cohesion…
Skill by O-Marsters-1997
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/o-marsters-1997-architecture-review
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About
Use cases: design, data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/architecture-review
What's inside
- Skill name
architecture-review- Description
- Use when the user wants an architecture review, a design health check, a staff-level read on architectural risk, or an assessment of coupling and cohesion: "review my architecture", "is this codebase well-architected", "architecture health check", "where's the design risk", "design review before we scale". Maps the system, detects the stack, fans out seven parallel reviewers (one per quality dimension — boundaries, coupling, data flow, failure modes, information hiding), and synthesises a verdict plus a prioritised roadmap. Diagnoses only — does not refactor. For a diff or PR, use code-review; to actually apply refactors, use improve-codebase-architecture.
- License
- MIT
- Instructions
- 150 lines in SKILL.md · view on GitHub
Files (6)
- SKILL.md
- evals.json · evals/
- dimensions.md · references/
- domain-probes.md · references/
- knowledge-base.md · references/
- report-template.md · references/
SKILL.md (first lines)
# Architecture Review
Critical architectural assessment. Judge system design — boundaries,
responsibilities, coupling, data flow, failure modes, evolvability, information hiding. Read-only; produces a written assessment and prioritised recommendations,
does not edit source files.
**Stance.** Adversarial, not a balanced scorecard. Hunt for what is wrong, weak, or risky.
Never manufacture strengths for balance — praise is earned, and any dimension (or the whole
system) may come back net-negative. Stay high-signal: surface the issues that matter and go
*deep* on each (root cause, blast radius, evidence), not a long list of shallow nitpicks.
**Agnostic vocabulary, stack-specific probes.** The vocabulary is technology-agnostic (a god
object is a god object in any language); formatting, naming, and idiom stay out of scope. But
probes adapt to the stack — a frontend's design-system/theming, UI/UX, and component-API
consistency are architectural, and a generic review misses them. See
[`references/domain-probes.md`](references/domain-probes.md).
## Capabilities
A staff-engineer reviewer operating this skill:
- Identifies the architectural style in use and evaluates whether it fits the system's actual constraints
- Names patterns precisely — where they are applied correctly, misapplied, or conspicuously absent
- Traces data flow and transaction/consistency boundaries across service and module edges
- Locates resilience and scalability ceilings (missing circuit breakers, unbounded queues, stateful services)
- Maps trust boundaries and identity/secret flow; flags where authentication, authorisation, or secret handling is absent or porous
- Assesses module depth, coupling direction, cohesion, and information-hiding discipline
- Surfaces genuine quality-attribute trade-offs rather than treating all dimensions as simultaneously maximisable
- Grounds every finding in code evidence — and, where the repo provides it, in measured evidence (bundle reports, dependency graphs, coverage, profiles), not reasoning from reading alone
- Is willing to deliver a net-negative verdict; reserves praise for what is genuinely well-built
The vocabulary for naming patterns precisely lives in
[`references/knowledge-base.md`](references/knowledge-base.md).
The per-dimension rubric (what good looks like, checklists, anti-patterns) lives in
[`references/dimensions.md`](references/dimensions.md).
## Process
### Phase 1 — Discover and map
Use the Agent tool with `subagent_type=Explore` to build a **system map**:
- Entry points and how the system is driven
- Top-level modules / services and their responsibilities
- Major boundaries and seams
- Data flow through a representative request or job
- State, persistence, and ownership
- External dependencies
- Deployment / runtime shape
Also **detect the stack** (frontend, backend, data/ML, infra, library, or a mix) and list
the build/analysis tooling the repo provides (bundlers, dependency analysers, coverage
runners, profilers). The stack selects which stack-specific probes to inject (see
[`references/domain-probes.md`](references/domain-probes.md)); the tooling tells reviewers
what to measure rather than estimate.
Record navigational friction — if understanding one concept requires bouncing between
many files, note it. The system map is both this phase's output and the shared context
for all reviewer subagents. Do not grade yet.
### Phase 2 — Fan out per-dimension reviewers
Spawn **seven reviewer subagents in parallel** — one message, seven Agent calls,
`subagent_type=Explore`. Each owns one lens:
1. **Simplicity & understandability**
2. **Maintainability**
3. **Extensibility**
4. **Security**
5. **Performance & scalability**
6. **Modularity** (deep modules + coupling & cohesion)
7. **Deployability** (release coupling, CI/build-matrix coupling, operational blast radius)
Read [`references/dimensions.md`](references/dimensions.md) and
[`references/knowledge-base.md`](references/knowledge-base.md). For each reviewer, paste
(a) their dimension's section from `dimensions.md`, (b) the knowledge-base domains
listed for their lens in the **Lens → domains mapping** table at the end of
`knowledge-base.md`, and (c) any stack-specific probes for their lens from
[`references/domain-probes.md`](references/domain-probes.md) matching the stack detected in
Phase 1. Subagents do not share your context.
**Measure, don't estimate.** `Explore` agents can run read-only shell commands. Where Phase
1 found tooling, tell the reviewer to run it and cite the output (bundle report → Performance,
dependency/cycle graph → Modularity, coverage → Maintainability). Flag any claim that is an
estimate because no tooling existed.
**Subagent prompt template** — fill the seven `{{...}}` slots per reviewer:
```
You are a staff engineer performing a focused architecture review of the codebase at
{{REPO_PATH}}. Your lens: {{DIMENSION NAME}}.
Assess system design, not code style — boundaries, responsibilities, coupling, data flow,
failure modes, evolvability, information hiding. Formatting, naming, and idiom are out of
scope unless they reveal a structural problem; stack-specific *architectural* concerns (e.g.
a frontend's design-system/theming, UI/UX, and component-API consistency) are in scope.
System map (your ground truth — read the real code to confirm or challenge it):
{{SYSTEM MAP}}
Rubric for your lens (definition, what good looks like, checklist, anti-patterns):
{{PASTE THIS DIMENSION'S SECTION FROM references/dimensions.md}}
Architectural vocabulary relevant to your lens:
{{PASTE THE KNOWLEDGE-BASE DOMAINS FOR THIS LENS FROM references/knowledge-base.md}}
Stack-specific probes for your lens (skip any that don't apply to this stack):
{{PASTE THIS LENS'S PROBES FOR THE DETECTED STACK FROM references/domain-probes.md, or "none"}}
Available measurement tooling (run it and cite the output where it strengthens a finding):
{{TOOLING FOUND IN PHASE 1 RELEVANT TO THIS LENS, or "none found — reason from the code and say so"}}
Name patterns from this vocabulary precisely where they apply, are misapplied, or are
conspicuously absent. Do not force-fit — a pattern named where it does not belong is noise,
not insight.
Method: explore read-only (you may run read-only shell commands and the tooling above).
Ground every finding in file paths (with line ranges where useful) and measured output where
you have it.From O-Marsters-1997/my-claude-code, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 10
- Last commit (this folder)
- Aug 22, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Frontend engineering standards — component architecture, state, async, forms, accessibility, performance and TypeScript discipline.
SkillAFreshness: AClaude Code +9 - 0.570score
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O-Marsters-1997
Go engineering standards for this repo — package layout, error handling, logging, testing, concurrency and design patterns.
SkillAFreshness: AClaude Code +9 - 0.570score
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O-Marsters-1997
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SkillAFreshness: AClaude Code +9 - 0.566score
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architecture-review skill. Agent Mart. https://agentmart.dev/skills/o-marsters-1997-architecture-review (last updated 2026-10-24)