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Agent skill

Architecture Selection

by rsmdt in rsmdt/the-startup

System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria.

MITAuto-check passedBackend & APIs

Install Architecture Selection

skills CLI
$ npx skills add rsmdt/the-startup --skill architecture-selection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rsmdt/the-startup architecture-selection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rsmdt/the-startup.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/team/skills/development/architecture-selection .claude/skills/architecture-selection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
architecture-selection
GitHub stars
551
Token cost
~1.2k tokens
SKILL.md length
473 words
Files
6
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria.

  • Works in 5 steps: Gather Requirements → Evaluate Patterns → Select Architecture → …
  • Designing system architectures
  • SKILL.md covers Persona, Interface, Constraints and Reference Materials, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Architecture Selection is an agent skill from rsmdt/the-startup. System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `examples/adrs/001-example-adr.md`, `examples/architecture-patterns.md` and `reference/architecture-patterns.md`).

It sits in Backend & APIs, covering Microservices, Software architecture and Event-driven systems. The repository describes itself as: The Agentic Startup - A collection of Claude Code commands, skills, and agents. The licence is MIT.

When your agent uses it

  • Designing system architectures
  • Evaluating patterns
  • Planning scalability

Example prompts

  • “/architecture-selection”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Gather Requirements
  2. Evaluate Patterns
  3. Select Architecture
  4. Document Decision
  5. Recommend Next Steps

What it can do on your machine

Read from SKILL.md and the folder at commit 88d447c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Architecture Selection loads about 1.2k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 473 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from rsmdt/the-startup at commit 88d447c, republished under its MIT licence (© rsmdt). 473 words, ~1,226 tokens.

Download SKILL.mdSave it as .claude/skills/architecture-selection/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
architecture-selection
description
System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.

Persona

Act as a system architecture advisor who guides teams in selecting and implementing architecture patterns matched to their requirements, team capabilities, and scalability needs. You balance pragmatism with forward-thinking design.

Architecture Target: $ARGUMENTS

Interface

EvaluationCriteria { teamSize: string // e.g., "< 10", "> 20" domainComplexity: SIMPLE | MEDIUM | COMPLEX scalingNeeds: UNIFORM | VARIED | ASYNC | UNPREDICTABLE opsMaturity: LOW | MEDIUM | HIGH timeToMarket: FAST | MEDIUM | SLOW }

ArchitectureRecommendation { pattern: MONOLITH | MICROSERVICES | EVENT_DRIVEN | SERVERLESS | HYBRID rationale: string tradeoffs: string migrationPath: string }

TechnologyScore { name: string fit: number // 1-5 maturity: number // 1-5 teamSkills: number // 1-5 performance: number // 1-5 operations: number // 1-5 cost: number // 1-5 weighted: number // calculated }

State { target = $ARGUMENTS criteria: EvaluationCriteria candidates: ArchitectureRecommendation[] selected: ArchitectureRecommendation technologies: TechnologyScore[] }

Constraints

Always:

  • Evaluate at least 2 candidate patterns before recommending.
  • Document trade-offs for every recommendation.
  • Consider team capabilities and ops maturity, not just technical fit.
  • Provide a migration path from current state when applicable.
  • Use ADR format for architecture decisions.

Never:

  • Recommend patterns based on resume-driven development (choosing tech for experience).
  • Skip trade-off analysis for any recommendation.
  • Assume microservices are always better than monoliths.
  • Ignore operational complexity when evaluating patterns.
  • Recommend scaling before measuring actual bottlenecks.

Reference Materials

  • reference/architecture-patterns.md — Monolith, microservices, event-driven, serverless with diagrams and trade-offs
  • reference/c4-model.md — System context, container, component, and code level diagrams
  • reference/scalability-and-reliability.md — Horizontal scaling, caching, database scaling, circuit breakers

Workflow

1. Gather Requirements

Analyze target context for:

  • Team size and structure
  • Domain complexity and bounded contexts
  • Scaling requirements (read/write patterns, peak loads)
  • Operational maturity (CI/CD, monitoring, on-call)
  • Time-to-market pressure
  • Existing infrastructure and constraints

Build EvaluationCriteria from gathered information.

Show full SKILL.md (224 more words)Show less
2. Evaluate Patterns

Use the selection guide below to identify candidate patterns:

FactorMonolithMicroservicesEvent-DrivenServerless
Team SizeSmall (<10)Large (>20)AnyAny
Domain ComplexitySimpleComplexComplexSimple-Medium
Scaling NeedsUniformVariedAsyncUnpredictable
Time to MarketFast initiallySlower startMediumFast
Ops MaturityLowHighHighMedium

Read reference/architecture-patterns.md for detailed pattern analysis.

Score each candidate pattern against criteria. Identify anti-patterns to avoid:

  • Big Ball of Mud — no clear architecture => establish bounded contexts
  • Distributed Monolith — microservices without independence => true service boundaries
  • Premature Optimization — scaling before needed => start simple, measure, scale
  • Golden Hammer — same solution for every problem => evaluate each case
  • Ivory Tower — architecture divorced from reality => evolutionary architecture
3. Select Architecture

Select highest-scoring pattern with migration feasibility.

For technology selection, use weighted evaluation matrix: Weights: Fit(25%), Maturity(15%), Skills(20%), Perf(15%), Ops(15%), Cost(10%)

Read reference/c4-model.md when creating architecture documentation. Read reference/scalability-and-reliability.md when detailing scaling strategy.

4. Document Decision

Write an ADR using the following structure:

  • Status — Proposed | Accepted | Deprecated | Superseded
  • Context — What decision needs to be made and why
  • Decision — The selected architecture with rationale
  • Consequences — Positive, negative, and neutral impacts
  • Alternatives Considered — Each with pros, cons, and rejection reason
5. Recommend Next Steps

match (decision) { new system => Create C4 diagrams, define bounded contexts, plan infrastructure migration => Define incremental migration plan with rollback strategy review => List specific improvements with trade-off analysis }

© rsmdt, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files in plugins/team/skills/development/architecture-selection of rsmdt/the-startup.

  • SKILL.md
  • examples/adrs/001-example-adr.md
  • examples/architecture-patterns.md
  • reference/architecture-patterns.md
  • reference/c4-model.md
  • reference/scalability-and-reliability.md

Open the folder on GitHubat commit 88d447c

Compare with similar skills

Architecture Selection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Architecture Selection compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Architecture Selection this skillrsmdt/the-startup551—~1.2kAutomated safety check: PassMIT
Anth Architecture Variantsjeremylongshore/tons-of-skills-marketplace2.8k—~1.9kAutomated safety check: PassMIT
AWS Serverless Edazxkane/aws-skills3674 repos~3.2kAutomated safety check: PassMIT
NestJS Modular Monolith Architecttech-leads-club/agent-skills7k—~3.9kAutomated safety check: PassCC-BY-4.0
Architecture Pattern Selectoralirezarezvani/claude-cto-team117—~1.6kAutomated safety check: PassMIT
Microservices ArchitectJeffallan/claude-skills12k—~1.8kAutomated safety check: PassMIT

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Categories

Questions about Architecture Selection

What does Architecture Selection do?

System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Architecture Selection is an agent skill from rsmdt/the-startup. System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria.

When should I use Architecture Selection?

Architecture Selection fits situations like: designing system architectures; evaluating patterns; planning scalability.

How do I install Architecture Selection in Claude Code?

Run `npx skills add rsmdt/the-startup --skill architecture-selection -a claude-code`. Or copy the skill folder (plugins/team/skills/development/architecture-selection in rsmdt/the-startup) into .claude/skills/architecture-selection in your project. Claude Code loads it when a task matches its description.

How do I install Architecture Selection in Codex?

Run `npx skills add rsmdt/the-startup --skill architecture-selection -a codex`. Or copy the skill folder (plugins/team/skills/development/architecture-selection in rsmdt/the-startup) into .agents/skills/architecture-selection in your project. Codex loads it when a task matches its description.

Can I use Architecture Selection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rsmdt/the-startup --skill architecture-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/architecture-selection, .gemini/skills/architecture-selection, .github/skills/architecture-selection and .opencode/skills/architecture-selection in your project.

What does Architecture Selection need to run?

SKILL.md names no scripts, command-line tools or credentials: Architecture Selection is instructions for the agent only.

Does Architecture Selection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Architecture Selection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Architecture Selection use?

Architecture Selection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Architecture Selection use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Architecture Selection?

Skills that share tags, products or a category with Architecture Selection: Anth Architecture Variants (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), AWS Serverless Eda (zxkane/aws-skills, 367 stars), NestJS Modular Monolith Architect (tech-leads-club/agent-skills, 7k stars) and Architecture Pattern Selector (alirezarezvani/claude-cto-team, 117 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Architecture Selection?

rsmdt (a GitHub user) maintains it in rsmdt/the-startup, which has 551 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on August 3, 2026.

Source: rsmdt/the-startup on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.