agentsclimarketplace

Claude code starter

Skill cassmtnr/claude-code-starter

Intelligent CLI that uses Claude to deeply analyze your project and generate tailored Claude Code configurations.

Install
npx -y skills add cassmtnr/claude-code-starter

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Analyze a project's tech stack and generate comprehensive Claude Code configuration files (.claude/ directory with CLAUDE.md, skills, agents, rules, and commands). Use when setting up Claude Code for a new or existing repository.

SKILL.md

9.8 KB, ~2.4k tokens by cl100k_base, as published. Nobody here has run it

Claude Code Starter

You are setting up Claude Code configuration for a project. Follow the flow below to analyze the project and generate all .claude/ configuration files.

Step 1: Detect Project Type

Check if this is a new project (empty or <3 source files) or an existing project.

For new projects, ask the user these questions:

  1. What are you building? (project description)
  2. Primary language? (TypeScript, JavaScript, Python, Go, Rust, Swift, Kotlin, Java, Ruby, C#, PHP, C++)
  3. Framework? (filtered by language — e.g. Next.js/React/Vue for TS/JS, FastAPI/Django/Flask for Python)
  4. Package manager? (filtered by language)
  5. Testing framework? (filtered by language, or "None")
  6. Linter/Formatter? (filtered by language, or "None")
  7. Project type? (Web App, API/Backend, CLI Tool, Library/Package, Mobile App, Desktop App, Monorepo, Other)

For existing projects, analyze the codebase:

  • Read package.json, pyproject.toml, Cargo.toml, go.mod, Gemfile, or equivalent
  • Detect languages, frameworks, package manager, testing, linting, formatting, bundler
  • Identify architecture patterns, directory structure, code conventions

Step 2: Create .claude/settings.json

Generate settings.json with permissions based on detected stack. Example:

{
  "$schema": "https://json.schemastore.org/claude-code-settings.json",
  "permissions": {
    "allow": [
      "Read(**)", "Edit(**)", "Write(.claude/**)", "Bash(git:*)",
      "Bash(npm:*)", "Bash(node:*)"
    ]
  }
}

Add language/framework-specific permissions (e.g. Bash(cargo:*) for Rust, Bash(pytest:*) for Python).

Step 3: Generate CLAUDE.md

Perform deep codebase analysis and generate .claude/CLAUDE.md following this structure:

Phase 1: Discovery

Read actual project files to discover:

  • Project identity (name, version, description, purpose)
  • Directory structure map (depth 3)
  • Tech stack deep scan (languages, frameworks, database, auth, API layer, styling, build tools, CI/CD)
  • Architecture pattern recognition (MVC, Clean, Hexagonal, etc.)
  • Entry points and key files
  • Code conventions (naming, imports, exports, function style, error handling)
  • Development workflow (scripts, env vars, pre-commit hooks, testing setup)
  • Domain knowledge (entities, workflows, integrations)

Phase 2: Write CLAUDE.md

Using ONLY discovered information, write .claude/CLAUDE.md with:

  • Project name + one-line description
  • Overview (purpose, audience, value proposition)
  • Architecture (pattern, directory structure, data flow, key files)
  • Tech stack table
  • Development setup (prerequisites, getting started, env variables)
  • Common commands
  • Code conventions (naming patterns, patterns to follow, anti-patterns)
  • Testing (commands, writing patterns)
  • Domain knowledge (entities, workflows)
  • Gotchas & important notes
  • Rules

Phase 3: Quality Check

Verify every section contains project-specific content, not generic boilerplate. Skip sections without real content.

Step 4: Generate Skills

Write each skill file to .claude/skills/ with YAML frontmatter (name, description, globs).

Core Skills (ALWAYS generate all 8):

  1. .claude/skills/pattern-discovery.md — Analyze codebase to discover and document patterns. Include project-specific search strategies based on the actual directory structure and file patterns found.

  2. .claude/skills/systematic-debugging.md — 4-phase methodology: Reproduce, Locate, Diagnose, Fix. Tailor reproduction steps to the project's actual test runner and dev server commands.

  3. .claude/skills/testing-methodology.md — AAA pattern (Arrange, Act, Assert). Use the project's actual testing framework syntax (e.g., describe/it for Jest/Vitest, def test_ for pytest). Include mocking patterns specific to the stack.

  4. .claude/skills/iterative-development.md — TDD workflow loop: write failing test → implement → verify → refactor. Use the project's actual test command and lint command.

  5. .claude/skills/commit-hygiene.md — Atomic commits, conventional commit format, size thresholds (±300 lines), when-to-commit triggers.

  6. .claude/skills/code-deduplication.md — Check-before-write principle. Search existing code before writing new code. Include project-specific glob patterns for common file types.

  7. .claude/skills/simplicity-rules.md — Function length limits (≤40 lines), file limits (≤300 lines), cyclomatic complexity constraints. Decomposition patterns.

  8. .claude/skills/security.md — .gitignore entries for the stack, environment variable handling patterns, OWASP checklist items relevant to the detected framework.

Framework-Specific Skills (ONLY if detected):

Generate the appropriate skill based on detected frameworks:

FrameworkSkill FileKey Content
Next.jsnextjs-patterns.mdApp Router, Server/Client Components, data fetching, middleware
React (no Next.js)react-components.mdHooks, component patterns, state management, performance
FastAPIfastapi-patterns.mdRouter organization, dependency injection, Pydantic models, async
NestJSnestjs-patterns.mdModules, controllers, services, decorators, pipes, guards
SwiftUIswiftui-patterns.mdProperty wrappers, MVVM, navigation, previews
UIKituikit-patterns.mdView controllers, Auto Layout, delegates, MVC
Vaporvapor-patterns.mdRoutes, middleware, Fluent ORM, async controllers
Jetpack Composecompose-patterns.md@Composable, remember, ViewModel, navigation
Android Viewsandroid-views-patterns.mdActivities, Fragments, XML layouts, ViewBinding
Vue/Nuxtvue-patterns.mdComposition API, composables, Pinia, routing
Djangodjango-patterns.mdModels, views, serializers, middleware, admin
Railsrails-patterns.mdMVC, ActiveRecord, concerns, service objects
Springspring-patterns.mdBeans, controllers, services, repositories, AOP

Tailor ALL skill content to the specific project's patterns, file structure, and conventions discovered during analysis.

Step 5: Generate Agents

Write 2 agent files to .claude/agents/:

.claude/agents/code-reviewer.md

---
name: code-reviewer
description: Reviews code for quality, security issues, and best practices
tools:
  - Read
  - Grep
  - Glob
  - "Bash(biome check .)"  # Use actual lint command
disallowed_tools:
  - Write
  - Edit
model: sonnet
---

Body: Instructions for reviewing code quality, security, naming conventions, test coverage, and adherence to project patterns.

.claude/agents/test-writer.md

---
name: test-writer
description: Generates comprehensive tests for code
tools:
  - Read
  - Grep
  - Glob
  - Write
  - Edit
  - "Bash(bun test)"  # Use actual test command
model: sonnet
---

Body: Instructions for writing tests using the project's actual testing framework, following existing test patterns.

Step 6: Generate Rules

Write rule files to .claude/rules/:

Always Generate:

  • .claude/rules/code-style.md — Formatting tool, comment style, error handling, git commit conventions.

Conditional (by language):

LanguageFileYAML pathsKey Rules
TypeScripttypescript.md["**/*.ts", "**/*.tsx"]Strict mode, type annotations, import style
Pythonpython.md["**/*.py"]Type hints, docstrings, import ordering
Swiftswift.md["**/*.swift"]Access control, optionals, protocol-oriented
Gogo.md["**/*.go"]Error handling, interfaces, package naming
Rustrust.md["**/*.rs"]Ownership, error handling, trait patterns

Each rule file needs YAML frontmatter with paths for file matching.

Step 7: Generate Commands

Write 5 command files to .claude/commands/:

.claude/commands/task.md

---
allowed-tools: ["Read", "Write", "Edit", "Glob"]
description: "Start or switch to a new task"
argument-hint: "<task description>"
---

Instructions to update .claude/state/task.md with new task, set status to "In Progress".

.claude/commands/status.md

---
allowed-tools: ["Read", "Glob", "Bash(git status)"]
description: "Show current task and session state"
---

Instructions to read task.md, show git status, summarize current state.

.claude/commands/done.md

---
allowed-tools: ["Read", "Write", "Edit", "Glob", "Bash(git:*)", "Bash(bun test)"]
description: "Mark current task complete"
---

Instructions to run tests, lint, verify, update task.md status to "Done".

.claude/commands/analyze.md

---
allowed-tools: ["Read", "Glob", "Grep"]
description: "Deep analysis of a specific area"
argument-hint: "<area or file path>"
---

Instructions to perform thorough analysis of specified area.

.claude/commands/code-review.md

---
allowed-tools: ["Read", "Glob", "Grep", "Bash(git diff)"]
description: "Review code changes for quality and security"
---

Instructions to review staged/unstaged changes.

Output Summary

After generating all files, output a brief summary:

  • List of files created
  • Any gaps found (missing config files, unclear patterns)
  • Suggested next steps

Important Guidelines

  1. Be specific, not generic. Every file must contain project-specific content.
  2. Reference real files. Use path/to/file.ts:lineNumber format.
  3. Use actual commands. Reference the project's real test/lint/build commands.
  4. Skip what doesn't apply. Don't generate framework skills for frameworks not in use.
  5. Respect existing files. If .claude/ files exist, read and preserve manually-added content.

What ships with it: 34 files

545.2 KB alongside SKILL.md, 17 of them executable

.githooks/

src/

Gives 0 of the 12 instructions most context ai engineering skills give in ~2.4k tokens

Counted across 1,193 of the 1,976 authors here whose files we hold, read 2026-08-07

  • Dispatch a fresh implementer subagent per taskin 48 of 1193, across 19 files
  • Dispatch a final code reviewer after all tasksin 33 of 1193, across 8 files
  • Provide full task text to the subagentin 30 of 1193, across 9 files
  • Review spec compliance before code qualityin 27 of 1193, across 10 files
  • Make the hook script executablein 26 of 1193, across 8 files
  • Re-snapshot after navigation or DOM changesin 25 of 1193, across 19 files
  • Read files before editing themin 22 of 1193, across 11 files
  • Answer subagent questions before proceedingin 22 of 1193, across 7 files
  • Mark task complete in TodoWrite after approvalin 22 of 1193, across 6 files
  • Merge hook into existing settingsin 21 of 1193, across 3 files
  • Ask if installation is global or projectin 20 of 1193, across 2 files
  • Copy the hook script to target locationin 20 of 1193, across 2 files

Said here and by no other author read

  • Generate the .claude directory configuration files
  • Ask the user questions for new project setup
  • Analyze the codebase to detect the tech stack
  • Generate settings.json with correct permissions
  • Generate CLAUDE.md using only discovered information
  • Verify generated sections contain project-specific content

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 327,069. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.