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Quick Context

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npx machina-cli add skill Alik-gushkan/claude-marketplace/quick-context --openclaw
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SKILL.md
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Quick Context

Generate a concise project summary for the current working directory (or $ARGUMENTS if provided).

Steps

  1. Detect project type and tech stack

    • Look for package.json, Cargo.toml, go.mod, pyproject.toml, Gemfile, pom.xml, build.gradle, composer.json, or similar manifest files
    • Read the manifest to identify: language, framework, dependencies, scripts
    • Check for .tool-versions, .nvmrc, .python-version for runtime versions
  2. Map the directory structure

    • Run tree -L 2 -I 'node_modules|.git|dist|build|__pycache__|.next|target|vendor' --dirsfirst to get an overview
    • Identify source directories, test directories, config files, CI/CD setup
  3. Identify key files

    • Read README.md (first 50 lines) if it exists
    • Check for CLAUDE.md, .claude/ directory, Dockerfile, docker-compose.yml
    • Look for entry points: src/index., src/main., app.*, manage.py, main.go
  4. Check recent activity

    • Run git log --oneline -10 --no-decorate to see recent commits
    • Run git diff --stat HEAD~5..HEAD 2>/dev/null to see recently changed files
  5. Present the summary in this format:

## Project: [name from manifest or directory]

**Tech Stack:** [language] + [framework] | [package manager] | [runtime version]
**Type:** [web app / CLI / library / API / monorepo / etc.]

### Structure
[tree output, annotated with purpose of key directories]

### Key Files
- `[path]` — [purpose]
- `[path]` — [purpose]

### Dependencies (Notable)
- [key deps with brief purpose]

### Recent Activity
[last 5 commits, one line each]

### Notes
[anything unusual: monorepo setup, custom build system, CLAUDE.md conventions, etc.]
  1. Keep the summary under 40 lines. Prioritize signal over completeness.

Source

git clone https://github.com/Alik-gushkan/claude-marketplace/blob/main/plugins/dev-toolkit/skills/quick-context/SKILL.mdView on GitHub

Overview

Quick Context generates a concise project summary for the current working directory or a provided path. It detects the project type from common manifests, maps the directory structure, identifies key files, and reports recent changes to give you a quick understanding of the codebase.

How This Skill Works

It first detects the project type and tech stack by locating manifests (package.json, Cargo.toml, go.mod, pyproject.toml, Gemfile, pom.xml, build.gradle, composer.json, etc.) and reading runtime versions. Next it maps the directory with tree -L 2 -I 'node_modules|.git|dist|build|__pycache__|.next|target|vendor' to identify source, test, and config directories. It then identifies key files by reading README.md (first 50 lines) and checking for CLAUDE.md, .claude/ directories, Dockerfile and docker-compose.yml, plus common entry points like src/index.*, src/main.*, app.*, manage.py, or main.go. Finally it checks recent activity using git log and git diff to surface recent commits and changes, and presents a structured summary.

When to Use It

  • When asked to summarize this project
  • When asked what is this codebase
  • When asked to give me context
  • When asked for quick context
  • When starting work on an unfamiliar codebase

Quick Start

  1. Step 1: Run in the repository or pass an optional [directory-path] argument.
  2. Step 2: The tool scans manifests, maps structure, and identifies key files.
  3. Step 3: Review the generated Project summary in the prescribed format.

Best Practices

  • Detect manifests first to determine language, framework, dependencies, and runtime versions.
  • Map the repository structure with tree using the specified ignore list to focus on source and config directories.
  • Identify key files by inspecting README.md (first 50 lines), CLAUDE.md, Dockerfile, docker-compose.yml, and common entry points.
  • Capture recent activity with git log --oneline -10 and git diff HEAD~5..HEAD to surface recent changes.
  • Present the final summary in the prescribed format, keeping it concise (about 40 lines) with clear sections.

Example Use Cases

  • A Next.js frontend with a Node.js API backend and a Docker setup.
  • A Python Django monorepo containing multiple services and shared libraries.
  • A Rust CLI tool with a small core library and a Makefile-based build.
  • A Go web API with separate frontend and backend repos and CI configuration.
  • A Java Maven project with microservices and a Jenkins/CI workflow.

Frequently Asked Questions

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