Interactive installer for Everything Claude Code — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "configure-ecc" skill from askskill: 1. Download https://raw.githubusercontent.com/affaan-m/ECC/main/skills/configure-ecc/SKILL.md 2. Save it as ~/.claude/skills/configure-ecc/SKILL.md 3. Reload skills and tell me it's ready
An interactive, step-by-step installation wizard for the Everything Claude Code project. Uses AskUserQuestion to guide users through selective installation of skills and rules, then verifies correctness and offers optimization.
This skill must be accessible to Claude Code before activation. Two ways to bootstrap:
/plugin install ecc@ecc — the plugin loads this skill automatically~/.claude/skills/configure-ecc/SKILL.md, then activate by saying "configure ecc"Before any installation, clone the latest ECC source to /tmp:
rm -rf /tmp/everything-claude-code
git clone https://github.com/affaan-m/everything-claude-code.git /tmp/everything-claude-code
Set ECC_ROOT=/tmp/everything-claude-code as the source for all subsequent copy operations.
If the clone fails (network issues, etc.), use AskUserQuestion to ask the user to provide a local path to an existing ECC clone.
Use AskUserQuestion to ask the user where to install:
Question: "Where should ECC components be installed?"
Options:
- "User-level (~/.claude/)" — "Applies to all your Claude Code projects"
- "Project-level (.claude/)" — "Applies only to the current project"
- "Both" — "Common/shared items user-level, project-specific items project-level"
Store the choice as INSTALL_LEVEL. Set the target directory:
TARGET=~/.claudeTARGET=.claude (relative to current project root)TARGET_USER=~/.claude, TARGET_PROJECT=.claudeCreate the target directories if they don't exist:
mkdir -p $TARGET/skills $TARGET/rules
Default to Core (recommended for new users) — copy .agents/skills/* plus skills/search-first/ for research-first workflows. This bundle covers engineering, evals, verification, security, strategic compaction, frontend design, and Anthropic cross-functional skills (article-writing, content-engine, market-research, frontend-slides).
Use AskUserQuestion (single select):
Question: "Install core skills only, or include niche/framework packs?"
Options:
- "Core only (recommended)" — "tdd, e2e, evals, verification, research-first, security, frontend patterns, compacting, cross-functional Anthropic skills"
- "Core + selected niche" — "Add framework/domain-specific skills after core"
- "Niche only" — "Skip core, install specific framework/domain skills"
Default: Core only
If the user chooses niche or core + niche, continue to category selection below and only include those niche skills they pick.
There are 7 selectable category groups below. The detailed confirmation lists that follow cover 45 skills across 8 categories, plus 1 standalone template. Use AskUserQuestion with multiSelect: true:
Question: "Which skill categories do you want to install?"
Options:
- "Framework & Language" — "Django, Laravel, Spring Boot, Quarkus, Go, Python, Java, Frontend, Backend patterns"
- "Database" — "PostgreSQL, ClickHouse, JPA/Hibernate patterns"
- "Workflow & Quality" — "TDD, verification, learning, security review, compaction"
- "Research & APIs" — "Deep research, Exa search, Claude API patterns"
- "Social & Content Distribution" — "X/Twitter API, crossposting alongside content-engine"
- "Media Generation" — "fal.ai image/video/audio alongside VideoDB"
- "Orchestration" — "dmux multi-agent workflows"
…
Apply modern, safe, idiomatic C++ standards for writing, review, and refactoring.
Refine retrieved context iteratively to improve subagent understanding and output quality.
Fetches up-to-date framework docs for setup, APIs, and code examples.
Conduct multi-source web research and produce cited, source-attributed reports.
Design adaptive agent workflows with eval gates and reusable skill extraction.
Speed up complex tasks with parallel execution while preserving correctness.