244 lines
7.9 KiB
Bash
Executable file
244 lines
7.9 KiB
Bash
Executable file
#!/bin/bash
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#
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# Install Hindsight Agent Skill
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#
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# Usage:
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# curl -fsSL https://hindsight.vectorize.io/get-skill | bash
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#
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# Options:
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# --app <app> Target app: claude, opencode, codex
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#
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# Examples:
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# curl -fsSL https://hindsight.vectorize.io/get-skill | bash -s -- --app claude
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# curl -fsSL https://hindsight.vectorize.io/get-skill | bash -s -- --app opencode
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#
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set -e
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# Colors for output
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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BLUE='\033[0;34m'
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CYAN='\033[0;36m'
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BOLD='\033[1m'
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DIM='\033[2m'
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NC='\033[0m' # No Color
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print_info() {
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echo -e "${BLUE}ℹ${NC} $1"
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}
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print_success() {
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echo -e "${GREEN}✓${NC} $1"
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}
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print_error() {
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echo -e "${RED}✗${NC} $1"
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exit 1
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}
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print_warning() {
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echo -e "${YELLOW}⚠${NC} $1"
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}
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print_step() {
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echo ""
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echo -e "${BOLD}${CYAN}▸ $1${NC}"
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echo ""
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}
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print_banner() {
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echo ""
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# ANSI logo
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echo -e " \033[38;2;9;127;184m▄\033[0m\033[48;2;8;130;178m\033[38;2;5;133;186m▄\033[0m \033[48;2;10;143;160m\033[38;2;10;143;165m▄\033[0m\033[38;2;7;140;156m▄\033[0m "
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echo -e " \033[38;2;8;125;192m▄\033[0m \033[38;2;3;132;191m▀\033[0m\033[38;2;2;133;192m▄\033[0m \033[38;2;3;132;180m▄\033[0m\033[38;2;1;137;184m▄\033[0m\033[38;2;3;133;174m▄\033[0m \033[38;2;3;142;176m▄\033[0m\033[38;2;4;142;169m▀\033[0m \033[38;2;10;144;164m▄\033[0m "
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echo -e "\033[38;2;6;121;195m▀\033[0m\033[38;2;5;128;203m▀\033[0m\033[48;2;5;124;195m\033[38;2;3;125;200m▄\033[0m\033[38;2;2;126;196m▄\033[0m\033[48;2;3;128;188m\033[38;2;1;131;196m▄\033[0m\033[48;2;0;152;219m\033[38;2;2;131;191m▄\033[0m\033[38;2;1;141;196m▀\033[0m\033[38;2;1;135;183m▀\033[0m\033[38;2;1;148;198m▀\033[0m\033[48;2;1;156;202m\033[38;2;2;135;180m▄\033[0m\033[48;2;4;134;169m\033[38;2;1;137;177m▄\033[0m\033[38;2;3;138;173m▄\033[0m\033[48;2;6;137;165m\033[38;2;2;140;170m▄\033[0m\033[38;2;7;144;169m▀\033[0m\033[38;2;7;139;158m▀\033[0m"
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echo -e " \033[48;2;2;128;202m\033[38;2;2;124;201m▄\033[0m\033[48;2;1;130;201m\033[38;2;0;135;212m▄\033[0m\033[38;2;2;128;196m▄\033[0m \033[48;2;2;142;204m\033[38;2;7;138;199m▄\033[0m \033[38;2;1;135;186m▄\033[0m\033[48;2;1;142;186m\033[38;2;2;144;194m▄\033[0m\033[48;2;3;138;176m\033[38;2;2;134;176m▄\033[0m "
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echo -e " \033[48;2;8;118;200m\033[38;2;8;121;209m▄\033[0m\033[38;2;3;121;203m▀\033[0m \033[38;2;3;122;192m▀\033[0m\033[38;2;1;138;216m▀\033[0m\033[48;2;0;138;210m\033[38;2;3;128;198m▄\033[0m\033[48;2;0;126;188m\033[38;2;2;131;198m▄\033[0m\033[48;2;0;142;205m\033[38;2;3;132;193m▄\033[0m\033[38;2;1;140;196m▀\033[0m \033[38;2;4;134;175m▀\033[0m\033[48;2;13;135;167m\033[38;2;8;136;174m▄\033[0m "
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echo ""
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echo -e " ${BOLD}HINDSIGHT SKILL INSTALLER${NC}"
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echo -e " ${DIM}Give your AI agent persistent memory${NC}"
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echo ""
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}
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# Embedded SKILL.md content
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SKILL_CONTENT='---
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name: hindsight
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description: Give your agent persistent memory that works like human memory. Store facts, preferences, and context that persist across sessions.
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---
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# Hindsight Memory Skill
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You have access to persistent memory via the `hindsight-embed` CLI. Use it to remember important information about the user and recall it when relevant.
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## Setup (first time only)
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Run: `uvx hindsight-embed configure`
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## Commands
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### Store a memory
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Use `retain` to store important facts, preferences, decisions, or context:
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```bash
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uvx hindsight-embed retain "User prefers dark mode for all UIs"
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uvx hindsight-embed retain "Project uses Python 3.11 with FastAPI" --context work
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```
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### Recall memories
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Use `recall` to search for relevant memories before starting tasks:
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```bash
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uvx hindsight-embed recall "What are the user'"'"'s UI preferences?"
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uvx hindsight-embed recall "What tech stack does this project use?"
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```
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## When to Use
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### Store memories when you learn:
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- User preferences (coding style, tools, UI preferences)
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- Project context (tech stack, architecture decisions)
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- Personal information the user shares (name, role, company)
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- Important decisions or outcomes
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### Recall memories when:
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- Starting a new task (get relevant context first)
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- Making decisions that should consider user preferences
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- Working on a project where past context would help
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## Best Practices
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1. **Be specific**: Store "User prefers 2-space indentation" not "User has preferences"
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2. **Recall first**: Before starting tasks, recall relevant context
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3. **Use context tags**: Organize with `--context` (work, personal, preferences)
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'
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# Get skills directory for app (bash 3.x compatible)
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get_skills_dir() {
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case "$1" in
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claude) echo "$HOME/.claude/skills" ;;
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opencode) echo "$HOME/.opencode/skills" ;;
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codex) echo "$HOME/.codex/skills" ;;
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*) echo "" ;;
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esac
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}
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# Get app display name (bash 3.x compatible)
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get_app_name() {
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case "$1" in
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claude) echo "Claude Code" ;;
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opencode) echo "OpenCode" ;;
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codex) echo "Codex CLI" ;;
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*) echo "$1" ;;
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esac
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}
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# Parse arguments
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APP=""
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show_usage() {
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echo "Usage: $0 [--app <app>]"
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echo ""
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echo "Options:"
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echo " --app <app> Target app: claude, opencode, codex"
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echo ""
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echo "Examples:"
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echo " $0 --app claude"
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echo " $0 --app opencode"
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exit 1
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}
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while [[ $# -gt 0 ]]; do
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case $1 in
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--app)
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APP="$2"
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shift 2
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;;
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--help|-h)
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show_usage
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;;
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*)
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print_error "Unknown option: $1"
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;;
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esac
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done
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# Show banner
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print_banner
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# Validate app parameter
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if [ -z "$APP" ]; then
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echo -e "${DIM}Select your AI coding assistant:${NC}"
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echo ""
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echo " ${BOLD}1)${NC} Claude Code"
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echo " ${BOLD}2)${NC} OpenCode"
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echo " ${BOLD}3)${NC} Codex CLI"
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echo ""
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read -p "Enter choice [1]: " app_choice
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app_choice=${app_choice:-1}
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case $app_choice in
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1) APP="claude" ;;
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2) APP="opencode" ;;
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3) APP="codex" ;;
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*) APP="claude" ;;
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esac
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echo ""
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fi
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# Get skills directory for selected app
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SKILLS_DIR=$(get_skills_dir "$APP")
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APP_NAME=$(get_app_name "$APP")
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if [ -z "$SKILLS_DIR" ]; then
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print_error "Unknown app '$APP'. Supported: claude, opencode, codex"
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fi
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print_info "Installing for ${BOLD}$APP_NAME${NC}"
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# Step 1: Check for Python/uvx
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print_step "Checking prerequisites"
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if ! command -v python3 &> /dev/null && ! command -v uvx &> /dev/null; then
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print_error "Python 3 or uvx is required.\nInstall from https://python.org or https://docs.astral.sh/uv/"
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fi
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print_success "Python/uvx available"
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# Step 2: Configure LLM provider using the CLI
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print_step "Configuring LLM provider"
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# Install/run hindsight-embed configure
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if command -v uvx &> /dev/null; then
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uvx hindsight-embed configure
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else
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pip install -q hindsight-embed
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hindsight-embed configure
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fi
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# Step 3: Install skill to app's skills directory
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print_step "Installing skill to $APP_NAME"
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mkdir -p "$SKILLS_DIR/hindsight"
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# Write embedded SKILL.md content
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echo "$SKILL_CONTENT" > "$SKILLS_DIR/hindsight/SKILL.md"
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print_success "Installed to $SKILLS_DIR/hindsight/"
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# Done!
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echo ""
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echo -e "${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
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echo -e "${GREEN} ✓ Installation Complete!${NC}"
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echo -e "${GREEN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
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echo ""
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echo -e " The Hindsight skill is now available in ${BOLD}$APP_NAME${NC}."
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echo ""
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echo -e " ${DIM}Test the CLI:${NC}"
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echo -e " ${CYAN}uvx hindsight-embed retain \"Test memory\"${NC}"
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echo -e " ${CYAN}uvx hindsight-embed recall \"test\"${NC}"
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echo ""
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echo -e " ${DIM}$APP_NAME will automatically use the skill when relevant.${NC}"
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echo ""
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echo -e " ${DIM}Documentation:${NC} ${BLUE}https://hindsight.vectorize.io${NC}"
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echo ""
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