--- name: setup-122a0a8f1736 description: First-time ttal setup. Installs ttal, then runs ttal onboard for daemon, hooks, and config. Run this after cloning a ttal workspace template. --- # TTAL Setup Run setup steps automatically. Only pause when user action is required (Telegram bot creation, pasting tokens). Fix things yourself when possible. **Principle:** Do the work. Only ask the user when you genuinely need their input (secrets, choices). **UX Note:** Use `AskUserQuestion` for all user-facing questions. ## Context This skill runs inside the ttal-cli repository. All documentation is available in `docs/` (VitePress site) and templates are in `templates/`. When the user asks questions about ttal, read from `docs/` directly — no network requests needed. ## 1. Install ttal Check if ttal is installed: ```bash which ttal && echo "TTAL_OK=true" || echo "TTAL_OK=false" ``` If TTAL_OK=false, detect platform and install: - macOS: `brew tap tta-lab/ttal && brew install ttal` - Linux/other: `go install github.com/tta-lab/ttal-cli@latest` - If `go` not found: `brew install go` (macOS) or guide user to install Go Verify: `ttal version` ## 2. Run ttal onboard `ttal onboard` handles everything: prerequisites (tmux, taskwarrior, ffmpeg), workspace scaffold, taskwarrior UDAs, daemon install, worker hooks. When it runs `ttal init`, templates are found locally in this repo — no network clone needed. Just run it: ```bash ttal onboard ``` If onboard reports fixable issues, re-run with `ttal onboard --fix`. Parse its output for any errors that need user attention. After onboard completes, capture workspace path and verify team_path points to current directory: ```bash WORKSPACE=$(pwd) grep "team_path" ~/.config/ttal/config.toml ``` If team_path doesn't match current workspace, update it using `perl -i -pe` (portable across macOS and Linux): ```bash perl -i -pe "s|team_path = .*|team_path = \"$WORKSPACE\"|" ~/.config/ttal/config.toml ``` ## 3. Telegram Bot Setup (Optional) AskUserQuestion: "Would you like to set up Telegram integration? This lets you manage agents from your phone. (You can skip this and add it later.)" If yes: ### 3a. Get chat_id Tell user: 1. Open Telegram, search for `@userinfobot` 2. Send `/start` — it replies with your chat ID 3. Ask user to paste their chat ID Write the chat_id to config.toml under `[teams.default]`: ```bash perl -i -pe "s|chat_id = .*|chat_id = \"\"|" ~/.config/ttal/config.toml ``` If the `chat_id` key doesn't exist yet, append it under `[teams.default]`: ```bash perl -i -pe 's/(\[teams\.default\])/\1\nchat_id = ""/' ~/.config/ttal/config.toml ``` ### 3b. Create agent bots Discover agents in the workspace root (`$WORKSPACE`): ```bash shopt -s nullglob for dir in */CLAUDE.md; do dirname "$dir"; done ``` Token naming convention: uppercase the agent name and append `_BOT_TOKEN`. For example: agent `manager` → `MANAGER_BOT_TOKEN`, agent `yuki` → `YUKI_BOT_TOKEN`. For each agent, tell user: 1. Open Telegram, search for `@BotFather` 2. Send `/newbot` 3. Name: ` (ttal)` (or whatever they want) 4. Username: `_ttal_bot` (must end in `bot`) 5. Copy the bot token After user creates all bots, ask them to paste each token. Write to `~/.config/ttal/.env` using heredoc to avoid token exposure in process list: ```bash # For each agent (example for agent named "yuki"): cat >> ~/.config/ttal/.env << 'ENVEOF' YUKI_BOT_TOKEN= ENVEOF ``` ### 3c. Notification bot Tell user to create one more bot for system notifications (PR status, CI results): - Suggested username: `ttal_notify_bot` Write token as `DEFAULT_NOTIFICATION_BOT_TOKEN` to `.env`: ```bash cat >> ~/.config/ttal/.env << 'ENVEOF' DEFAULT_NOTIFICATION_BOT_TOKEN= ENVEOF ``` ### 3d. Verify ```bash ttal daemon restart # pick up new tokens ttal doctor # should show all green ``` ## 4. Verify & Done Run final health check: ```bash ttal doctor ``` If all green, print success with discovered agents and next steps: ``` ✓ ttal is ready! Your agents: (list discovered agent directories) Next steps: • Start your agents: ttal team start • Add a project by editing ~/.config/ttal/projects.toml directly • Create a task: ttal task add --project myapp "Build the thing" ``` If warnings/errors remain, explain each and offer to fix. --- Source attribution: tta-lab Original project: https://github.com/tta-lab/ttal-cli/blob/3576d21f223ff97eb258b868553b6266ad393847/.claude/skills/setup/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 GuionAI Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: tta-lab Original project: https://github.com/tta-lab/ttal-cli/blob/3576d21f223ff97eb258b868553b6266ad393847/.claude/skills/setup/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Product Management Roles: Backend Developer, DevOps / SRE, Technical Product Manager Specialties: API, Word Documents, Frontend, Git, Testing Tools: Telegram Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: aaaf214bc957ac8346608ab5d547583ff6653271efa61e8caa63f289571db2f7