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orchestration daemon for Telora - spawns and manages Claude Code instances","maintainers":[{"name":"syntelyos","email":"jeremy@syntelyos.com"}],"readme":"# @telora/daemon\n\nAgent orchestration daemon for Telora - spawns and manages Claude Code instances to work on deliveries autonomously.\n\n## Overview\n\nThe Telora daemon watches for active focuses in your Telora organization and spawns Claude Code Agent Teams to execute them. Each focus gets a single Agent Team that coordinates work across all deliveries and issues.\n\nKey features:\n- **Focus-level Agent Teams**: One team per focus manages all deliveries, building a task DAG and coordinating parallel execution\n- **Multi-repo support**: Multiple daemons can run against the same Telora org, each handling focuses for different repos\n- **Integration branch workflow**: Teams work on isolated branches, auto-merge to integration on success\n- **Worktree isolation**: Each team gets its own git worktree\n- **Dynamic delivery pickup**: Teams detect and incorporate new deliveries added mid-execution\n\n## Installation\n\nFor long-running daemon hosts, install globally so `telora-daemon update` and the in-process auto-updater can replace the binary in place:\n\n```bash\nnpm install -g @telora/daemon\n```\n\n`npx` is supported only for one-shot bootstrap commands (`init`, `connect`, `check-update`). The long-running daemon (`run`/`start`) **refuses** to run from an npx cache and exits with the global-install instruction: the cache makes the running binary effectively immutable -- `npm install -g` writes to the global prefix while the process keeps loading the cached copy, so a daemon launched via npx could never self-update. Install on disk (`npm install -g @telora/daemon`) and start `telora-daemon run`. (The refusal is overridable for false positives via `TELORA_ALLOW_NPX_RUN=1`, but a non-updating daemon is not recommended.)\n\n> **Note:** The `.mcp.json` file for Claude Code integration is auto-generated by `telora-daemon init`.\n\n## Quick Start\n\n### Option 1: Interactive Setup (Recommended)\n\n```bash\nnpm install -g @telora/daemon\ncd /path/to/your/repo\ntelora-daemon init\n```\n\nThe setup wizard will guide you through:\n- Telora URL configuration\n- Organization ID\n- Integration branch name\n- Max concurrent agents\n\nThen set your tracker ID and start the daemon:\n\n```bash\nexport TELORA_TRACKER_ID=your-tracker-id-here\ntelora-daemon run\n```\n\n### Option 2: Manual Setup\n\n1. **Get your Tracker ID** from Telora:\n   - Go to Settings → AI Work Trackers\n   - Click \"Generate Tracker ID\" on your profile\n   - Copy the tracker ID\n\n2. **Configure environment variables** in your repo:\n\n```bash\ncd /path/to/your/repo\n\n# Create .env file\ncat > .env << EOF\nTELORA_URL=https://your-telora-instance.supabase.co\nTELORA_TRACKER_ID=your-tracker-id-here\nTELORA_ORGANIZATION_ID=your-org-id-here\nEOF\n```\n\n3. **Start the daemon**:\n\n```bash\ntelora-daemon run\n```\n\n### Option 3: One-shot via npx\n\n```bash\nnpx -p @telora/daemon telora-daemon init   # interactive setup (one-shot)\nnpm install -g @telora/daemon              # then install on disk\ntelora-daemon run                          # start the daemon\n```\n\nnpx is fine for the one-shot `init`, but the long-running daemon refuses to run\nfrom an npx cache -- it can't update itself there. Install globally with\n`npm install -g @telora/daemon` and start `telora-daemon run` for any host you\nexpect to leave running.\n\n## Updating\n\n```bash\ntelora-daemon check-update   # report whether a newer version exists\ntelora-daemon update         # stop, install latest, apply migrations, restart\n```\n\nWhen installed globally or from a git checkout, the daemon also self-updates on a periodic timer (configurable via `autoUpdate.intervalMs` in `.telora/daemon.json`, or disable with `--no-auto-update`).\n\nThe long-running daemon refuses to run from an npx cache, so there is no auto-updating npx mode. If you reach an npx-cache daemon via the `TELORA_ALLOW_NPX_RUN` override, `telora-daemon update` cannot restart it in place (the running process loads from a cache it just cleared); install on disk instead -- `npm install -g @telora/daemon`, then `telora-daemon run`.\n\n## Configuration\n\nThe daemon is configured via environment variables:\n\n| Variable | Required | Default | Description |\n|----------|----------|---------|-------------|\n| `TELORA_URL` | Yes | - | Telora API URL |\n| `TELORA_TRACKER_ID` | Yes | - | Your tracker ID for authentication |\n| `TELORA_ORGANIZATION_ID` | Yes | - | Organization to watch for work |\n| `TELORA_REPO_PATH` | No | `cwd()` | Path to git repository |\n| `TELORA_INTEGRATION_BRANCH` | No | `integration` | Branch for agent merges |\n| `TELORA_WORKTREE_DIR` | No | `.telora/worktrees` | Directory for git worktrees |\n| `TELORA_LOG_DIR` | No | `.telora/logs` | Directory for agent logs |\n| `CLAUDE_CODE_PATH` | No | `claude` | Path to Claude Code executable |\n| `MAX_TOTAL_SESSIONS` | No | `5` | Max concurrent agents |\n| `SESSION_TIMEOUT_MS` | No | `3600000` | Session timeout (1 hour) |\n| `TOKEN_LIMIT` | No | `200000` | Max tokens per session |\n| `COST_LIMIT` | No | `10.0` | Max cost per session ($) |\n\n## CLI Options\n\n```bash\ntelora-daemon [options]\n\nOptions:\n  -V, --version        Output version number\n  -v, --verbose        Enable verbose logging\n  -c, --config <path>  Path to config file (default: .telora/daemon.json)\n  --dry-run            Print configuration and exit\n  -h, --help           Display help\n```\n\n## Config File\n\nInstead of environment variables, you can use a JSON config file. The daemon looks for `.telora/daemon.json` by default.\n\n```json\n{\n  \"teloraUrl\": \"https://your-telora-instance.supabase.co\",\n  \"organizationId\": \"your-organization-uuid\",\n  \"productId\": \"your-product-uuid\",\n  \"integrationBranch\": \"integration\",\n  \"maxTotalSessions\": 5\n}\n```\n\n**Configuration priority** (highest to lowest):\n1. Environment variables\n2. Config file values\n3. Default values\n\n**Security note:** The `trackerId` may live in `~/.telora/daemon.json` (mode 0600, written by the connect flow) or in the `TELORA_TRACKER_ID` environment variable. Env vars take priority. The home-scoped daemon.json is the same posture as `~/.aws/credentials` -- not committable.\n\n### Workstation tracking install model\n\nConnect time, the daemon detects `telora-ai` (a Python CLI shipped under\n`scripts/`) on `PATH`. If present, connect:\n\n1. Pre-populates the user's local tracking DB with the redeem-derived\n   credentials (`telora-ai config tracker_id ...`, etc.) -- this skips\n   the registration-code round-trip that Settings > AI Trackers normally\n   requires\n2. Merges `PostToolUse` and `UserPromptSubmit` hook entries into\n   `~/.claude/settings.json` so a fresh Claude Code session is tracked\n   end-to-end without manual `telora-ai setup-hooks`\n\nIf `telora-ai` is absent, connect prints a remediation hint and\ncontinues -- the daemon, MCP, and scaffolding parts of connect must\nsucceed even when tracking can't be wired automatically.\n\nWe picked detect-only (option c) over the alternatives:\n\n- **(a) pipx/uv install**: `telora-ai` is not on PyPI; no upstream\n  install target exists yet. A pipx install of a path-shipped script\n  doesn't generalise across machines that haven't checked out the repo.\n- **(b) Single-binary build / fold into daemon**: cleanest long-term but\n  out of scope here; it requires either a PyInstaller pipeline that\n  doesn't exist yet, or a TS rewrite of the tracking instrumentation.\n\nThe remediation hint points users at the documented bring-up so they can\nopt into tracking manually when they want it.\n\n### `.mcp.json` resolution model (option C)\n\nThe connect flow writes a credential-free `.mcp.json` so it can be committed and shared across collaborators:\n\n```json\n{\n  \"mcpServers\": {\n    \"telora-products\": {\n      \"command\": \"npx\",\n      \"args\": [\"-p\", \"@telora/mcp-products@latest\", \"telora-mcp-products\"]\n    }\n  }\n}\n```\n\nThe MCP server resolves credentials at startup in this order:\n\n1. `TELORA_TRACKER_ID` + `TELORA_URL` env vars (explicit override)\n2. `~/.telora/daemon.json` (written by `telora-daemon connect`)\n\nWe picked option (c) -- read from daemon.json -- over the alternatives:\n\n- **(a) Export from shell rc**: works only when the user's shell rc was sourced before `claude` was launched. Breaks under IDE-spawned Claude Code, `.envrc`-only setups, or any path where the rc didn't run.\n- **(b) Sourced `~/.telora/env`**: same brittleness as (a), plus a new file we'd have to teach the user about.\n- **(c) Read from `~/.telora/daemon.json`**: single source of truth, no shell-state coupling, same file the daemon already reads.\n\nThe trade-off: the MCP server has to do one filesystem read per startup. That's negligible compared to npx's cold-cache cost on the same path.\n\nAvailable config file fields:\n- `teloraUrl` - Telora API URL\n- `organizationId` - Organization UUID\n- `productId` - Product UUID (scopes daemon to one product; omit to handle all)\n- `repoPath` - Repository path\n- `worktreeDir` - Worktree directory\n- `integrationBranch` - Integration branch name\n- `claudeCodePath` - Claude Code executable path\n- `logDir` - Log directory\n- `maxTotalSessions` - Max concurrent agents\n- `sessionTimeoutMs` - Session timeout in milliseconds\n- `tokenLimit` - Max tokens per session\n- `costLimit` - Max cost per session in dollars\n\n## How It Works\n\n### Focus Team Execution Model\n\n1. **Focus polling**: The daemon polls Telora every 30 seconds for active focuses with an assigned agent role and queued deliveries\n2. **Filtering**: Only picks up focuses for the configured `productId` (if set)\n3. **Team spawning**: For each ready focus, spawns a single Claude Code Agent Team (one team per focus)\n4. **Task DAG**: The team lead reads all deliveries and issues, builds a dependency graph respecting delivery priority and file overlap\n5. **Parallel execution**: Workers execute issues in parallel where safe (no file conflicts), sequentially where needed\n6. **Delivery progression**: As issues complete, deliveries advance through workflow stages (coding -> verify -> done)\n7. **Merge on success**: When all deliveries are complete, the focus branch is merged to integration\n8. **Dynamic pickup**: If new deliveries are added to the focus mid-execution, the team incorporates them automatically\n\n### Key daemon modules\n\n- `focus-executor.ts` - Focus team lifecycle (spawn, monitor, completion)\n- `task-dag-builder.ts` - Pure function that builds dependency graphs from deliveries/issues\n- `focus-prompt-builder.ts` - Builds the team lead's prompt with all context\n- `delivery-lifecycle.ts` - Extracted guard evaluation, stage transition, git merge functions\n- `completion-handler.ts` - Per-delivery completion (used by team lead for sub-delivery transitions)\n- `spawner.ts` - Process spawning with Agent Teams mode always enabled\n\n## Multi-Repo Setup\n\nTo run agents on multiple repositories:\n\n1. Set `productId` in each daemon's `.telora/daemon.json` (or `TELORA_PRODUCT_ID` env var)\n2. Run one daemon per repository:\n\n```bash\n# Terminal 1 - Repo A (productId set in .telora/daemon.json)\ncd /path/to/repo-a\ntelora-daemon run\n\n# Terminal 2 - Repo B (productId set in .telora/daemon.json)\ncd /path/to/repo-b\ntelora-daemon run\n```\n\nEach daemon only picks up deliveries for the configured product.\n\n## Signals\n\n- `SIGINT` / `SIGTERM`: Graceful shutdown (waits for agents to checkpoint)\n- `SIGUSR1`: Print status of running agents\n\n## Running in Production vs Development\n\n**For production use**, always run the daemon with the compiled version:\n\n```bash\n# Global install (recommended -- enables self-update)\nnpm install -g @telora/daemon\ntelora-daemon run\n\n# Or from source\ncd packages/daemon\nnpm run build\nnpm start\n```\n\n**Do NOT use `npm run dev`** (watch mode) when agents are running. The file watcher will restart the daemon whenever source files change, which kills any running agents and may leave sessions in a stuck \"running\" state.\n\nIf you need to modify daemon code while agents are working:\n1. Wait for agents to complete\n2. Or stop the daemon gracefully (Ctrl+C)\n3. Make your changes\n4. Restart the daemon\n\n## Requirements\n\n- Node.js 20+\n- Claude Code CLI (`claude`) installed and authenticated\n- Git repository with write access\n- Active Telora account with AI Work Tracker\n\n## License\n\nMIT\n","readmeFilename":"README.md"}