Usage¶
Day-to-day operation of Pynchy — managing groups, scheduling tasks, and talking to your agents.
What You Can Do¶
- Channels — Message your assistant from WhatsApp, Slack, or Discord (plugin-provided — more can be added)
- Workspaces — Bind a chat to reusable profiles for prompts, tools, skills, repositories, and security policy
- Admin channel — Your private channel (self-chat) for admin control; every other group is completely isolated
- Persistent memory — Agents save and recall facts across sessions using structured memory tools with ranked search (plugin-provided backend)
- Scheduled tasks — Recurring jobs that run the selected agent core and can message you back
- Personalization repository — Keep settings, LiteLLM routes, skills, and automations in an independent private repository
- Agent cores — Choose which LLM powers your agents — Claude SDK, OpenAI SDK, Codex CLI, or plugin-provided cores
- Control plane — Inspect local or remote operational state through fail-closed listeners and bearer authentication
- Integrations — Connect your workspaces to Google, GitHub, mail, Slack, Linear, and other external services
- Web access — Search and fetch content through configured browser tools
- Container isolation — Agents sandboxed in Apple Container (macOS) or Docker (macOS/Linux)
Talking to Your Assistant¶
Talk to your assistant with the trigger word (default: @Pynchy):
@Pynchy send an overview of the sales pipeline every weekday morning at 9am (has access to my Obsidian vault folder)
@Pynchy review the git history for the past week each Friday and update the README if there's drift
@Pynchy every Monday at 8am, compile news on AI developments from Hacker News and TechCrunch and message me a briefing
From the Admin channel (your self-chat), you can manage groups and tasks:
@Pynchy list all scheduled tasks across groups
@Pynchy pause the Monday briefing task
@Pynchy join the Family Chat group
Messaging During Active Tasks¶
When the agent is busy (handling a user message or scheduled task), new messages behave differently depending on prefix:
btw ... adds context to in-flight work ("btw the file is in /tmp/data.csv"). The agent sees it as a follow-up message.
todo ... queues an item for later without derailing the current task ("todo also rename the config keys when you're done"). The agent views and manages the todo list via list_todos and complete_todo MCP tools.
A normal message (no prefix) interrupts the active task — the container stops and your new message starts fresh.
Customizing¶
Start conversationally, then put repeatable channel, workspace, and security policy in data/personalization/pynchy.toml when you need it to survive restarts and deployments. For example, you can ask Pynchy to help you:
- "Change the trigger word to @Bob"
- "Remember in the future to make responses shorter and more direct"
- "Add a custom greeting when I say good morning"
- "Store conversation summaries weekly"
Detailed Guides¶
| Topic | What it covers |
|---|---|
| Channels | WhatsApp, Slack, and Discord — multi-channel sync |
| Control plane | Local Unix socket, remote bearer authentication, rate limits, and deployment access |
| Groups | Group management, admin channel privileges |
| Workspace configuration | Compose profiles and bind workspaces to configured chats |
| Memory | Structured memory tools, file-based memory, conversation archives |
| Scheduled tasks | Task types, MCP tools, execution model |
| Personalization repository | Layered settings, file-backed automations, custom skills, and CI validation |
| Agent cores | LLM framework selection, LiteLLM gateway |
| Prompts | System prompt extensions via profiles and workspaces |
| MCP servers | Adding external tool servers, environment variables, multi-tenant setup |
| Host capabilities | Computer use, screenshots, and local speech services for the host desktop |
| Tool Trust | Configure tool trust declarations — control when agents need human approval |