Pi Intercom

Direct 1:1 messaging between pi sessions on the same machine. Send context, findings, or requests from one session to another — whether you're driving the conversation or letting agents coordinate.

User flow: press Alt+M or run /intercom to pick a session and send a message

Why

Sometimes you're running multiple pi sessions — one researching, one executing, one reviewing. Pi-intercom lets you:

• User-driven orchestration — Send context or findings from your research session to your execution session
• Agent collaboration — An agent can reach out to another session when it needs help or wants to share results
• Session awareness — See what other pi sessions are running and their current status

Unlike pi-messenger (a shared chat room for multi-agent swarms), pi-intercom is for targeted 1:1 communication where you pick the recipient.

Pi-intercom also integrates well with pi-subagents: delegated child agents get a child-only contact_supervisor tool when pi-subagents supplies bridge metadata. Use reason: "need_decision" for blocking clarification, reason: "interview_request" for multiple structured supervisor answers, and reason: "progress_update" for meaningful plan-changing updates. Normal sessions only see the regular intercom tool.

In One Minute

Each pi session that has pi-intercom loaded and enabled connects to a tiny local broker over a local IPC transport. The broker keeps track of connected sessions and routes direct messages to the one you target by name or session ID. The extension gives you both a tool (intercom) and a small overlay UI (/intercom or Alt+M). Incoming messages are rendered inline inside the recipient session, can trigger a turn immediately, and are also stored in Pi session history as extension entries.

Install

pi install npm:pi-intercom

Then restart Pi. The extension auto-connects to the broker on startup and registers the bundled pi-intercom skill for common coordination patterns.

Recommended: Add this snippet to your project's AGENTS.md to help agents understand when to coordinate across sessions:

<pi-intercom>
Coordinate with other local pi sessions on related codebases. Use `/skill:pi-intercom` for patterns.

**When:** Same codebase (parallel work), reference codebase (consulting patterns), related repos (shared libraries).

**Not when:** Unrelated codebases, trivial questions, or when you can proceed independently.

**Principle:** Prefer `send` for notifications; `ask` only when blocked waiting for input.
</pi-intercom>

A session becomes intercom-connected when all of these are true:

• the pi-intercom extension is installed and loaded in that session
• enabled is not set to false in ~/.pi/agent/intercom/config.json
• the session has started or reloaded after the extension was installed
• the local broker is running or can be auto-started

The session list only shows intercom-connected sessions, not every open Pi process on the machine.

If a session is unnamed, pi-intercom now exposes a runtime-only fallback alias like subagent-chat-1a2b3c4d so other sessions can still target it. That alias is not persisted as the Pi session title, so pi --resume can keep showing the transcript snippet instead of a generic session-... name.

Quick Start

From the Keyboard

Press Alt+M or type /intercom to open the session list overlay:

1. Select a session — Use arrow keys to pick a target session
2. Compose message — Write your message in the compose overlay
3. Send — Press Enter to send, Escape to cancel

From the Agent

The agent can list sessions and send messages using the intercom tool. Tool calls and results render as compact transcript rows so send/ask/reply flows are easy to scan. For common patterns like planner-worker delegation, the bundled pi-intercom skill provides copy-paste ready examples:

// List active sessions
intercom({ action: "list" })
// → **Current session:**
// → • executor (20d43841) — ~/projects/api (claude-sonnet-4) [self, idle]
// → **Other sessions:**
// → • research (6332faab) — ~/projects/api (claude-sonnet-4) [same cwd, thinking]

// Send a message
intercom({ action: "send", to: "research", message: "Check if UserService.validate() handles null" })
// → Message sent to research

// Check connection status
intercom({ action: "status" })
// → Connected: Yes, Session ID: abc123, Active sessions: 3

// Send with attachments (code snippets, files, or context)
intercom({
  action: "send",
  to: "worker",
  message: "Here's the fix:",
  attachments: [{
    type: "snippet",
    name: "auth.ts",
    language: "typescript",
    content: "function validate(user: User) { ... }"
  }]
})

Receiving Messages

When a message arrives, it appears inline in your chat with the sender's info and a reply hint:

**From research** (~/projects/api)

To reply, use the intercom tool: intercom({ action: "reply", message: "..." })

Found the issue — UserService.validate() doesn't check for null input.
See auth.ts:142-156.

The reply hint (enabled by default) points to intercom({ action: "reply", ... }), so recipients do not need raw sender or replyTo IDs. Idle recipients get a new turn immediately; busy interactive recipients receive the message once they go idle. Attachment content is included in the agent-visible body, and messages are rendered inline and stored in Pi session history.

Workflow: Planner-Worker Coordination

The most natural use of pi-intercom is splitting a task between two sessions — one holds the big picture, the other does the hands-on work. When the worker hits an ambiguity ("should I optimize for readability or performance here?"), they ask without losing context.

Setup

Open two terminals and start pi in each. Name them so they can find each other:

# Terminal 1                    # Terminal 2
/name planner                   /name worker

Verify they see each other from either session:

intercom({ action: "list" })
// → • worker — ~/projects/api (claude-sonnet-4) [idle]

The Conversation

Here's how a typical exchange looks. The planner delegates with send (fire-and-forget). The worker uses ask for anything that needs a response — questions, discoveries, completion reports. ask sends the message and blocks until the planner replies, so the worker gets the answer as a tool result and continues in the same turn.

Planner sends a task:

intercom({
  action: "send",
  to: "worker",
  message: "Task-3: Add retry logic to API client. Key files: src/api/client.ts, src/api/types.ts. Ask if anything's unclear."
})

Worker hits an ambiguity — asks and waits:

intercom({
  action: "ask",
  to: "planner",
  message: "Should retry apply to all endpoints or just idempotent ones? Also, max retry count and backoff strategy?"
})
// → Reply from planner: Only GET/PUT/DELETE — never POST. Max 3 retries, exponential backoff starting at 100ms.
// Worker continues implementing with the answer, same turn, full context.

Worker finds something unexpected — escalates and waits:

intercom({
  action: "ask",
  to: "planner",
  message: "Found: fetchWithTimeout swallows network errors. Fixing this changes the error shape. OK to proceed?"
})
// → Reply from planner: Yes, surface the error types. The current behavior is a bug.

Worker reports completion:

intercom({
  action: "ask",
  to: "planner",
  message: "Task-3 done. Added RetryPolicy type, applied to GET/PUT/DELETE, surfaced NetworkError, 4 tests passing."
})
// → Reply from planner: Looks good. Move on to task-4.

Communication Patterns

Pattern	Action	Why
Task Delegation	Planner uses send	Fire-and-forget. Planner doesn't need to wait for an ack.
Clarification Request	Worker uses ask	Worker needs the answer to proceed. Blocks until reply.
Discovery Escalation	Worker uses ask	Worker needs approval before changing course.
Completion Report	Worker uses ask	Planner might have follow-up instructions or the next task.

Reply Hints

When replyHint is enabled (the default), incoming messages include the exact intercom() call to respond:

**From planner** (~/projects/api)

To reply, use the intercom tool: intercom({ action: "reply", message: "..." })

Only GET/PUT/DELETE — never POST. Max 3 retries with exponential backoff starting at 100ms.

This matters because the agent receiving the message doesn't need to reconstruct raw to and replyTo IDs — the hint is right there. Combined with idle-gated triggerTurn delivery, it enables real back-and-forth conversation without interrupting work in progress. If the reply happens later instead of in the triggered turn, intercom({ action: "reply" }) falls back to the single unresolved inbound ask, and intercom({ action: "pending" }) shows who is still waiting.

send vs ask

send is fire-and-forget — the tool returns immediately after delivery. By default, it sends immediately even in interactive sessions. If you want an approval dialog before non-reply sends, set confirmSend: true in config. Replies that include replyTo still skip confirmation so reply-hint flows can continue without an extra approval step.

ask sends the message and blocks until the recipient responds (10-minute timeout). The reply comes back as the tool result, so the agent continues in the same turn with full context. No confirmation dialog — if you're asking and waiting, the intent is clear.

reply is receiver-side sugar for replying to an inbound ask. In the turn triggered by an incoming intercom ask, intercom({ action: "reply", message: "..." }) targets that exact sender and message automatically. If you reply later, it falls back to the single unresolved inbound ask. If multiple asks are pending, use intercom({ action: "pending" }) to inspect them and then call reply with to to disambiguate.

The planner typically uses send. If you prefer manual approval for outgoing non-reply messages, turn on confirmSend: true. The worker uses ask for everything (no confirmation needed, gets answers inline), so it can operate autonomously either way.

Workflow: Subagent-to-Supervisor Escalation

This workflow requires pi-subagents to be installed and to supply child bridge metadata. When pi-subagents spawns a delegated child with that metadata, the child session gets a subagent-only contact_supervisor tool in addition to the regular intercom tool. Normal sessions never see contact_supervisor.

When the Tool Appears

contact_supervisor only registers when pi-subagents sets all of these environment variables:

• PI_SUBAGENT_ORCHESTRATOR_TARGET — the supervisor session name or ID
• PI_SUBAGENT_RUN_ID — the run identifier
• PI_SUBAGENT_CHILD_AGENT — the agent type
• PI_SUBAGENT_CHILD_INDEX — the child index within the run

If any are missing, the session falls back to the regular intercom tool.

Three Reasons

Reason	Behavior	Use When
need_decision	Sends an ask and blocks until the supervisor replies (10-minute timeout)	The subagent is blocked, uncertain, needs approval, or faces a product/API/scope decision
interview_request	Sends structured questions and blocks until the supervisor replies	The subagent needs multiple machine-readable answers from the supervisor in one exchange
progress_update	Fire-and-forget update to the supervisor	Meaningful progress or unexpected discoveries that change the plan

Do not use contact_supervisor for routine completion handoffs. Return the final subagent result normally through pi-subagents.

Example: Blocked Subagent Asks for Guidance

contact_supervisor({
  reason: "need_decision",
  message: "The auth service returns 403 instead of 401 for expired tokens. Should I treat 403 as a re-auth trigger or a hard failure?"
})
// → Reply from supervisor: Treat 403 as re-auth trigger. Update the token refresh logic.

Example: Structured Supervisor Interview

contact_supervisor({
  reason: "interview_request",
  message: "Please answer these before I continue the migration.",
  interview: {
    title: "API migration choices",
    questions: [
      { id: "api", type: "single", question: "Which API should I target?", options: ["Stable API", "Experimental API"] },
      { id: "constraints", type: "text", question: "What constraints should I preserve?" }
    ]
  }
})
// → Reply from supervisor: { "responses": [{ "id": "api", "value": "Stable API" }, ...] }

Example: Progress Update

contact_supervisor({
  reason: "progress_update",
  message: "Discovered the bug is in the retry wrapper, not the API client. Fixing the wrapper will also close issue #42."
})
// → Progress update sent to supervisor planner

What the Supervisor Sees

The supervisor receives a formatted message with run metadata:

**From subagent-worker-78f659a3-1**

Subagent needs a supervisor decision.
Run: 78f659a3
Agent: worker
Child index: 0

Which API should I use?

Reply hints work the same as regular intercom ask/reply flows. The supervisor can reply with intercom({ action: "reply", message: "..." }) and the subagent receives the answer as the tool result.

For interview_request, the supervisor message includes the structured questions plus a fenced JSON answer example using this stable shape:

{
  "responses": [
    { "id": "api", "value": "Stable API" },
    { "id": "constraints", "value": "Keep the public error shape unchanged." }
  ]
}

The supervisor can reply with plain JSON or a fenced json block. If the reply matches the { "responses": [...] } shape and references valid question ids/options, the child tool result includes it in details.structuredReply while still showing the raw reply text.

Tool Reference

intercom

Parameter	Type	Description
action	string	"list", "send", "ask", "reply", "pending", or "status"
to	string	Target session name or ID (for send/ask, or to disambiguate reply)
message	string	Message text (for send/ask/reply)
attachments	array	Optional file, snippet, or context attachments
replyTo	string	Optional message ID for threading or replying to an ask

contact_supervisor

Only registered in sessions where pi-subagents supplied the required child bridge metadata. Contacts the supervisor session that delegated the current task.

Parameter	Type	Description
reason	string	"need_decision" (blocking), "interview_request" (blocking structured questions), or "progress_update" (fire-and-forget)
message	string	The decision request, optional interview note, or progress update
interview	object	Required for interview_request: { title?, description?, questions: [...] }

need_decision — Sends a formatted ask to the supervisor and blocks until it replies (10-minute timeout). The reply comes back as the tool result. Includes run metadata in the message so the supervisor knows which subagent is asking.

interview_request — Sends a formatted, agent-readable interview to the supervisor and blocks until it replies. Questions use a local pi-interview-like shape: { id, type, question, options?, context? } where type is single, multi, text, image, or info. info questions are context-only and do not need responses. The supervisor reply should be JSON with { "responses": [{ "id": "...", "value": ... }] }. Parsed JSON replies are returned in details.structuredReply.

progress_update — Sends a non-blocking update to the supervisor. Returns immediately after delivery. Use only for meaningful progress or unexpected discoveries that change the plan.

intercom actions

list — Returns the current session plus other active intercom-connected sessions with name, short ID, working directory, model, and live status. Status is derived automatically from Pi lifecycle events: idle, thinking, or tool:<name>.

send — Sends a message to the specified session. By default it sends immediately, including in interactive sessions. Set confirmSend: true in config if you want a confirmation dialog for non-reply sends. Replies that include replyTo skip confirmation. Returns delivery confirmation.

ask — Sends a message and waits for the recipient to reply (10-minute timeout). The reply is returned as the tool result. No confirmation dialog. Only one pending ask is allowed per session at a time. Use this when the agent needs the answer to continue working.

reply — Replies to the current intercom-triggered message if there is one. Otherwise it falls back to the single unresolved inbound ask. If multiple asks are pending, pass to or inspect them with pending first. Under the hood this is still a normal send with the exact replyTo value.

pending — Lists unresolved inbound asks with sender, message ID, elapsed time, and a short preview. Useful when replying after the original triggered turn.

status — Shows connection status, session ID, and total count of active sessions (including the current session).

Keyboard Shortcuts

Key	Action
Alt+M	Open session list overlay
↑/↓	Navigate session list
Enter	Select session / Send message
Escape	Cancel / Close overlay

Config

Create ~/.pi/agent/intercom/config.json:

{
  "brokerCommand": "npx",
  "brokerArgs": ["--no-install", "tsx"],
  "confirmSend": false,
  "enabled": true,
  "replyHint": true,
  "status": "researching"
}

Setting	Default	Description
brokerCommand	"npx"	Command used to start the local broker process
brokerArgs	["--no-install", "tsx"]	Arguments passed to brokerCommand before the broker script path
confirmSend	false	Show a confirmation dialog before non-reply sends from an interactive session with UI
enabled	true	Enable/disable intercom entirely
replyHint	true	Include reply instruction in incoming messages
status	—	Optional custom status suffix shown after the automatic lifecycle status, for example thinking · researching

For example, if you have Bun installed and want it to start the broker directly, use:

{
  "brokerCommand": "bun",
  "brokerArgs": []
}

Pi-intercom publishes live session status automatically. Sessions register as idle, switch to thinking while the agent is running, show tool:<name> during tool execution, and return to idle on agent completion. If status is set in config, it is appended as context instead of replacing the lifecycle status.

How It Works

graph TB
    subgraph A["Pi Session A"]
        A1[Intercom Client]
        A2[intercom tool]
        A3[UI overlays]
    end

    subgraph Broker["Intercom Broker"]
        B1[Session Registry]
        B2[Message Router]
    end

    subgraph B["Pi Session B"]
        B3[Intercom Client]
        B4[intercom tool]
        B5[UI overlays]
    end

    A1 <-->|Local Socket/Pipe| B1
    B1 --- B2
    B2 <-->|Local Socket/Pipe| B3

The broker is a standalone TypeScript process that manages session registration and message routing. It auto-spawns when the first intercom-enabled session needs it and exits after 5 seconds when the last connected session disconnects. Clients now reconnect automatically if the broker disappears and later comes back.

Messages use length-prefixed JSON over a local socket/pipe transport (4-byte length + JSON payload) to handle fragmentation properly. The protocol includes request correlation for session listing, explicit delivery failures, and validation for malformed or out-of-order messages.

Async extension work (startup, inbound flushes, reconnects, overlays, and relays) no-ops if the session shuts down or reloads before it settles.

Runtime files live at ~/.pi/agent/intercom/:

• broker.sock — Unix domain socket for communication (macOS/Linux only; Windows uses a named pipe instead)
• broker-launch.vbs — Windows helper script used to launch the broker without a console window
• broker.pid — Broker process ID
• config.json — User configuration

Design Decisions

Local IPC instead of TCP. Same-machine only by design. pi-intercom uses Unix sockets on macOS/Linux and a named pipe on Windows, which keeps setup simple and avoids port management.

Auto-spawn with file lock. The broker starts on first connection and exits after 5 seconds idle. There is no daemon to manage. A spawn lock file, keyed by PID and timestamp, prevents duplicate brokers when multiple sessions start at once.

ask stays client-side. The broker still routes plain messages; it does not have a special request/response mode for ask. The client waits for a matching reply before it triggers a new turn, then returns that reply as the tool result. Reply hints make that flow practical by showing the recipient the exact send call to use. Separately, list / sessions now carry a requestId so a delayed session-list reply cannot be mistaken for a newer one.

pi-intercom vs pi-messenger

Aspect	pi-intercom	pi-messenger
Model	Direct 1:1 messaging	Shared chat room
Primary use	User orchestrating sessions	Autonomous agent coordination
Discovery	Broker-based (real-time)	File-based registry
Messages	Private, session-to-session	Broadcast to all agents
Persistence	In Pi session history	Shared coordination files

Use pi-messenger for multi-agent swarms working on a shared task. Use pi-intercom when you want to manually coordinate your own sessions or have one agent reach out to another specific session.

File Structure

~/.pi/agent/extensions/pi-intercom/
├── package.json
├── index.ts              # Extension entry point
├── types.ts              # SessionInfo, Message, protocol types
├── config.ts             # Config loading
├── broker/
│   ├── broker.ts         # Broker process
│   ├── client.ts         # IntercomClient class
│   ├── framing.ts        # Length-prefixed JSON protocol
│   ├── paths.ts          # Platform-specific socket/pipe paths
│   ├── spawn.ts          # Auto-spawn logic with lock file
│   ├── spawn.test.ts     # Broker spawn tests
│   └── paths.test.ts     # Path resolution tests
├── ui/
│   ├── session-list.ts   # Session selection overlay
│   ├── compose.ts        # Message composition overlay
│   └── inline-message.ts # Received message display
└── skills/
    └── pi-intercom/
        └── SKILL.md      # Bundled skill for common patterns

Limitations

• Same machine only — Uses local sockets/pipes, no network support
• No dedicated intercom log — Messages are kept in Pi session history, but there is no separate intercom transcript or inbox
• No attachments UI — file, snippet, and context attachments are supported in the protocol, but not in the compose overlay
• Only connected sessions appear — The list shows Pi sessions that have loaded pi-intercom and successfully registered with the broker, not every open Pi process on the machine
• Broker lifecycle — The broker auto-spawns on first use and exits when idle; sessions reconnect automatically if the broker restarts