@yzlin/pi-subagents

A pi extension that brings Claude Code-style autonomous sub-agents to pi. Spawn specialized agents that run in isolated sessions — each with its own tools, system prompt, model, and thinking level. Run them in foreground or background, steer them mid-run, resume completed sessions, and define your own custom agent types.

Status: Early release. Credit: Forked from the original @tintinweb/pi-subagents work by tintinweb.

https://github.com/user-attachments/assets/8685261b-9338-4fea-8dfe-1c590d5df543

Features

• Claude Code look & feel — same tool names, calling conventions, and UI patterns (Agent, get_subagent_result, steer_subagent, reply_to_subagent) — feels native
• Parallel background agents — spawn multiple agents that run concurrently with automatic queuing (configurable concurrency limit, default 4) and smart group join for widget state
• Live widget UI — persistent above-editor widget with animated spinners, live tool activity, token counts, and colored status icons
• Conversation viewer — select any agent in /agents to open a live-scrolling overlay of its full conversation (auto-follows new content, scroll up to pause)
• Custom agent types — define agents in .pi/agents/<name>.md with YAML frontmatter: custom system prompts, model selection, thinking levels, tool restrictions
• Mid-run steering — inject messages into running agents to redirect their work without restarting
• Parent↔subagent bridge — subagents can queue one-way updates with message_parent, and background subagents can ask blocking questions with ask_parent; the parent replies with reply_to_subagent
• Session resume — pick up where an agent left off, preserving full conversation context
• Graceful turn limits — agents get a "wrap up" warning before hard abort, producing clean partial results instead of cut-off output
• Case-insensitive agent types — user-defined names are resolved case-insensitively ("auditor", "Auditor", "AUDITOR" all work). Unknown types are rejected with setup guidance
• Fuzzy model selection — specify models by name ("haiku", "sonnet") instead of full IDs, with automatic filtering to only available/configured models
• Context inheritance — optionally fork the parent conversation into a sub-agent so it knows what's been discussed
• Persistent agent memory — three scopes (project, local, user) with automatic read-only fallback for agents without write tools
• Git worktree isolation — run agents in isolated repo copies; changes auto-committed to branches on completion
• Skill preloading — inject named skill files from .pi/skills/ into agent system prompts
• Tool denylist — block specific tools via disallowed_tools frontmatter
• Widget-only terminal state — background agent completion/failure/stopped states update the live widget, lifecycle events, persisted records, and output files without inserting chat messages or waking the model
• Event bus — lifecycle events (subagents:created, started, completed, failed, steered) emitted via pi.events, enabling other extensions to react to sub-agent activity
• Cross-extension RPC — other pi extensions can spawn and stop subagents via the pi.events event bus (subagents:rpc:ping, subagents:rpc:spawn, subagents:rpc:stop). Standardized reply envelopes with protocol versioning. Emits subagents:ready on load

Install

pi install npm:@yzlin/pi-subagents

Or load directly for development:

pi -e ./src/index.ts

Shared Pi runtime

The Pi extension entry loads from TypeScript so Pi resolves @earendil-works/pi-* and typebox imports through the host's shared-module aliases. Custom-provider subagent sessions therefore use the same runtime singletons as the parent Pi session, including for local-path installs with development dependencies present. Public package exports remain compiled JavaScript for native Node consumers.

Keep Pi runtime packages as "*" peer dependencies. Local node_modules copies remain build/test dependencies only; no deletion or symlink setup is required.

Quick Start

First define at least one agent, for example .pi/agents/auditor.md as shown below.

The parent agent then spawns sub-agents using the Agent tool:

Agent({
  subagent_type: "auditor",
  prompt: "Review the authentication module for security issues",
  description: "Review auth security",
  run_in_background: true,
})

Foreground agents block until complete and return results inline. Background agents return an ID immediately; completion/failure/stopped states update the live widget and remain available through get_subagent_result without waking the model.

Subagents launched by this extension also get native bridge tools:

• message_parent — queue a one-way update for the parent
• ask_parent — queue a question and wait for reply_to_subagent (background agents only)

These bridge messages are queue-first: the subagent tool call returns after enqueueing (or waits on the reply for ask_parent), and the parent receives the queued update at the next safe turn boundary. Delivery is scoped to the parent session that spawned the subagent. Notifications contain only metadata and request_ids; the parent must explicitly fetch the raw payload with get_subagent_message. Queued questions also wake a parent turn so the parent can fetch the payload and explicitly answer with reply_to_subagent.

UI

The extension renders a persistent widget above the editor showing all active agents:

● Agents
├─ ⠹ reviewer  Refactor auth module · ⟳5≤30 · 5 tool uses · 33.8k token · 12.3s
│    ⎿  editing 2 files…
├─ ⠹ auditor  Review auth security · ⟳3 · 3 tool uses · 12.4k token · 4.1s
│    ⎿  searching…
└─ 2 queued

Individual agent results render Claude Code-style in the conversation:

State	Example
Running	⠹ ⟳3≤30 · 3 tool uses · 12.4k token / ⎿ searching, reading 3 files…
Completed	✓ ⟳8 · 5 tool uses · 33.8k token · 12.3s / ⎿ Done
Wrapped up	✓ ⟳50≤50 · 50 tool uses · 89.1k token · 45.2s / ⎿ Wrapped up (turn limit)
Stopped	■ ⟳3 · 3 tool uses · 12.4k token / ⎿ Stopped
Error	✗ ⟳3 · 3 tool uses · 12.4k token / ⎿ Error: timeout
Aborted	✗ ⟳55≤50 · 55 tool uses · 102.3k token / ⎿ Aborted (max turns exceeded)

Completed foreground results can be expanded (ctrl+o in pi) to show the full agent output inline.

Background terminal states are widget/state only: completed, failed, and stopped agents update the live widget, emit lifecycle events, persist records/output files, and remain available through get_subagent_result without inserting a chat message or triggering a model turn.

Agent Types

This extension ships no built-in agent types. You must define the agents you want to use.

Define agent types by creating .md files. The filename becomes the agent type name. Any name is allowed.

Agents are discovered from two locations (higher priority wins):

Priority	Location	Scope
1 (highest)	.pi/agents/<name>.md	Project — per-repo agents
2	~/.pi/agent/agents/<name>.md	Global — available everywhere

Project-level agents override global ones with the same name, so you can customize a global agent for a specific project.

Example: .pi/agents/auditor.md

---
description: Security Code Reviewer
tools: read, grep, find, bash
model: anthropic/claude-opus-4-6
thinking: high
max_turns: 30
---

You are a security auditor. Review code for vulnerabilities including:
- Injection flaws (SQL, command, XSS)
- Authentication and authorization issues
- Sensitive data exposure
- Insecure configurations

Report findings with file paths, line numbers, severity, and remediation advice.

Then spawn it with the Agent tool:

Agent({ subagent_type: "auditor", prompt: "Review the auth module", description: "Security audit" })

Frontmatter Fields

All fields are optional — sensible defaults for everything.

Field	Default	Description
description	filename	Agent description shown in tool listings
display_name	—	Display name for UI (e.g. widget, agent list)
tools	all 7	Comma-separated built-in tools: read, bash, edit, write, grep, find, ls. none for no tools
extensions	true	Inherit MCP/extension tools. false to disable
skills	true	Inherit skills from parent. Can be a comma-separated list of skill names to preload from .pi/skills/
memory	—	Persistent agent memory scope: project, local, or user. Auto-detects read-only agents
disallowed_tools	—	Comma-separated tools to deny even if extensions provide them
isolation	—	Set to worktree to run in an isolated git worktree
model	inherit parent	Model — provider/modelId or fuzzy name ("haiku", "sonnet")
thinking	inherit	off, minimal, low, medium, high, xhigh
max_turns	unlimited	Max agentic turns before graceful shutdown. 0 or omit for unlimited. Unsupported when runnerBackend is "herdr"; explicit max_turns fails fast there
prompt_mode	replace	replace: body is the full system prompt (no AGENTS.md / CLAUDE.md inheritance). append: body appended to parent's prompt (agent acts as a "parent twin" — inherits parent's AGENTS.md / CLAUDE.md)
context	fresh	Agent conversation context: fresh or fork. This replaces the removed inherit_context option
run_in_background	false	Run in background by default
isolation	—	worktree: run in a temporary git worktree for full repo isolation
isolated	false	No extension/MCP tools, only built-in
caveman	—	Boolean only. Applies/removes caveman prompt text before child session creation
enabled	true	Set to false to disable an agent without deleting its file

Frontmatter is authoritative. If an agent file sets model, thinking, max_turns, context, run_in_background, isolated, isolation, or caveman, those values are locked for that agent. Agent tool parameters only fill fields the agent config leaves unspecified.

Caveman frontmatter

caveman accepts booleans only:

---
caveman: true
---

Behavior:

• With the default in-process runner, caveman: true asks the separate caveman extension to append its canonical caveman prompt before the child session starts.
• With the default in-process runner, caveman: false asks caveman to strip inherited caveman prompt text.
• The in-process runner requires the caveman extension event-bus RPC v1 (caveman:rpc:capabilities and caveman:rpc:apply).
• If RPC is unavailable, times out, or apply fails, the agent still starts with the unmodified prompt. Foreground runs can show a UI warning; background runs keep warnings in result details.
• With runnerBackend: "herdr", caveman frontmatter is applied parent-side to the system prompt before the child Pi starts. Herdr child launches omit --caveman / --no-caveman for CLI compatibility.
• Non-boolean caveman values are treated as omitted and warn during agent startup.

Agent runs are tagged for UI/status rendering: caveman:on, caveman:off, or caveman:unavailable.

Tools

Agent

Launch a sub-agent.

Parameter	Type	Required	Description
prompt	string	yes	The task for the agent
description	string	yes	Short 3-5 word summary (shown in UI)
subagent_type	string	yes	User-defined agent type
model	string	no	Model — provider/modelId or fuzzy name ("haiku", "sonnet")
thinking	string	no	Thinking level: off, minimal, low, medium, high, xhigh
max_turns	number	no	Max agentic turns. Omit for unlimited (default). Unsupported with runnerBackend: "herdr"
run_in_background	boolean	no	Run without blocking
resume	string	no	Agent ID to resume a previous session
isolated	boolean	no	No extension/MCP tools
isolation	"worktree"	no	Run in an isolated git worktree
context	"fresh" | "fork"	no	Agent conversation context. fresh starts without parent chat history; fork copies it. Use this instead of removed inherit_context

workflow

Run a blocking JavaScript workflow script that coordinates subagents and returns one structured envelope. The tool is installed with this extension; there is no extra setup, workflow registry, or /workflows manager in v1.

Workflow scripts must begin with a literal metadata export before any other code:

export const meta = {
  name: "review-and-fix",
  description: "Review a change and summarize the result",
};

phase("review");
log("starting review", { target: args.target });
const result = await agent(`Review ${args.target}`, { agent: "reviewer" });
return { result };

Runtime globals:

Global	Description
phase(name, fn?)	Record and optionally run a named phase
log(message, data?)	Add a progress log entry
agent(prompt, opts?)	Run a child subagent and wait for its result
parallel(steps)	Run an array of functions/thunks concurrently; promises and other non-functions are rejected
pipeline(items, ...stages)	Run each item through sequential stages while items fan out concurrently; each stage receives (previous, original, index)
args	JSON-like inputs passed to the tool call
cwd / process.cwd()	Current working directory
budget	Agent/log budget counters and remaining agent calls

agent(prompt) defaults to the general-purpose agent type. Override it with options:

const review = await agent("Review this diff", { agent: "reviewer" });

Use opts.schema for structured child-agent output. When a schema is supplied, agent() returns the structured value directly:

const opts = {
  schema: {
    type: "object",
    properties: { headline: { type: "string" } },
    required: ["headline"],
  },
};

const review = await agent("Return a headline", {
  agent: "reviewer",
  schema: opts.schema,
});
return review;

Workflow child agents use the existing subagent runtime and concurrency queue. They show up in the normal agents widget and can be steered while running. Pressing Esc/cancel on the workflow aborts workflow-owned queued and running child agents.

v1 workflows are blocking-only: the tool call stays active until the script completes, fails, or is cancelled. There is no workflow persistence, resume, background workflow mode, or workflow manager UI.

Programmatic workflow progress

@yzlin/pi-subagents/pi exports workflow progress helpers for Pi extensions that run workflows directly instead of through the workflow tool. Use createWorkflowProgressTracker() to merge runtime WorkflowProgressEvent updates from runWorkflowScript(...) with child-agent updates from a WorkflowAgentRunner. The tracker returns a WorkflowProgressEnvelope containing meta, phases, recent logs, agents, currentPhase, currentTask, duration, status, result, and optional error fields.

Typical integration:

1. Create one tracker before the workflow starts.
2. Call tracker.updateFromProgressEvent(event) from runWorkflowScript's onProgress callback.
3. Call tracker.updateChildAgent(child) whenever a child agent is queued, starts, completes, or fails.
4. Render formatWorkflowProgress(tracker.getEnvelope()) for live progress, or pass envelopes to createWorkflowProgressUi(ctx, { onUpdate }) to reuse the built-in widget/status/partial-update controller.
5. On success, call tracker.complete(result); on failure, call tracker.error(error).

workflowProgressResult(envelope, summary) produces the same JSON-safe tool-result shape used by the built-in workflow tool. Non-JSON-safe values in result are replaced with { unsupported: true, type, value? } markers so callers can safely serialize progress details.

createWorkflowProgressUi(...) defaults to the built-in workflow-progress widget key and workflow status key. Pass widgetKey and statusKey when embedding the canonical workflow progress UI in another extension-owned surface. When the host supports callback widgets, the controller renders a themed widget with pi semantic colors, a star spinner, and independently scoped workflow, phase, and agent-call elapsed durations refreshed every 100 ms; completed phase and agent-call durations remain frozen. If callback widgets are unavailable, it falls back to the plain string-array widget output. The controller deduplicates partial updates, clears terminal completed / stopped / error widget and status output, and can also be cleared explicitly with controller.clear().

Runner backend

By default, subagents run in-process. To launch agents through Herdr panes instead, set runnerBackend in .pi/subagents/config.json (project) or ~/.pi/agent/subagents/config.json (user):

{
  "runnerBackend": "herdr"
}

runnerBackend: "herdr" requires the herdr command plus pi-intercom (installed in the target project or Pi package directory) or pi with intercom support, and the parent Pi session must be running inside a Herdr pane with HERDR_PANE_ID set. If pi-intercom is missing, background launches fall back to the in-process runner and record a warning instead of failing. It opens a human-readable interactive Pi pane next to the parent pane for tracing while subagent results continue to be captured through the hidden output file used by get_subagent_result. It supports selected agent types, including agent prompt/tool/skill/extension/model/thinking settings, and preserves the same context behavior:

• context: "fresh" starts a new persisted child session without parent chat history.
• context: "fork" forks from the parent session.
• inherit_context has been removed; use context explicitly.

Herdr child launches mirror the parent project trust decision with --approve or --no-approve so the child pane does not block on startup trust prompts. After the child reaches its first final result, subagents capture that hidden output/result as the tracked result and stop reading additional child output. The Herdr pane remains open and interactive for manual follow-up work, but anything typed or produced there after the first final is untracked; the child prints a warning before handing control back. If a Herdr launch fails after the pane has been split, the failed pane remains visible for diagnosis.

Current Herdr limitations:

• Explicit max_turns / maxTurns is unsupported and fails fast because Pi CLI has no max-turns support and child-side enforcement is not implemented.
• Selected-agent extensions / skills limits are not enforced by Herdr launches. Herdr lets child Pi load its normal extensions and skills so extension-provided prompts/rules remain available; this can expose broader tools than the in-process backend.
• caveman frontmatter is applied by the parent before Herdr child launch; Herdr never passes child-native --caveman / --no-caveman flags.
• Automated tests cover Herdr command construction and parity contracts with mocked Herdr/Pi commands. Real Herdr end-to-end coverage is intentionally out of scope for this package's normal validation.

get_subagent_result

Check status and retrieve results from a background agent.

Parameter	Type	Required	Description
agent_id	string	yes	Agent ID to check
wait	boolean	no	Wait for completion
verbose	boolean	no	Include full conversation log

steer_subagent

Send a steering message to a running agent. The message interrupts after the current tool execution.

Parameter	Type	Required	Description
agent_id	string	yes	Agent ID to steer
message	string	yes	Message to inject into agent conversation

get_subagent_message

Fetch the raw payload for a queued parent-bridge notification.

Parameter	Type	Required	Description
request_id	string	yes	Request ID from the queued parent-bridge notification

reply_to_subagent

Reply to a queued ask_parent request from a running subagent.

Parameter	Type	Required	Description
request_id	string	yes	Request ID from the queued parent-bridge notification
message	string	yes	Reply text sent back to the waiting subagent

Sub-agent bridge tools

These tools are injected automatically into subagents spawned by this extension. They are not top-level user tools; the parent sees their queued output and answers with reply_to_subagent when needed. Queued bridge traffic is scoped to the parent session that launched the subagent.

message_parent

Queue a one-way update for the parent agent. The tool returns a requestId immediately after enqueueing.

Parameter	Type	Required	Description
message	string	yes	Update to send to the parent

ask_parent

Queue a question for the parent agent and wait for a reply. This tool is only injected into background subagents to avoid deadlocking foreground runs.

Parameter	Type	Required	Description
message	string	yes	Question or request for the parent
timeout_ms	number	no	Optional timeout while waiting for reply_to_subagent

Queue-first semantics: both bridge tools enqueue their message first. Parent updates are flushed in creation order at the next safe turn boundary and only into the originating parent session. Notifications contain metadata plus request_ids instead of raw subagent text. One-way updates do not auto-trigger the parent; use get_subagent_message to inspect them. Queued ask_parent questions wake a parent turn so the parent can explicitly fetch the payload and answer with reply_to_subagent. Timed-out asks are removed from the queue.

Commands

Command	Description
/agents	Interactive agent management menu

The /agents command opens an interactive menu:

Running agents (2) — 1 running, 1 done     ← only shown when agents exist
Agent types (6)                             ← user-defined project/global agents
Create new agent                            ← manual wizard or generated by an existing agent
Settings                                    ← max concurrency, max turns, grace turns, join mode

• Agent types — user-defined list with source indicators: • (project), ◦ (global), ✕ (disabled). Select an agent to manage it:
  • Enabled agents: Edit, Disable, Delete
  • Disabled agents: Enable, Edit, Delete
• Disable/Enable — toggle agent availability. Disabled agents stay visible in the list (marked ✕) and can be re-enabled
• Create new agent — choose project/personal location, then manual wizard (step-by-step prompts for name, tools, model, thinking, system prompt). If at least one agent already exists, you can also generate a new .md definition with an existing agent.
• Settings — configure max concurrency, default max turns, grace turns, and join mode at runtime

Graceful Max Turns

Graceful max turns apply to the default in-process runner. Explicit max_turns is not supported by runnerBackend: "herdr".

Instead of hard-aborting at the turn limit, agents get a graceful shutdown:

1. At max_turns — steering message: "Wrap up immediately — provide your final answer now."
2. Up to 5 grace turns to finish cleanly
3. Hard abort only after the grace period

Status	Meaning	Icon
completed	Finished naturally	✓ green
steered	Hit limit, wrapped up in time	✓ yellow
aborted	Grace period exceeded	✗ red
stopped	User-initiated abort	■ dim

Concurrency

Background agents are subject to a configurable concurrency limit (default: 4). Excess agents are automatically queued and start as running agents complete. The widget shows queued agents as a collapsed count.

Foreground agents bypass the queue — they block the parent anyway.

Join Strategies

When background agents complete, terminal state is reflected in the live widget and lifecycle events without waking the main agent. The join mode controls how completions are batched for widget/state updates. It applies only to background agents.

Mode	Behavior
smart (default)	2+ background agents spawned in the same turn are auto-grouped for consolidated widget/state updates. Solo agents update individually.
async	Each agent updates widget/state immediately on completion.
group	Force grouping even when spawning a single agent. Useful when you know more agents will follow.

Timeout behavior: When agents are grouped, a 30-second timeout starts after the first agent completes. If not all agents finish in time, completed results update widget/state and remaining agents continue with a shorter 15-second re-batch window for stragglers.

Configuration:

• Configure join mode in /agents → Settings → Join mode

Events

Agent lifecycle events are emitted via pi.events.emit() so other extensions can react:

Event	When	Key fields
subagents:created	Background agent registered	id, type, description, isBackground
subagents:started	Agent transitions to running (including queued→running)	id, type, description
subagents:completed	Agent finished successfully	id, type, durationMs, tokens, toolUses, result
subagents:failed	Agent errored, stopped, or aborted	same as completed + error, status
subagents:steered	Steering message sent	id, message
subagents:ready	Extension loaded and RPC handlers registered	—

Cross-Extension RPC

Other pi extensions can spawn and stop subagents programmatically via the pi.events event bus, without importing this package directly.

All RPC replies use a standardized envelope: { success: true, data?: T } on success, { success: false, error: string } on failure.

Discovery

Listen for subagents:ready to know when RPC handlers are available:

pi.events.on("subagents:ready", () => {
  // RPC handlers are registered — safe to call ping/spawn/stop
});

Ping

Check if the subagents extension is loaded and get the protocol version:

const requestId = crypto.randomUUID();
const unsub = pi.events.on(`subagents:rpc:ping:reply:${requestId}`, (reply) => {
  unsub();
  if (reply.success) console.log("Protocol version:", reply.data.version);
});
pi.events.emit("subagents:rpc:ping", { requestId });

Spawn

Spawn a subagent and receive its ID:

const requestId = crypto.randomUUID();
const unsub = pi.events.on(`subagents:rpc:spawn:reply:${requestId}`, (reply) => {
  unsub();
  if (!reply.success) {
    console.error("Spawn failed:", reply.error);
  } else {
    console.log("Agent ID:", reply.data.id);
  }
});
pi.events.emit("subagents:rpc:spawn", {
  requestId,
  type: "auditor",
  prompt: "Review authentication code",
  options: { description: "My task", run_in_background: true },
});

Stop

Stop a running agent by ID:

const requestId = crypto.randomUUID();
const unsub = pi.events.on(`subagents:rpc:stop:reply:${requestId}`, (reply) => {
  unsub();
  if (!reply.success) console.error("Stop failed:", reply.error);
});
pi.events.emit("subagents:rpc:stop", { requestId, agentId: "agent-id-here" });

Reply channels are scoped per requestId, so concurrent requests don't interfere.

Persistent Agent Memory

Agents can have persistent memory across sessions. Set memory in frontmatter to enable:

---
memory: project   # project | local | user
---

Scope	Location	Use case
project	.pi/agent-memory/<name>/	Shared across the team (committed)
local	.pi/agent-memory-local/<name>/	Machine-specific (gitignored)
user	~/.pi/agent-memory/<name>/	Global personal memory

Memory uses a MEMORY.md index file and individual memory files with frontmatter. Agents with write tools get full read-write access. Read-only agents (no write/edit tools) automatically get read-only memory — they can consume memories written by other agents but cannot modify them. This prevents unintended tool escalation.

The disallowed_tools field is respected when determining write capability — an agent with tools: write + disallowed_tools: write correctly gets read-only memory.

Worktree Isolation

Set isolation: worktree to run an agent in a temporary git worktree:

Agent({ subagent_type: "refactor", prompt: "...", isolation: "worktree" })

The agent gets a full, isolated copy of the repository. On completion:

• No changes: worktree is cleaned up automatically
• Changes made: changes are committed to a new branch (pi-agent-<id>) and returned in the result

If the worktree cannot be created (not a git repo, no commits, or git worktree add fails), the Agent tool returns a clear error instead of running unisolated — isolation: "worktree" is a strict guarantee, not a hint. Initialize git and commit at least once, or omit isolation.

Skill Preloading

Skills can be preloaded as named files from .pi/skills/ or ~/.pi/skills/:

---
skills: api-conventions, error-handling
---

Skill files (.md, .txt, or extensionless) are read and injected into the agent's system prompt. Project-level skills take priority over global ones. Symlinked skill files are rejected for security.

Tool Denylist

Block specific tools from an agent even if extensions provide them:

---
tools: read, bash, grep, write
disallowed_tools: write, edit
---

This is useful for creating agents that inherit extension tools but should not have write access.

Architecture

src/
  index.ts            # Extension entry: tool/command registration, rendering
  types.ts            # Type definitions (AgentConfig, AgentRecord, etc.)
  agent-types.ts      # User-defined agent registry, tool factories
  agent-runner.ts     # Session creation, execution, graceful max_turns, steer/resume
  agent-manager.ts    # Agent lifecycle, concurrency queue, terminal state updates
  cross-extension-rpc.ts # RPC handlers for cross-extension spawn/ping via pi.events
  group-join.ts       # Group join manager: batched terminal state updates with timeout
  parent-bridge.ts    # Native parent↔subagent message queue + ask/reply coordination
  custom-agents.ts    # Load user-defined agents from .pi/agents/*.md
  memory.ts           # Persistent agent memory (resolve, read, build prompt blocks)
  skill-loader.ts     # Preload skill files from .pi/skills/
  output-file.ts      # Streaming output file transcripts for agent sessions
  worktree.ts         # Git worktree isolation (create, cleanup, prune)
  prompts.ts          # Config-driven system prompt builder
  context.ts          # Parent conversation context for forked agent context
  env.ts              # Environment detection (git, platform)
  ui/
    agent-widget.ts       # Persistent widget: spinners, activity, status icons, theming
    conversation-viewer.ts # Live conversation overlay for viewing agent sessions

License

MIT.

Release process

Release automation assumes the default branch is main and runs on Node 24.

One-time setup

1. Bootstrap the current package version locally before the first automated release. The changelog bootstrap is a dry run by default and only writes CHANGELOG.md when -- --yes is passed:

   npm ci
   npm run build
   npm run release:bootstrap:0.6.0
   npm run release:bootstrap:0.6.0 -- --yes
   npm run release:gate
   npm publish --provenance --access public --tag latest
   git tag -a v0.6.0 -m v0.6.0
   git push origin v0.6.0
   gh release create v0.6.0 --title v0.6.0 --notes-file <(awk '/^## \[0.6.0\]/{flag=1; next} /^## \[/{flag=0} flag' CHANGELOG.md)
   

   This folds the current [Unreleased] notes into [0.6.0], publishes 0.6.0 once, creates and pushes the annotated v0.6.0 tag, and creates the matching GitHub Release from the folded changelog section.

2. Rename the default branch from master to main before using release workflows. After the remote rename, refresh the local clone:

   git branch -m master main
   git fetch origin
   git branch --set-upstream-to=origin/main main
   

3. If this fork tracks the original repository as upstream, fetch it without tags and remove any local upstream tags that should not belong to this package:

   git fetch --no-tags upstream
   git tag -l | xargs -n1 git tag -d
   git fetch --tags origin
   

4. In npm, configure this repository as a trusted publisher for @yzlin/pi-subagents. The publish workflow uses GitHub OIDC provenance (npm publish --provenance) and does not require an NPM_TOKEN.

5. In GitHub, create a protected environment named npm-publish. Require approval if you want a manual gate before release preparation commits, tags, pushes, and dispatches publishing.

Future releases

1. Run Prepare release (.github/workflows/release-prepare.yml) from main. Optional bump input accepts major, minor, or patch; otherwise the script infers the bump from CHANGELOG.md.
2. The workflow runs npm run release:gate, then npm run release:prepare -- --yes. That updates package.json, package-lock.json, and CHANGELOG.md, commits chore: release vX.Y.Z, creates vX.Y.Z, atomically pushes main and the tag, then dispatches npm-publish.yml.
3. Publish npm package runs only on refs/tags/v*. It runs npm run release:publish -- --yes, validates the tag matches package.json, publishes with OIDC provenance if the version is not already on npm, and creates or updates the GitHub Release from the changelog section.

Dry-run locally before trusting a release:

npm run release:prepare
npm run release:publish

Dry runs print mutating commands instead of running them. Only pass -- --yes when you intend to commit, tag, push, dispatch, publish, or edit a GitHub Release.

Fork attribution: original package by tintinweb.