pi-subagents

pi-subagents lets Pi delegate work to focused child agents. Use it for code review, scouting, implementation, parallel audits, saved workflows, background jobs, and anything else that benefits from a second or third set of model eyes.

https://github.com/user-attachments/assets/702554ec-faaf-4635-80aa-fb5d6e292fd1

Installation

pi install npm:pi-subagents

That is the only required step. You can add optional pieces later.

Try this first

You do not need to create agents, write config, or learn slash commands. After installing, ask Pi for delegation in plain language:

Use reviewer to review this diff.

Ask oracle for a second opinion on my current plan.

Use scout to understand this code based on our discussion then ask me clarification questions.

Run parallel reviewers: one for correctness, one for tests, and one for unnecessary complexity.

That is enough to start.

What happens

Pi is the parent session. A subagent is a focused child Pi session with its own job.

When you ask for a subagent, Pi starts the child, gives it the task, and brings the result back. Foreground runs stream in the conversation. Background runs keep working and can be checked later.

Installing the extension does not start an automatic reviewer in the background. It gives Pi a delegation tool. If you want every implementation reviewed, say that in your prompt or put it in your project instructions:

When you finish implementing, run a reviewer subagent before summarizing.

Good first prompts

These cover most day-to-day use:

Ask oracle for a second opinion on my current plan. Challenge assumptions and tell me what I might be missing.

Use oracle to help solve this hard bug. Have it inspect the code and propose the best next move before we edit anything.

Run parallel reviewers on this diff. I want one focused on correctness, one on tests, and one on unnecessary complexity.

Have worker implement this approved plan. Afterward, run parallel reviewers, summarize their feedback, and apply the fixes that make sense.

Run a review loop on this change until reviewers stop finding fixes worth doing, with a max of 3 rounds.

Use scout to understand the auth flow, then have planner turn that into an implementation plan.

Those are ordinary Pi requests. Pi decides whether to call subagent, which agent to use, and whether a chain or parallel run makes sense.

Common workflows

Want	Ask naturally
Get a second opinion	“Ask oracle to review this plan and challenge assumptions.”
Solve a hard problem	“Use oracle to investigate this bug before we edit.”
Review a diff	“Use reviewer to review this diff.”
Run parallel reviewers	“Run reviewers for correctness, tests, and cleanup.”
Implement then review	“Implement this, then review it.”
Review until clean	“Run a review loop on this change with a max of 3 rounds.”
Execute a plan carefully	“Have worker implement this approved plan, then run reviewers and apply the feedback.”
Scout before planning	“Use scout to inspect the auth flow before planning.”
Run in the background	“Run this in the background.”
Browse agents	“Show me the available subagents.”
Use a saved workflow	“Run the review chain on this branch.”
See running work	“Show active async runs.” or “Show the subagent fleet.”
Check setup	“Check whether subagents are configured correctly.”

The extension ships with builtin agents you can use immediately.

Builtin agents in plain English

Agent	Use it when you want...
scout	Fast local codebase recon: relevant files, entry points, data flow, risks, and where another agent should start.
researcher	Web/docs research with sources: official docs, specs, benchmarks, recent changes, and a concise research brief.
planner	A concrete implementation plan from existing context. It should read and plan, not edit code.
worker	Implementation work, including approved oracle handoffs. It edits files, validates, and escalates unapproved decisions instead of guessing.
reviewer	Code review and small fixes. It checks the implementation against the task/plan, tests, edge cases, and simplicity.
context-builder	A stronger setup pass before planning: gathers code context and writes handoff material such as context.md and meta-prompt.md.
oracle	A second opinion before acting. It challenges assumptions, catches drift, and recommends the safest next move without editing.
delegate	A lightweight general delegate when you want a child agent that behaves close to the parent session.

A simple rule of thumb: use scout before you understand the code, researcher before you trust external facts, planner before a bigger change, worker to implement, reviewer to check, and oracle when the decision itself feels risky.

Changing an agent's model

Builtin agents inherit your current Pi default model by default. This keeps new installs from depending on a provider you may not have configured. If you want every subagent without its own model to use a different default, set subagents.defaultModel. If you want a role to use a specific model, set an override instead of copying the bundled agent file.

{
  "defaultModel": "deepseek-v4-pro",
  "subagents": {
    "defaultModel": "deepseek-v4-flash",
    "agentOverrides": {
      "oracle": {
        "model": "deepseek-v4-pro"
      }
    }
  }
}

For one run, put the override in the command:

/run reviewer[model=anthropic/claude-sonnet-4:high] "Review this diff"

For a persistent override, edit settings. This example pins the reviewer everywhere, adds a backup model for provider failures, and keeps the other builtins on your normal default model:

{
  "subagents": {
    "agentOverrides": {
      "reviewer": {
        "model": "anthropic/claude-sonnet-4",
        "thinking": "high",
        "fallbackModels": ["openai/gpt-5-mini"]
      }
    }
  }
}

Use ~/.pi/agent/settings.json for a user override or the project config settings file (.pi/settings.json in standard Pi) for a project override. subagents.defaultModel applies to builtin, package, user, and project agents that do not set model in frontmatter. Per-run model overrides and agentOverrides.<name>.model still win, and explicit agent frontmatter still wins over the global default. The same agentOverrides block can change tools, skills, inherited context, prompt text, or disable a builtin. Matching user and project agents also receive override fields that their frontmatter leaves unset, so a shared project config agent can keep the persona while local settings choose the model.

If your provider rejects model IDs with thinking suffixes, set subagents.disableThinking: true in user or project settings. That clears bundled builtin thinking defaults in one place; an explicit higher-precedence agentOverrides.<name>.thinking value can opt a role back in.

To inspect what pi-subagents has actually loaded right now, use:

/subagents-models
/subagents-models reviewer

That reports the live runtime mapping, which can differ from settings on disk until you reload Pi.

You do not have to spell a model exactly. Model ids are matched fuzzily against the registry, so provider separator variations (anthropic/claude-sonnet-4, anthropic:claude-sonnet-4, or anthropic.claude-sonnet-4), id separator variations (claude-haiku-4.5 vs claude-haiku-4-5), case differences (Claude-Sonnet-4 vs claude-sonnet-4), and optional trailing date stamps (claude-haiku-4-5-20251001 or claude-haiku-4-5-2025-10-01 vs claude-haiku-4-5) all resolve to the same model. Exact provider/id matches still win, and a qualified provider query never silently switches providers — it only matches within the named provider. Ambiguous bare ids that exist under multiple providers still require a provider prefix or the current session's provider to disambiguate.

To keep subagents inside a budget or compliance profile, enforce a model scope. Put subagents.modelScope in user or project settings (project overrides user):

{
  "subagents": {
    "modelScope": {
      "enforce": true,
      "allow": ["anthropic/*", "openai/gpt-5-*"]
    }
  }
}

allow is a list of glob patterns matched against the resolved provider/id (only * is special, case-insensitive). A resolved model that matches none of the patterns is rejected. Models you pass explicitly — the tool-call model, --model, or a clarify pick — error and abort the run. Models that come from agent frontmatter, subagents.defaultModel, or the inherited parent session model only warn, so existing configurations keep working while you tighten the scope. enforce: true requires a non-empty allow list; otherwise the config is rejected at load time.

Where running subagents show up

Foreground runs stream progress in the conversation while they run.

Background runs keep working after control returns to you. Inspect active runs with subagent({ action: "status" }), or a specific run with subagent({ action: "status", id: "..." }). For a read-only fleet view across active foreground and background work, use /subagents-fleet or subagent({ action: "status", view: "fleet" }). To inspect what a background child is saying without hunting through artifact directories, tail its live transcript with subagent({ action: "status", id: "...", view: "transcript" }); add index for a specific child in a parallel or chain run.

They also show a compact async widget and send completion notifications. Parallel background runs show per-agent progress instead of fake chain steps. Chains with parallel groups keep their grouped shape in progress and results, so failed or paused agents stay visible next to completed ones. When a child is explicitly allowed to fan out with tools: subagent, its nested runs appear under that parent child in the main status tree instead of being hidden inside the child process.

You can also ask naturally:

Show me the current async runs.

Async runs also write machine-readable lifecycle artifacts for observability and workflow gates. For a top-level async run, details.asyncDir points at a directory containing status.json, events.jsonl, output-<index>.log, and subagent-log-<runId>.md; the final summary is written to Pi's subagent results directory as <runId>.json. Nested async runs use the same shape under the nested async root and are discoverable through status projections that read the nested-run registry. These files are append/update artifacts only; interactive foreground behavior is unchanged.

The stable v1 status/result fields are lifecycleArtifactVersion, runId/id, sessionId, mode, state, startedAt, lastUpdate, endedAt, durationMs, cwd, asyncDir, sessionFile, outputFile, workflowGraph, steps, results, totalTokens, totalCost, model/attemptedModels/modelAttempts, toolCount, turnCount, and nested children when a child is allowed to launch subagents. events.jsonl records lifecycle transitions such as subagent.run.started, subagent.step.started, subagent.step.completed/failed/paused, control attention events, nested interrupt failures, and subagent.run.completed; run boundary events include the lifecycle artifact version. Consumers should read these JSON files instead of scraping terminal output; unknown fields and event types should be ignored for forward compatibility.

Other Pi extensions can use the versioned in-process event-bus RPC instead of scraping slash output or calling internal modules. Listen for subagents:rpc:v1:ready, send requests on subagents:rpc:v1:request, and read replies from subagents:rpc:v1:reply:<requestId>.

const requestId = crypto.randomUUID();
pi.events.on(`subagents:rpc:v1:reply:${requestId}`, (reply) => {
  // { version: 1, requestId, success: true, data } or
  // { version: 1, requestId, success: false, error: { code, message } }
});
pi.events.emit("subagents:rpc:v1:request", {
  version: 1,
  requestId,
  method: "spawn",
  params: { agent: "reviewer", task: "Review the current diff", context: "fresh" }
});

The v1 methods are ping, status, spawn, interrupt, and stop. status and interrupt reuse the normal control actions. spawn is async-only: omit async or set async: true, omit clarify or set clarify: false, and do not pass management action values. It goes through the same executor as the subagent tool, so agent discovery, validation, session attribution, spawn limits, child-safety depth, artifacts, and async status all behave the same. stop targets running async runs through the existing timeout control channel.

pi.events is in-process only. It does not reach separate Pi processes or child subagents; use the file lifecycle artifacts or pi-intercom for cross-process coordination.

If something feels misconfigured, run:

/subagents-doctor

or ask:

Check whether subagents and intercom are set up correctly.

Recommended orchestration pattern (scaffolding)

Use orchestration as parent-agent guidance, not as a runtime workflow mode. For implementation work, the recommended loop is:

clarify → planner → worker → fresh reviewers → worker

Use the optional prompt shortcuts below when you want the pattern to be repeatable.

Packaged planner, worker, and oracle default to forked context when a launch omits context; pass context: "fresh" when you intentionally want a fresh child run.

Child-safety boundaries are enforced at runtime. Spawned child sessions do not receive the bundled pi-subagents skill, and forked child context filtering removes parent-only subagent artifacts (including old hidden orchestration-instruction messages, slash/status/control messages, and prior parent subagent tool-call/tool-result history) while preserving ordinary prose and unrelated tool calls/results. By default, children do not register the subagent tool and receive boundary instructions that they are not the parent orchestrator and must not propose or run subagents. The explicit exception is an agent whose resolved builtin tools includes subagent; that child gets a child-safe subagent tool for the fanout work the parent assigned, still bounded by maxSubagentDepth.

Optional shortcuts

The package includes reusable prompt templates for common workflows. You do not need them, but they are handy when you want the same shape every time:

Prompt	Use it for
/parallel-review	Launch fresh-context reviewers with distinct angles, then synthesize what to fix.
/review-loop	Run parent-controlled worker, reviewer, and fix-worker cycles until clean or capped.
/parallel-research	Combine researcher and scout for external evidence, local code context, and practical tradeoffs.
/parallel-context-build	Run context-builder agents in parallel to produce planning handoff context and meta-prompts.
/parallel-handoff-plan	Combine external research and context-builder passes into an implementation handoff plan and meta-prompt.
/gather-context-and-clarify	Scout/research first, then ask the user the clarification questions that matter.
/parallel-cleanup	Run review-only cleanup passes after implementation.

Add autofix to /parallel-review or /parallel-cleanup to apply only the synthesized fixes worth doing now after reviewers return.

Native supervisor coordination

Child agents can talk back to the parent Pi session without installing pi-intercom. pi-subagents now provides the child-facing contact_supervisor tool and the parent-facing subagent_supervisor({ action: "reply" }) path natively. If no external pi-intercom tool owns the intercom name, the native channel also exposes intercom as a compatibility fallback.

Use it for work where the child might need a decision instead of guessing:

Run this implementation in the background. If the worker gets blocked or needs a product decision, have it ask me through intercom.

Ask oracle to review this plan. If it sees a decision I need to make, have it ask me instead of assuming.

The child can use one dedicated coordination tool:

• contact_supervisor: the child contacts the parent/supervisor session that delegated the task. Use reason: "need_decision" for blocking decisions or clarification, reason: "interview_request" for structured input, and reason: "progress_update" for short non-blocking updates when a discovery changes the plan. Do not ask for clarification when the only conflict is review-only/no-edit versus progress-writing or artifact-writing instructions; no-edit wins.

The parent replies with subagent_supervisor({ action: "reply", replyTo, message }) or checks pending requests with subagent_supervisor({ action: "pending" }). Supervisor messages are scoped to the exact Pi session id that spawned the child. A second Pi session in the same repository does not receive those requests.

Child-side routine completion handoffs are still not expected. If a child appears stalled, needs-attention notices can show up in the parent session with useful next actions, such as checking subagent({ action: "status" }), interrupting the run, or nudging the child.

If messages do not show up, run:

/subagents-doctor

For normal use, you do not need to configure anything. Advanced users can tune the bridge with intercomBridge in the configuration section below.

At this point, you know enough to use the plugin. The rest of this README is reference material for exact command syntax, custom agents, saved chains, worktrees, and configuration.

Optional pi-permission-system integration

@gotgenes/pi-permission-system adds a second policy layer — allow / ask / deny — on top of pi-subagents' visibility-based tool restrictions.

The two compose independently:

Layer	What it controls	Who provides it
Visibility	Which tools are registered before the session starts	pi-subagents (tools: frontmatter key)
Policy	Runtime allow/ask/deny decisions on every tool call, bash command, MCP operation	pi-permission-system (permission: frontmatter key)

Installing

pi install npm:@gotgenes/pi-permission-system

No configuration is required for the integration — it is automatic when both extensions are installed. pi-subagents passes the parent session identity to child processes via the PI_SUBAGENT_PARENT_SESSION environment variable, which the permission system uses to forward ask prompts from headless subagent processes back to the parent session's UI.

Per-agent permission frontmatter

Agent files can include a permission: block alongside the standard tools: key. The permission system reads it independently:

---
name: worker
tools: bash,read,write,edit
permission:
  "*": ask
  read: allow
  bash:
    "*": ask
    "git *": allow
    "npm test": allow
---

In this example the subagent extension restricts visibility to four tools, and the permission system then applies ask/allow policy within that visible set. Both keys coexist without collision.

Checking the integration

Run /subagents-doctor to check the permission system status. If ask prompts from children are not reaching the parent UI, verify both extensions are installed:

pi list

How it works

At session start, the interactive (root) session records its own identity in PI_SUBAGENT_PARENT_SESSION. When pi-subagents launches a child, it passes the launching session's identity to that child explicitly, falling back to the inherited environment variable. When the permission system inside a child encounters an ask permission, it reads this variable to locate the parent session and forwards the confirmation request there.

This resolves an interactive prompt only when the parent it points at is the interactive session — i.e. for the direct children of the root session. A nested child's parent is itself a headless subagent process with no UI to surface the prompt, so ask policies are best placed on agents that run as direct children of the interactive session.

Direct commands

Skip this section until you want exact syntax.

Command	Description
/run <agent> [task]	Run one agent; omit the task for self-contained agents
/chain agent1 "task1" -> agent2 "task2"	Run agents in sequence
/chain scout "scan" -> (reviewer "A" | reviewer "B") -> writer "fix"	Run a chain with a static parallel group inline
/parallel agent1 "task1" -> agent2 "task2"	Run agents in parallel
/run-chain <chainName> -- <task>	Launch a saved .chain.md or .chain.json workflow
/subagent-cost	Show parent plus child subagent token usage and cost for this session
/subagents-doctor	Show read-only setup diagnostics
/subagents-models [agent]	Show the runtime-loaded builtin model mapping, optionally filtered to one builtin
/subagents-profiles	List saved subagent profiles from ~/.pi/agent/profiles/pi-subagents/
/subagents-load-profile <name>	Replace only settings.subagents with a saved profile and optionally switch this session to the profile worker model
/subagents-refresh-provider-models <provider> [--force]	Create or refresh the cached provider model catalog
/subagents-generate-profiles <provider>	Generate <provider>.quota.json and <provider>.quality.json profiles
/subagents-check-profile <name>	Check a saved profile against the current registry and live model probes

Commands validate agent names locally, support tab completion, and send results back into the conversation.

Profiles and provider model catalogs

Profiles are stored under:

~/.pi/agent/profiles/pi-subagents/

Provider model catalogs are cached under:

~/.pi/agent/profiles/pi-subagents/providers/

Use the profile workflow like this:

/subagents-refresh-provider-models openai-codex
/subagents-generate-profiles openai-codex
/subagents-load-profile openai-codex.quota

/subagents-refresh-provider-models writes a serialized provider model catalog with observed registry data, simple role-oriented classification, and live probe results from tiny one-shot pi -p --model ... --no-tools checks. The cache refreshes when missing or stale; use --force to ignore freshness and probe again immediately.

/subagents-generate-profiles uses the provider catalog to produce quota and quality profiles. /subagents-check-profile re-checks each assigned model in a saved profile against the current registry and a live probe so you can detect model removals, auth problems, or stale assignments.

Per-step tasks

Use -> to separate steps and give each step its own task:

/chain scout "scan the codebase" -> planner "create an implementation plan"
/parallel scanner "find security issues" -> reviewer "check code style"

Both double and single quotes work. You can also use -- as a delimiter:

/chain scout -- scan code -> planner -- analyze auth

Steps without a task inherit behavior from the execution mode. Chain steps get {previous}, the prior step’s output. Parallel steps use the first available task as a fallback.

Inline parallel groups in /chain

Wrap a group of agents in parentheses and separate them with | to fan them out within a single chain step. The group runs all of its tasks concurrently, then the next -> step continues once they finish:

/chain scout "scan" -> (reviewer "review A" | reviewer "review B") -> writer "fix"

Notes:

• Groups must contain at least two tasks separated by |, each with its own task.
• Group syntax is only valid between -> separators, and the group must appear as a complete step.
• Only a step that opens with ( is a group. Parentheses inside a shared -- task (e.g. /chain scout -- inspect auth (backend)) stay literal text and keep the legacy single-agent behavior.
• A group is treated as the prior step’s output for the next sequential step.
• Tab completion suggests agents inside groups — after (, after |, and on each new -> step.

Add a [...] suffix right after the closing ) to set step-level options on the group:

/chain scout "scan" -> (reviewer "A" | reviewer "B")[concurrency=2,failFast,worktree] -> writer "fix"

Group option	Description
concurrency=N	Max tasks running at once within the group.
failFast	Stop the group as soon as one task fails.
worktree	Run each group task in its own git worktree.

Dynamic fanout (expand / collect) is intentionally not available inline — use the subagent({ chain: [...] }) tool API or a saved .chain.json for data-driven fan-out.

/chain scout "analyze auth" -> planner -> worker
# scout gets "analyze auth"; planner gets scout output; worker gets planner output

For a shared task, list agents and place one -- before the task:

/chain scout planner -- analyze the auth system
/parallel scout reviewer -- check for security issues

Inline per-step config

Append [key=value,...] to an agent name to override defaults. /chain applies every key below; /run and /parallel use the execution-behavior keys (output, outputMode, reads, model, skills, progress) and ignore chain-only metadata such as as, label, phase, count, outputSchema, and acceptance.

/chain scout[output=context.md] "scan code" -> planner[reads=context.md] "analyze auth"
/run scout[model=anthropic/claude-sonnet-4] summarize this codebase
/parallel reviewer[skills=code-review+security] "review backend" -> reviewer[model=openai/gpt-5-mini] "review frontend"

Key	Example	Description
output	output=context.md	Write results to a file. Absolute paths are used as-is. Relative paths in /run resolve under singleRunOutputBaseDir when configured, otherwise under the run's output artifact directory. Relative paths in /chain and /parallel live under the chain or parallel run directory.
outputMode	outputMode=file-only	Return only a concise file reference for saved output instead of the full saved content. Requires output; default is inline.
reads	reads=a.md+b.md	Read files before executing. + separates multiple paths.
model	model=anthropic/claude-sonnet-4	Override model for this step.
skills	skills=planning+review	Override available skills. + separates multiple skills.
progress	progress	Enable progress tracking.
as	as=context	Name this step’s output so later steps can reference it.
label	label=Recon	Human-readable label for the step.
phase	phase=analysis	Group steps into a named phase.
cwd	cwd=packages/api	Run the step in a subdirectory.
count	count=3	Fan a group task into N copies (only inside a ( ... ) group).
outputSchema	outputSchema=schema.json	Validate structured output against a JSON Schema file (path resolved against the session cwd, not an inline step cwd).
acceptance	acceptance=checked	Inline acceptance level: auto, attested, or checked. Use the tool API or saved .chain.json for object contracts such as none, verified, or reviewed.

Set output=false, reads=false, or skills=false to disable that behavior explicitly. Do not use output=false for file-only returns; use outputMode=file-only with an output path.

Inline [...] values must not contain spaces or commas — keep label/phase to single tokens.

Background and forked runs

Add --bg to run in the background:

/run scout "audit the codebase" --bg
/chain scout "analyze auth" -> planner "design refactor" -> worker --bg
/parallel scout "scan frontend" -> scout "scan backend" --bg

Add --fork to start each child from a real branched session created from the parent’s current leaf:

/run reviewer "review this diff" --fork
/chain scout "analyze this branch" -> planner "plan next steps" --fork
/parallel scout "audit frontend" -> reviewer "audit backend" --fork

You can combine them in either order:

/run reviewer "review this diff" --fork --bg
/run reviewer "review this diff" --bg --fork

Background runs are detached. If the parent agent has other independent work, it should keep working. When it has nothing useful to do until a background result arrives, it should call the wait tool instead of running sleep or status-polling loops. wait() returns when the next active run finishes or needs attention and keeps the turn alive for normal notification delivery; use wait({ all: true }) to drain every active run, wait({ id }) for one run, and wait({ timeoutMs }) to cap the block.

wait is what lets a background-launching skill keep moving in a single turn, including non-interactive pi -p invocations where there is no subsequent turn to receive a completion notification. Ending the turn to wait for a completion only works in an interactive session where the user will prompt the agent again; in a run-to-completion skill or a non-interactive run, use wait so the still-running children are not abandoned.

The oracle and worker builtins are designed for an explicit decision loop. A typical pattern is to ask oracle for diagnosis and a recommended execution prompt, then only run worker after the main agent approves that direction.

Clarify and launch UI

Tool calls launch directly by default. Set clarify: true on single, parallel, or chain runs when you want to preview and edit the workflow before it runs; slash commands launch directly.

Common clarify keys:

• Enter runs in the foreground, or in the background if background is toggled on
• Esc cancels or backs out
• ↑↓ moves between steps or tasks
• e edits the task/template
• m selects a model
• t selects thinking level
• s selects skills
• b toggles background execution
• w edits output/write behavior where supported
• r edits reads where supported
• p toggles progress tracking where supported Picker screens use ↑↓, Enter, Esc, and type-to-filter. The full-screen editor supports word wrapping, paste, Esc to save, and Ctrl+C to discard.

Agents and chains

Agents are markdown files with YAML frontmatter and a system prompt body. They define the specialist that will run in the child Pi process.

Agent locations, lowest to highest priority:

Scope	Path
Builtin	~/.pi/agent/extensions/subagent/agents/
Installed package	package.json pi-subagents.agents or pi.subagents.agents
User	~/.pi/agent/agents/**/*.md
Project	Project config agents/**/*.md (.pi/agents/**/*.md in standard Pi)

Project discovery also reads legacy .agents/**/*.md files. Nested subdirectories are discovered recursively. .chain.md files do not define agents. Installed Pi packages can expose agent directories from either {"pi-subagents":{"agents":["./agents"]}} or {"pi":{"subagents":{"agents":["./agents"]}}} in their package manifest. Package agents load above builtins and below user/project agents. If both .agents/ and the project config agents directory define the same parsed runtime agent name, the project config directory wins. Use agentScope: "user" | "project" | "both" to control discovery; both is the default and project definitions win runtime-name collisions.

Builtin agents load at the lowest priority, so a user or project agent with the same name overrides them. They do not pin a provider model; they inherit your current Pi default model unless you set subagents.defaultModel or subagents.agentOverrides.<name>.model. oracle is an advisory reviewer that critiques direction and proposes an execution prompt without editing files. worker is the implementation agent for normal tasks and approved oracle handoffs.

The researcher builtin uses web_search, fetch_content, and get_search_content; those require pi-web-access:

pi install npm:pi-web-access

Builtin overrides

You can override selected builtin fields without copying the whole agent. Overrides live in settings:

• User: ~/.pi/agent/settings.json
• Project: project config settings file (.pi/settings.json in standard Pi)

Example:

{
  "subagents": {
    "agentOverrides": {
      "reviewer": {
        "inheritProjectContext": false
      }
    }
  }
}

Supported override fields are model, fallbackModels, thinking, systemPromptMode, inheritProjectContext, inheritSkills, defaultContext, disabled, skills, tools, and systemPrompt. Use defaultContext: false in builtin overrides to clear an inherited context default. Project overrides beat user overrides.

Set subagents.defaultModel to give all subagents without an explicit model their own default model, separate from the parent session model. Per-agent model overrides and agent frontmatter still win.

Set disabled: true to hide a builtin from runtime discovery and agent-facing subagent({ action: "list" }) output. For bulk control, set subagents.disableBuiltins: true in settings. You can also toggle a single agent without editing settings by hand: subagent({ action: "disable", agent: "reviewer" }) writes that override, and subagent({ action: "enable", agent: "reviewer" }) removes it.

Set subagents.disableThinking: true to clear bundled builtin thinking defaults globally for providers that do not support :low, :medium, :high, or similar model suffixes. A higher-precedence per-agent thinking override can opt one builtin back in.

Prompt assembly

Subagents are designed to be narrow by default. Custom agents start with a clean system prompt and only the context you intentionally give them. They do not automatically inherit Pi’s whole base prompt, project instruction files, or discovered skills catalog.

Use these fields when an agent should see more:

Field	Effect
systemPromptMode: append	Append the agent prompt to Pi’s normal base prompt.
inheritProjectContext: true	Keep inherited project instructions from files like AGENTS.md and CLAUDE.md.
inheritSkills: true	Let the child see Pi’s discovered skills catalog.
defaultContext: fork	Use forked session context when a launch omits context; explicit context: "fresh" still wins.

Builtin agents opt into project instruction inheritance by default so they follow repo-specific rules out of the box. delegate also uses append mode because its job is orchestration inside the parent workflow.

Agent frontmatter

A typical agent looks like this:

---
name: scout
# Optional: registers this as code-analysis.scout while preserving name: scout
package: code-analysis
description: Fast codebase recon
tools: read, grep, find, ls, bash, mcp:chrome-devtools
extensions:
subagentOnlyExtensions: ./tools/child-only-search.ts
model: claude-haiku-4-5
fallbackModels: openai/gpt-5-mini, anthropic/claude-sonnet-4
thinking: high
systemPromptMode: replace
inheritProjectContext: false
inheritSkills: false
skills: safe-bash, chrome-devtools
output: context.md
defaultReads: context.md
defaultProgress: true
completionGuard: false
interactive: true
maxSubagentDepth: 1
---

Your system prompt goes here.

Important fields:

Field	Notes
package	Optional package identifier. A file with name: scout and package: code-analysis registers as code-analysis.scout; serialization keeps name and package separate.
tools	Builtin tool allowlist. mcp: entries select direct MCP tools when pi-mcp-adapter is installed.
extensions	Omitted means normal extensions; empty means no extensions; comma-separated values allowlist specific extensions.
subagentOnlyExtensions	Comma-separated extension paths loaded only in spawned child sessions for this agent. Tools registered there are unavailable to the main agent unless also installed through normal Pi extension configuration.
model	Default model. Bare ids prefer the current provider when possible, then unique registry matches.
fallbackModels	Ordered backup models for provider/model failures such as quota, auth, timeout, or unavailable model. Ordinary task failures do not trigger fallback.
thinking	Appended as a :level suffix at runtime unless a suffix is already present.
systemPromptMode	replace by default; append keeps Pi’s base prompt.
inheritProjectContext	Keeps or strips inherited project instruction blocks.
inheritSkills	Keeps or strips Pi’s discovered skills catalog.
defaultContext	Optional fresh or fork launch context default for this agent.
skills	Adds specific skills to the child’s available skill list, regardless of inheritSkills.
output	Default single-agent output file.
defaultReads	Files to read before running in chain/parallel behavior.
defaultProgress	Maintain progress.md.
completionGuard	Set false only for non-implementation agents that may mention implementation words while using mutation-capable tools such as bash.
interactive	Parsed for compatibility but not enforced in v1.
maxSubagentDepth	Tightens nested delegation for this agent's children.
memory	Opt-in role-specific persistent memory. memory: { scope: "project" | "user", path: "<name>" } injects the first lines of a MEMORY.md from a dedicated agent-memory/ directory into the child system prompt. Agents with write tools (edit/write/bash) get a read-write block; read-only agents get a read-only fallback. Project scope resolves under <project>/.pi/agent-memory/, user scope under ~/.pi/agent/agent-memory/. Paths are validated against traversal and symlink escape.

Per-agent persistent memory

A recurring custom agent can opt into a durable, role-specific memory scope with the memory frontmatter field. This is independent of Pi's own parent/session/project memory system and writes nothing to it; memory lives under a dedicated agent-memory/ namespace so the two never collide.

memory:
  scope: project
  path: security-reviewer

On each run, the first 200 lines of MEMORY.md in the resolved memory directory are injected into the child system prompt so the agent can recall accumulated role notes such as threat-model entries, release gotchas, or verified commands. Agents that have write tools (edit, write, or bash, or no tools allowlist at all) are told they may append concise dated entries to the file. Agents without write tools receive a read-only memory block and are not instructed to edit it, so a read-only reviewer can still recall prior notes without being granted write capability. The memory directory is never created eagerly; the agent's own write tool creates it (and MEMORY.md) on the first persist. Memory paths are validated against ./.. traversal and symlink escape, and an unsafe or unresolvable scope is silently skipped rather than breaking the run.

Project-scoped memory resolves under <project>/.pi/agent-memory/<path> and travels with the repo. User-scoped memory resolves under ~/.pi/agent/agent-memory/<path> and is shared across projects for that agent.

Tool and extension selection

If tools is omitted, pi-subagents does not pass --tools, so the child gets Pi’s normal builtin tools. If tools is present, regular tool names become an explicit allowlist. mcp: entries are split out and forwarded as direct MCP selections. Path-like tools entries, such as extension paths or .ts/.js files, are treated as tool-extension paths rather than builtin tool names. Agents that declare only known read-only builtin tools skip the implementation completion guard, but bash, unknown tools, and MCP tools stay mutation-capable. Use completionGuard: false for bash-enabled validators or advisors that should never be judged as implementation agents.

Examples:

• tools omitted and extensions omitted: normal builtins and normal extensions.
• tools: mcp:chrome-devtools: normal builtins plus direct Chrome DevTools MCP tools.
• tools: read, bash, mcp:chrome-devtools: only read and bash as builtins, plus direct Chrome DevTools MCP tools.
• tools: subagent, read: a child-safe subagent tool is available inside that child so it can run explicitly assigned nested fanout.

Direct MCP tools require pi-mcp-adapter. Subagents only receive direct MCP tools when mcp: entries are listed in their frontmatter; global directTools: true in mcp.json is not enough by itself. The generic mcp proxy tool can still be used for discovery when available. The adapter caches tool metadata at startup, so after connecting a new MCP server for the first time, restart Pi before relying on direct tools. An mcp: entry named subagent does not authorize nested fanout; only the builtin subagent tool name does.

extensions controls child extension loading:

# Omitted: all normal extensions load

# Empty: no extensions
extensions:

# Allowlist
extensions: /abs/path/to/ext-a.ts, /abs/path/to/ext-b.ts

When extensions is present, it takes precedence over extension paths implied by tools entries.

Use subagentOnlyExtensions when a custom extension tool should exist only inside child sessions. It is scoped by agent config: every run of that agent receives those extension paths, while other agents do not unless they declare the same field. The current model does not have a separate named-subagent audience inside one agent definition.

Chain files

Chains are reusable workflows stored separately from agent files. Use .chain.md for simple sequential saved chains. Use .chain.json when a chain needs dynamic fanout.

Scope	Path
Installed package	package.json pi-subagents.chains or pi.subagents.chains
User	~/.pi/agent/chains/**/*.chain.md, ~/.pi/agent/chains/**/*.chain.json
Project	Project config chains/**/*.chain.md, chains/**/*.chain.json (.pi/chains/... in standard Pi)

Nested subdirectories are discovered recursively. Installed Pi packages can expose chain directories from either {"pi-subagents":{"chains":["./chains"]}} or {"pi":{"subagents":{"chains":["./chains"]}}} in their package manifest. Package chains load below user/project chains. If both .chain.md and .chain.json define the same parsed runtime chain name in the same scope, .chain.json wins. If user and project scopes define the same parsed runtime chain name, the project chain wins. Chains support the same optional package frontmatter as agents; name: review-flow plus package: code-analysis runs as code-analysis.review-flow.

Example:

---
name: scout-planner
description: Gather context then plan implementation
---

## scout
phase: Context
label: Map auth flow
as: context
output: context.md

Analyze the codebase for {task}

## planner
phase: Planning
label: Implementation plan
reads: context.md
model: anthropic/claude-sonnet-4-5:high
progress: true

Create an implementation plan based on {outputs.context}

Each .chain.md ## agent-name section is a step. Config lines such as phase, label, as, outputSchema, output, outputMode, reads, model, skills, and progress go immediately after the header. A blank line separates config from task text. In saved .chain.md files, outputSchema is a path to a JSON Schema file; direct tool calls and .chain.json files can pass the schema object inline.

For output, reads, skills, and progress, chain behavior is three-state: omitted inherits from the agent, a value overrides, and false disables.

Use phase to group related work in status output, label for a readable step name, and as to store a successful step or parallel task result for later {outputs.name} references. Duplicate as names, invalid identifiers, and unknown output references fail before child execution.

Dynamic fanout is available only through direct subagent({ chain: [...] }) JSON or saved .chain.json files. It expands an array from a prior structured named output, runs one child template per item, and stores the ordered collection under collect.as. The source must be structured output; prose is never parsed. expand.maxItems is required, over-limit arrays fail, nested fanout and arbitrary expressions are not supported, and .chain.md has no dynamic syntax in this release.

{
  "name": "dynamic-review",
  "description": "Find review targets, fan out reviewers, then synthesize.",
  "chain": [
    {
      "agent": "scout",
      "task": "Return {\"items\":[{\"path\":\"...\",\"reason\":\"...\"}]} via structured_output.",
      "as": "targets",
      "outputSchema": { "type": "object" }
    },
    {
      "expand": {
        "from": { "output": "targets", "path": "/items" },
        "item": "target",
        "key": "/path",
        "maxItems": 12
      },
      "parallel": {
        "agent": "reviewer",
        "label": "Review {target.path}",
        "task": "Review {target.path}. Reason: {target.reason}",
        "outputSchema": { "type": "object" }
      },
      "collect": { "as": "reviews" },
      "concurrency": 4
    },
    {
      "agent": "worker",
      "task": "Synthesize fixes from {outputs.reviews}"
    }
  ]
}

Create simple .chain.md chains by writing files directly or with the subagent({ action: "create", config: ... }) management action. Create dynamic .chain.json chains by writing the JSON file directly. Run saved chains with natural language or:

/run-chain scout-planner -- refactor authentication

Chain variables

Task templates support:

Variable	Description
{task}	Original task from the first step.
{previous}	Output from the prior step, or aggregated output from a parallel step.
{chain_dir}	Path to the chain artifact directory.
{outputs.name}	Text value from a prior step or completed parallel task with as: "name".

Parallel outputs are aggregated with clear separators before being passed to the next step:

=== Parallel Task 1 (worker) ===
...

=== Parallel Task 2 (worker) ===
...

Skills

Skills are SKILL.md files made available to an agent. The prompt includes skill metadata and the file location; the agent reads the full skill file only when the task matches.

Discovery uses project-first precedence:

1. Project config skills/{name}/SKILL.md (.pi/skills/{name}/SKILL.md in standard Pi)
2. Project packages and project settings packages via package.json -> pi.skills
3. Current task cwd package via package.json -> pi.skills
4. Project config settings.json -> skills
5. ~/.pi/agent/skills/{name}/SKILL.md
6. User packages and user settings packages via package.json -> pi.skills
7. ~/.pi/agent/settings.json -> skills

Use agent defaults, override them at runtime, or disable them:

{ agent: "scout", task: "..." }
{ agent: "scout", task: "...", skill: "tmux, safe-bash" }
{ agent: "scout", task: "...", skill: false }

For chains, skill at the top level is additive. A step-level skill overrides that step; false disables skills for that step.

Available skills use this shape:

The following configured skills are available to this subagent.
Use the read tool to load a skill's file when the task matches its description.
When a skill file references a relative path, resolve it against the skill directory (parent of SKILL.md / dirname of the path) and use that absolute path in tool commands.

<available_skills>
  <skill>
    <name>safe-bash</name>
    <description>Run shell commands safely.</description>
    <location>/absolute/path/to/safe-bash/SKILL.md</location>
  </skill>
</available_skills>

If an agent has an explicit tools allowlist and resolved skills, read is added for that child run so the listed skill files can be loaded on demand.

Missing skills do not fail execution. The result summary shows a warning.

Bundled skill

The package bundles a pi-subagents skill that is automatically available to the parent agent when the extension is installed. It is for the orchestrating parent only: child subagents never receive it, and their context is explicitly filtered to strip parent-only orchestration instructions.

What the bundled skill covers:

• Delegation patterns: when to launch which agent, whether to use single, parallel, chain, or async mode, and whether to use fresh or forked context
• Prompt workflow recipes: how to apply the packaged techniques directly with subagent(...) when the user describes the workflow in natural language instead of invoking a slash command. This includes parallel review, review-loop, parallel research, parallel context-build, parallel handoff-plan, gather-context-and-clarify, and parallel cleanup
• Role-agent prompting guidance: compact contract prompts instead of long scripts, what to include in role-specific meta prompts, and retrieval budgets for researchers
• Safety boundaries: child agents must not run subagents unless their resolved builtin tools explicitly include subagent, must not invent intercom targets, and must escalate unapproved decisions
• Intercom conventions: when to ask vs send, and how parent-side supervisor/result delivery works through the native channel
• Control and diagnostics: attention signals, soft interrupts, status, and the doctor action

If you are writing an agent that orchestrates subagents, the bundled skill helps it behave correctly without guessing the patterns. If you are a human user, you do not need to read it directly; the README and prompt shortcuts encode the same workflows in user-facing form.

Programmatic tool usage

These are the parameters the LLM passes when it calls the subagent tool. Most users ask naturally or use slash commands instead.

Execution examples

// Single agent
{ agent: "worker", task: "refactor auth" }
{ agent: "scout", task: "find todos", maxOutput: { lines: 1000 } }
{ agent: "scout", task: "investigate", output: false }
{ agent: "scout", task: "write a large report", output: "reports/scout.md", outputMode: "file-only" }

// Forked context
{ agent: "worker", task: "continue this thread", context: "fork" }

// Parallel
{ tasks: [{ agent: "scout", task: "a" }, { agent: "reviewer", task: "b" }] }
{ tasks: [{ agent: "scout", task: "audit auth", count: 3 }] }
{ tasks: [{ agent: "scout", task: "audit frontend" }, { agent: "reviewer", task: "audit backend" }], context: "fork" }

// Chain
{ chain: [
  { agent: "scout", task: "Gather context for auth refactor" },
  { agent: "planner" },
  { agent: "worker" },
  { agent: "reviewer" }
]}

// Chain in the background, suitable for unblocking the main chat
{ chain: [...], async: true }

// Chain with fan-out/fan-in
{ chain: [
  { agent: "scout", task: "Gather context", phase: "Context", label: "Map code", as: "context" },
  { parallel: [
    { agent: "worker", task: "Implement feature A from {outputs.context}", label: "Feature A", as: "featureA" },
    { agent: "worker", task: "Implement feature B from {outputs.context}", label: "Feature B", as: "featureB" }
  ], concurrency: 2, failFast: true },
  { agent: "reviewer", task: "Review {outputs.featureA} and {outputs.featureB}" }
]}

// Dynamic fanout from structured output
{ chain: [
  {
    agent: "scout",
    task: "Return review targets as structured_output: { items: [{ path, reason }] }",
    as: "targets",
    outputSchema: { type: "object" }
  },
  {
    expand: { from: { output: "targets", path: "/items" }, item: "target", key: "/path", maxItems: 12 },
    parallel: { agent: "reviewer", task: "Review {target.path}. Reason: {target.reason}", outputSchema: { type: "object" } },
    collect: { as: "reviews" },
    concurrency: 4
  },
  { agent: "worker", task: "Synthesize fixes from {outputs.reviews}" }
] }

// Strict structured output for reliable handoff data
{ chain: [
  {
    agent: "scout",
    task: "Return the key files and risks for {task}",
    as: "scan",
    outputSchema: {
      type: "object",
      required: ["files", "risks"],
      properties: {
        files: { type: "array", items: { type: "string" } },
        risks: { type: "array", items: { type: "string" } }
      }
    }
  },
  { agent: "planner", task: "Plan from this scan: {outputs.scan}" }
] }

// Worktree isolation
{ tasks: [
  { agent: "worker", task: "Implement auth" },
  { agent: "worker", task: "Implement API" }
], worktree: true }

Management actions

Agent definitions are not loaded into context by default. Management actions let the LLM discover, inspect, create, update, and delete agents and chains at runtime.

{ action: "list" }
{ action: "list", agentScope: "project" }
{ action: "get", agent: "scout" }
{ action: "models" }
{ action: "models", agent: "reviewer" }
{ action: "get", agent: "code-analysis.scout" }
{ action: "get", chainName: "review-pipeline" }

{ action: "create", config: {
  name: "Code Scout",
  package: "code-analysis",
  description: "Scans codebases for patterns and issues",
  scope: "user",
  systemPrompt: "You are a code scout...",
  systemPromptMode: "replace",
  inheritProjectContext: false,
  inheritSkills: false,
  model: "anthropic/claude-sonnet-4",
  fallbackModels: ["openai/gpt-5-mini", "anthropic/claude-haiku-4-5"],
  tools: "read, bash, mcp:github/search_repositories",
  extensions: "",
  skills: "parallel-scout",
  thinking: "high",
  output: "context.md",
  reads: "shared-context.md",
  progress: true
}}

{ action: "create", config: {
  name: "review-pipeline",
  description: "Scout then review",
  scope: "project",
  steps: [
    { agent: "scout", task: "Scan {task}", output: "context.md" },
    { agent: "reviewer", task: "Review {previous}", reads: ["context.md"] }
  ]
}}

{ action: "update", agent: "code-analysis.scout", config: { model: "openai/gpt-4o" } }
{ action: "update", chainName: "review-pipeline", config: { steps: [...] } }
{ action: "delete", agent: "scout" }
{ action: "delete", chainName: "review-pipeline" }

{ action: "eject", agent: "reviewer" }
{ action: "eject", agent: "reviewer", agentScope: "project" }
{ action: "disable", agent: "reviewer" }
{ action: "enable", agent: "reviewer", agentScope: "project" }
{ action: "reset", agent: "reviewer" }

create uses config.scope, not agentScope. config.name is the local frontmatter name; optional config.package registers the runtime name as {package}.{name} and is saved as separate name and package frontmatter. update and delete use the runtime name and agentScope only when the same runtime name exists in multiple scopes. To clear optional string fields, including package, set them to false or "".

eject copies a bundled builtin or package agent verbatim into the user or project agent dir (default user) as an editable custom file that shadows the original, so you can customize a builtin without hunting package files. disable writes a reversible agentOverrides.<name>.disabled: true entry to the user or project settings file (default user); the agent stays on disk but is hidden from runtime discovery and list. enable removes that disabled field while preserving any other override fields on the same entry. reset deletes the scope's custom agent file and/or settings override entry, restoring the bundled default; it refuses if no bundled default exists (use delete for purely custom agents). All four accept agentScope: "user" | "project" and operate in one scope at a time; project overrides still win over user ones, so a project-scope disable survives a user-scope enable until you target the project scope.

Parameter reference

Param	Type	Default	Description
agent	string	-	Agent name for single mode, or target for management actions.
task	string	-	Task string for single mode.
action	string	-	list, get, create, update, delete, status, interrupt, resume, steer, append-step, or doctor.
chainName	string	-	Chain name for management actions.
config	object/string	-	Agent or chain config for create/update.
output	string | false	agent default	Override single-agent output file.
outputMode	"inline" | "file-only"	inline	Return saved output inline or as a concise saved-file reference. file-only requires an output path.
skill	string | string[] | false	agent default	Override skills or disable all.
model	string	agent default	Override model.
tasks	array	-	Top-level parallel tasks. Supports agent, task, cwd, count, output, outputMode, reads, progress, skill, model, toolBudget, and acceptance.
concurrency	number	config or 4	Top-level parallel concurrency.
worktree	boolean	false	Create isolated git worktrees for parallel tasks.
chain	array	-	Sequential, static parallel, and dynamic fanout chain steps. Steps and chain parallel tasks support phase, label, as, outputSchema, and acceptance in addition to the usual execution fields. Dynamic fanout uses expand, one child parallel template, and collect. With action: "append-step", pass exactly one step to append to a running async chain.
context	fresh | fork	per-agent default or fresh	Explicit fresh or fork overrides every child. When omitted, each agent uses its own defaultContext; fork creates real branched sessions from the parent leaf. Packaged planner, worker, and oracle default to fork.
chainDir	string	temp chain dir	Persistent directory for chain artifacts.
view	fleet | transcript	-	Optional status view for the active fleet surface or transcript tail inspection.
lines	number	80	Maximum transcript lines for action: "status", view: "transcript"; capped at 500.
clarify	boolean	false	Show TUI preview/edit flow. Explicit clarify: true keeps the run foreground for the clarify UI.
agentScope	user | project | both	both	Agent discovery scope. Project wins on collisions.
async	boolean	false	Background execution. For chains, clarify: true explicitly keeps the run foreground for the clarify UI.
timeoutMs / maxRuntimeMs	number	none	Optional run-level max runtime in milliseconds for foreground and async/background runs.
turnBudget	object	none	Optional assistant-turn budget { maxTurns, graceTurns }. At maxTurns the child is warned to wrap up; after graceTurns (default 1) more assistant turns the run is aborted and partial output is returned.
toolBudget	object	none	Optional child tool-call budget { soft?, hard, block? }. At soft the child is nudged to finalize. After hard, configured tools are blocked; block defaults to read, grep, find, and ls, or use "*" to block every tool call. Final assistant text is never blocked.
cwd	string	runtime cwd	Override working directory.
maxOutput	object	200KB, 5000 lines	Final output truncation limits.
artifacts	boolean	true	Write debug artifacts.
includeProgress	boolean	false	Include full progress in result.
share	boolean	false	Upload session export to GitHub Gist.
sessionDir	string	derived	Override session log directory.
acceptance	string/object/false	inferred	Override the run's inferred acceptance gates. Use "auto", "attested", "checked", "verified", "reviewed", or { level: "none", reason: "..." }.

context: "fork" fails fast when the parent session is not persisted, the current leaf is missing, or the branched child session cannot be created. When the inherited transcript contains signed Anthropic thinking / redacted_thinking blocks, pi-subagents strips those provider-private blocks from the forked child session and forces the child run's thinking level to off so Anthropic does not reject modified signatures after branching or compaction. Forking never silently downgrades to fresh. In multi-agent runs that omit context, each agent/task/step follows its own defaultContext, so a fresh-default scout can run fresh beside a fork-default worker. Pass explicit context: "fork" or context: "fresh" when you intentionally want one context for every child.

Use outputMode: "file-only" when a saved output may be large and the parent only needs a pointer. The returned text is a compact reference like Output saved to: /abs/report.md (48.2 KB, 2847 lines). Read this file if needed. Failed runs and save errors still return normal inline output for debugging. In chains, later {previous} steps receive the same compact reference when the prior step used file-only mode.

Sequential and parallel chain tasks accept agent, task, phase, label, as, outputSchema, cwd, output, outputMode, reads, progress, skill, model, and toolBudget. Parallel tasks also accept count. Parallel step groups accept parallel, concurrency, failFast, and worktree. If outputSchema is present, the child must call structured_output with schema-valid JSON; prose-only completion or invalid JSON fails the step. Validated structured values are preserved on the step result, and as also exposes a compact text representation through {outputs.name}.

Status and control actions:

subagent({ action: "status" })
subagent({ action: "status", view: "fleet" })
subagent({ action: "status", id: "<run-id>" })
subagent({ action: "status", id: "<run-id>", view: "transcript", index: 0, lines: 80 })
subagent({ action: "status", id: "<nested-run-id>" })
subagent({ action: "interrupt", id: "<run-id>" })
subagent({ action: "interrupt", id: "<nested-run-id>" })
subagent({ action: "resume", id: "<run-id>", message: "follow-up question" })
subagent({ action: "resume", id: "<run-id>", index: 1, message: "follow-up for child 2" })
subagent({ action: "resume", id: "<nested-run-id>", message: "follow-up for a nested child" })
subagent({ action: "steer", id: "<run-id>", message: "guidance for the running child" })
subagent({ action: "steer", id: "<run-id>", index: 1, message: "guidance for child 2" })
subagent({ action: "append-step", id: "<run-id>", chain: [{ agent: "worker", task: "Continue from {previous}" }] })
subagent({ action: "doctor" })

status resolves exact foreground ids, top-level async ids, and nested run ids before falling back to prefix matching. view: "fleet" is an optional read-only active-run surface with transcript commands; it does not add steering or stop controls. view: "transcript" tails the selected run's live output-<index>.log or persisted session transcript, with lines capped at 500. Nested status shows the root/parent path, nested children, session/artifact paths when known, and nested control commands. Inside child-safe fanout mode, bare status requires an id when no local foreground run is active, so children cannot enumerate unrelated top-level async runs. Bare interrupt still targets only the visible top-level run; interrupting a nested run requires its explicit nested id.

resume sends the follow-up directly when an async child is still reachable over intercom. After completion, it revives the child by starting a new async child from the stored child session file. Multi-child async runs and remembered foreground single, parallel, or chain runs can be revived by passing index to choose the child. Nested runs can be resumed by nested id when their live route or persisted session metadata is available. Revive starts a new child process from the old session context; it does not restart the same OS process, and it requires the chosen child to have a persisted .jsonl session file.

steer queues non-terminal guidance for a running async Pi child, or for a pending indexed child that will start later in the same async run. It does not interrupt, pause, or revive a child. Delivery requires the spawned Pi session to support mid-run sendUserMessage(..., { deliverAs: "steer" }); unsupported runtimes keep the request visible in control artifacts but cannot receive it live. Use index for multi-child runs when you want to steer one child; without index, steering targets the currently running child or children.

append-step accepts exactly one sequential, static parallel, or dynamic fanout chain step for a top-level async chain whose status is still running. The step is persisted in the run directory and becomes eligible only after the chain's already-queued steps finish; completed, failed, paused, foreground, single, and top-level parallel runs reject appends.

Worktree isolation

Parallel agents can clobber each other if they edit the same checkout. worktree: true gives each parallel child its own git worktree branched from HEAD.

{ tasks: [
  { agent: "worker", task: "Implement auth", count: 2 },
  { agent: "worker", task: "Implement API" }
], worktree: true }

{ chain: [
  { agent: "scout", task: "Gather context" },
  { parallel: [
    { agent: "worker", task: "Implement feature A from {previous}" },
    { agent: "worker", task: "Implement feature B from {previous}" }
  ], worktree: true },
  { agent: "reviewer", task: "Review all changes from {previous}" }
]}

Requirements:

• run inside a git repo
• working tree must be clean
• node_modules/ is symlinked into each worktree when present
• task-level cwd overrides must be omitted or match the shared cwd
• configured worktreeSetupHook must return valid JSON before timeout

By default, worktrees are created under the system temp directory. Set worktreeBaseDir in config, or PI_SUBAGENTS_WORKTREE_DIR when config is unset, to put them under a stable trusted directory. Missing base directories are created automatically.

After a worktree parallel step completes, per-agent diff stats are appended to the output and full patch files are written to artifacts. Worktrees and temp branches are cleaned up in finally blocks.

Configuration

pi-subagents reads optional JSON config from ~/.pi/agent/extensions/subagent/config.json.

toolDescriptionMode

{ "toolDescriptionMode": "compact" }

Controls the parent-facing subagent tool description registered at startup. full is the default. compact keeps the execution modes, async/wait guidance, child-safety boundary, management/action split, one-writer review guidance, and artifact/status essentials with less prompt bloat.

custom reads subagent-tool-description.md from the project config directory, then from ~/.pi/agent/subagent-tool-description.md. Missing, empty, unreadable, or oversized custom files fall back to the full description. Custom templates may use {{fullDescription}}, {{compactDescription}}, {{safetyGuidance}}, {{agentDir}}, and {{projectConfigDir}}; the safety guidance is always present so custom prose cannot remove the runtime guardrails. Restart Pi after changing the mode or custom file.

asyncByDefault

{ "asyncByDefault": true }

Makes top-level calls use background execution when the request does not explicitly set async. Callers can still force foreground with async: false unless forceTopLevelAsync is enabled.

forceTopLevelAsync

{ "forceTopLevelAsync": true }

Forces depth-0 single, parallel, and chain runs into background mode and bypasses clarify UI by forcing clarify: false. Nested calls keep their own inherited settings.

globalConcurrencyLimit

{ "globalConcurrencyLimit": 20 }

Caps simultaneously running subagent tasks within a single run across top-level parallel tasks, inline chain parallel groups, and dynamic fanout groups. The default is 20; invalid values are clamped to 1. Per-step concurrency and parallel.concurrency still apply, so effective concurrency is the lower of the local cap and the available global slots.

maxSubagentSpawnsPerSession

{ "maxSubagentSpawnsPerSession": 40 }

Caps the total number of child subagent launches allowed during one parent session, including single runs, parallel task counts, static chain steps, and bounded dynamic fanout children. Set PI_SUBAGENT_MAX_SPAWNS_PER_SESSION to override the config for a process. The default is 40; 0 blocks new subagent launches for that session.

scheduledRuns

{ "scheduledRuns": { "enabled": true, "maxPending": 20, "maxLatenessMs": 300000 } }

Enables optional one-shot scheduled subagent runs. When enabled, subagent({ action: "schedule", agent, task?, schedule: "+10m" | "2030-01-01T09:00:00Z", scheduleName? }) defers a subagent launch until a future time. Absolute ISO timestamps must include a timezone (Z or an offset such as +05:30). The scheduled run launches as a normal tracked async run with fresh context once it fires, and joins the existing async widget, status, wait, and completion-notification paths. schedule-list, schedule-status, and schedule-cancel manage pending jobs. Schedules are persisted per session and restored after a Pi restart; a job missed by more than maxLatenessMs while Pi is unavailable is marked missed instead of firing late. maxPending caps the number of pending or running scheduled jobs per session (default 20). The feature is opt-in: leave enabled unset to keep scheduling out of the tool surface and prompt. Only schedule explicit delayed runs the user asked for.

parallel

{
  "parallel": {
    "maxTasks": 12,
    "concurrency": 6
  }
}

maxTasks defaults to 8; concurrency defaults to 4. Per-call concurrency takes precedence.

defaultSessionDir

{ "defaultSessionDir": "~/.pi/agent/sessions/subagent/" }

Session directory precedence is: params.sessionDir, then config.defaultSessionDir, then a directory derived from the parent session. Sessions are always enabled.

singleRunOutputBaseDir

{ "singleRunOutputBaseDir": "~/.pi/subagent-outputs" }

Routes relative output paths for single-agent /run calls under this directory. Absolute per-call or agent output paths are still used as-is. When unset, relative single-run outputs go under the run's output artifact directory instead of the project root.

maxSubagentDepth

{ "maxSubagentDepth": 1 }

Controls nested delegation when no inherited PI_SUBAGENT_MAX_DEPTH is already in effect. Per-agent maxSubagentDepth can tighten the limit for that agent’s child runs, but cannot relax an inherited stricter limit. This applies even to children that explicitly declare tools: subagent; at the cap, execution fanout is blocked instead of silently hiding nested work.

PI_SUBAGENT_PI_BINARY

export PI_SUBAGENT_PI_BINARY=/path/to/pi-or-wrapper

Overrides the command used to launch child Pi processes. Package wrappers can set this to their own pi/agent binary so subagents inherit wrapper flags, environment setup, and bundled resources without relying on PATH ordering. Empty or whitespace-only values are ignored.

intercomBridge

{
  "intercomBridge": {
    "mode": "always",
    "instructionFile": "./intercom-bridge.md"
  }
}

Controls whether subagents receive runtime intercom coordination instructions and whether intercom and contact_supervisor are auto-added to their tool allowlist when needed.

Fields:

• mode: default always; use fork-only to inject only for forked runs, or off to disable the bridge.
• instructionFile: optional Markdown template replacing the default bridge instructions. {orchestratorTarget} is interpolated. Relative paths resolve from ~/.pi/agent/extensions/subagent/.

Bridge activation requires a targetable current parent session id, which pi-subagents passes to children automatically. It no longer depends on an external pi-intercom installation or per-agent extension allowlists.

The default injected guidance tells children to use contact_supervisor with reason: "need_decision" when blocked or needing a decision, reason: "progress_update" only for meaningful blocked/progress updates, generic intercom as fallback plumbing, and avoid routine completion handoffs.

worktreeBaseDir

{ "worktreeBaseDir": "/Users/matt/code/.worktrees/pi-subagents" }

Sets the base directory for worktree: true runs. Relative paths resolve from the repository root, ~/... expands to your home directory, and PI_SUBAGENTS_WORKTREE_DIR is used when config is unset. The default remains the system temp directory.

worktreeSetupHook

{
  "worktreeSetupHook": "./scripts/setup-worktree.mjs",
  "worktreeSetupHookTimeoutMs": 45000
}

The hook runs once per created worktree. Paths must be absolute, ~/..., or repo-relative; bare command names are rejected.

stdin is a JSON object with repoRoot, worktreePath, agentCwd, branch, index, runId, and baseCommit. stdout must be one JSON object, for example:

{ "syntheticPaths": [".venv", ".env.local"] }

syntheticPaths must be relative to the worktree root. They are removed before diff capture so helper files do not pollute patches. Tracked files are never excluded; marking a tracked path as synthetic fails setup. Default timeout is 30000 ms.

completionBatch

{
  "completionBatch": {
    "enabled": true,
    "debounceMs": 150,
    "maxWaitMs": 1000,
    "stragglerDebounceMs": 75,
    "stragglerMaxWaitMs": 400,
    "stragglerWindowMs": 2000
  }
}

Controls smart batching of async-completion notifications. When several background subagents finish within a short window, their successful completions are held briefly and delivered as a single grouped message instead of separate notifications. A hard maxWaitMs cap (measured from the first completion in a group) guarantees nothing is held indefinitely, and late-finishing siblings that arrive within stragglerWindowMs of a group emit join a shorter straggler group governed by stragglerDebounceMs and stragglerMaxWaitMs.

Failed and paused completions bypass batching and fire immediately, flushing any held successes first, so failure and needs-attention signals are never delayed. Set enabled to false to restore the original one-notification-per-completion behavior. Changes apply on the next session start.

Files, logs, and observability

Each chain run creates a user-scoped temp directory like:

<tmpdir>/pi-subagents-<scope>/chain-runs/{runId}/

It may contain files such as context.md, plan.md, progress.md, and parallel-{stepIndex}/.../output.md. Directories older than 24 hours are cleaned up on extension startup.

Debug artifacts live under {sessionDir}/subagent-artifacts/, .pi-subagents/artifacts/ for project-scoped runs, or a user-scoped temp artifact directory. Single-run relative output files are saved under {artifactsDir}/outputs/{runId}/ unless singleRunOutputBaseDir is configured. Per task you may see:

• {runId}_{agent}_input.md
• {runId}_{agent}_output.md
• {runId}_{agent}.jsonl
• {runId}_{agent}_meta.json

Metadata records timing, usage, exit code, final model, attempted models, and fallback attempt outcomes.

Session files are stored under a per-run session directory. With context: "fork", each child starts with --session <branched-session-file> produced from the parent’s current leaf. That is a real session fork, not an injected summary.

Async completions notify only the originating session. The result watcher emits subagent:async-complete, and the extension consumes that event to render completion notifications. Successful sibling completions are held briefly and delivered as a single grouped message when they finish within a short window (see completionBatch); failed and paused completions always fire immediately.

Async runs write:

<tmpdir>/pi-subagents-<scope>/async-subagent-runs/<id>/
  status.json
  events.jsonl
  output-<n>.log
  subagent-log-<id>.md

status.json powers the widget and subagent({ action: "status" }) output. events.jsonl contains wrapper events plus child Pi JSON events annotated with run and step metadata, including subagent.steer.requested when live async steering is queued. Nested fanout status is stored as compact sidecar event/registry metadata and merged into parent status views and result/intercom payloads; full recursive status snapshots are not embedded in parent result files. output-<n>.log is a live human-readable tail. Fallback information is persisted so background runs are debuggable after completion.

Acceptance Gates

Every run resolves an effective acceptance policy. Callers may omit acceptance for the inferred default, or set it on single runs, top-level parallel task items, chain steps, static parallel tasks, and dynamic fanout templates.

{
  agent: "worker",
  task: "Implement the fix",
  acceptance: {
    level: "verified",
    criteria: ["Patch the bug without widening scope"],
    evidence: ["changed-files", "tests-added", "commands-run", "residual-risks", "no-staged-files"],
    verify: [{ id: "focused", command: "npm test", timeoutMs: 120000 }]
  }
}

Accepted levels are auto, none, attested, checked, verified, and reviewed. acceptance: "auto" is the default. Read-only reviewer/scout tasks infer lightweight attestation, normal writer tasks infer checked evidence, and async/risky/dynamic writer contexts infer a reviewed gate. To disable gates, prefer { level: "none", reason: "..." }.

Acceptance provenance is stored separately from child prose:

• claimed: child finished but did not provide structured evidence.
• attested: child returned a structured acceptance report.
• checked: runtime structural checks passed, such as required evidence and no staged files.
• verified: configured runtime verification commands passed. Child-reported command success does not count.
• reviewed: an independent reviewer result is present.
• rejected: attestation, structural checks, verification, or review failed.

For attested or stricter levels, the child prompt includes a standardized acceptance section and asks for a fenced acceptance-report JSON block. Explicit failed gates fail the run. Inferred gates are persisted for observability without breaking older calls that omit acceptance.

Live progress

Foreground runs show compact live progress for single, chain, and parallel modes: current tool, recent output, token counts, aggregate cost, duration, activity freshness, current-tool duration, and chain graph metadata when available.

Press Pi's configured expand key (Ctrl+O by default) to expand the full streaming view with complete output per step.

Sequential chains show a flow line like done scout → running planner. Chains with parallel steps show per-step cards instead. Chain status uses label and phase metadata when present, while falling back to agent names for older chains.

Session sharing

Pass share: true to export a full session to HTML, upload it to a secret GitHub Gist through your gh credentials, and return a https://shittycodingagent.ai/session/?<gistId> URL.

{ agent: "scout", task: "...", share: true }

This is disabled by default. Session data may contain source code, paths, environment variables, credentials, or other sensitive output. You need gh installed and authenticated.

Recursion guard

Subagents can call subagent only when their resolved builtin tools explicitly include subagent. That is meant for delegated fanout agents, not ordinary worker/reviewer children. A depth guard prevents unbounded nesting.

By default, nesting is limited to two levels: main session → subagent → sub-subagent. Deeper calls are blocked with guidance to complete the current task directly. Nested runs appear in the parent status widget and status output as a tree, and status, interrupt, and resume can target a nested run by its id.

Configure the limit with:

1. PI_SUBAGENT_MAX_DEPTH before starting Pi
2. config.maxSubagentDepth
3. maxSubagentDepth in agent frontmatter, which can only tighten the inherited limit

export PI_SUBAGENT_MAX_DEPTH=3
export PI_SUBAGENT_MAX_DEPTH=1
export PI_SUBAGENT_MAX_DEPTH=0

PI_SUBAGENT_DEPTH is internal and propagated automatically. Do not set it manually.

Events

Async events:

• subagent:async-started
• subagent:async-complete

Intercom delivery events:

• subagent:control-intercom
• subagent:result-intercom

The result watcher emits subagent:async-complete; src/extension/index.ts registers the notification handler that consumes it. Control/attention events are surfaced as visible parent notices and persisted for async runs. Native supervisor requests are delivered only to the exact parent session that spawned the child.

Prompt-template integration

pi-subagents works standalone through natural language, the subagent tool, slash commands, and the packaged prompt shortcuts listed near the top of this README. It also includes a native prompt-workflow adapter for reusable subagent prompt templates, so you do not need pi-prompt-template-model for the common subagent workflow path.

Create a prompt in .pi/prompts/ or ~/.pi/agent/prompts/:

---
description: Take a screenshot
model: claude-sonnet-4-20250514
subagent: browser-screenshoter
cwd: /tmp/screenshots
---
Use url in the prompt to take screenshot: $@

Then run it through the native adapter:

/prompt-workflow take-screenshot https://example.com

The adapter delegates to the named subagent, applies model, skill, cwd, worktree, and fork/fresh context metadata, and supports runtime overrides such as --subagent reviewer, --fork, --fresh, --worktree, and --bg.

For prompt-template chains, use:

/chain-prompts analyze -> fix -- user arguments here

Each named prompt becomes a native subagent chain step. This is intentionally scoped to subagent workflows; compare-style prompt features such as /best-of-n are not part of the built-in adapter.

Runtime files

The main runtime files are:

File	Purpose
src/extension/index.ts	Extension registration, tool registration, message/render wiring.
src/agents/agents.ts	Agent and chain discovery, frontmatter parsing.
src/runs/foreground/subagent-executor.ts	Main execution routing for single, parallel, chain, management, status, interrupt, and doctor actions.
src/runs/foreground/execution.ts	Core foreground runSync handling.
src/runs/background/subagent-runner.ts	Detached async runner.
src/runs/background/async-execution.ts	Background launch support.
src/runs/background/async-status.ts	Status discovery and formatting for async runs.
src/runs/foreground/chain-execution.ts / src/agents/chain-serializer.ts	Chain orchestration and .chain.md parsing.
src/shared/settings.ts	Chain behavior, instructions, and config helpers.
src/runs/shared/worktree.ts	Git worktree isolation.
src/intercom/intercom-bridge.ts	Runtime intercom bridge instructions and diagnostics.
src/extension/schemas.ts / src/shared/types.ts	Tool schemas, shared types, and event constants.
test/unit/ / test/integration/ / test/e2e/	Unit, loader-based integration, and real-session E2E tests.