add nexus, hyperloop, model-router extensions and update themeMap, justfile

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Azreen Jamal
2026-03-10 01:32:15 +08:00
parent bd2c7d5102
commit 9bc94b0bab
9 changed files with 2354 additions and 0 deletions
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/**
* Hyperloop — Context-preserving sub-agent orchestrator
*
* The main agent stays lightweight and interactive. Heavy work is delegated
* to background sub-agents that run in isolated Pi sessions, preserving
* the main chat's context window.
*
* Key design:
* 1. Main agent KEEPS all its tools (read, bash, edit, write) for quick inline work
* 2. Heavy/complex tasks are offloaded to sub-agents via tools
* 3. Sub-agents run asynchronously — main chat stays responsive
* 4. Results stream back as follow-up messages when ready
* 5. Auto-delegation: detects when a task should be offloaded (configurable)
* 6. Sub-agents have persistent sessions for multi-turn continuations
* 7. Live widget dashboard shows all running/completed agents
*
* Auto-delegation triggers:
* - "across all files", "entire codebase", "every file" → offload
* - Explicit multi-step plans with 5+ steps → offload
* - User says "background", "async", "offload" → offload
* - Main context > 70% full → suggest offloading
*
* Tools (available to LLM):
* hyperloop_spawn — Spawn a sub-agent with a task
* hyperloop_continue — Continue a finished sub-agent's conversation
* hyperloop_status — Check status of all sub-agents
* hyperloop_kill — Kill/remove a sub-agent
* hyperloop_collect — Collect results from finished sub-agents
*
* Commands:
* /hl — Dashboard: show all sub-agents
* /hl spawn <task> — Manually spawn a sub-agent
* /hl kill <id> — Kill a running sub-agent
* /hl clear — Clear all sub-agents
* /hl auto on|off — Toggle auto-delegation suggestions
* /hl mode <mode> — Set mode: interactive (default), delegator, hybrid
*
* Modes:
* interactive — Main agent does everything, spawns sub-agents only when asked
* delegator — Main agent primarily delegates, keeps minimal tools
* hybrid — Main agent handles simple tasks inline, auto-offloads complex ones
*
* Usage: pi -e extensions/hyperloop.ts
*/
import type { AssistantMessage } from "@mariozechner/pi-ai";
import type { ExtensionAPI, ExtensionContext, ToolCallEvent } from "@mariozechner/pi-coding-agent";
import { DynamicBorder } from "@mariozechner/pi-coding-agent";
import { Container, Text, truncateToWidth, visibleWidth, type AutocompleteItem } from "@mariozechner/pi-tui";
import { Type } from "@sinclair/typebox";
import { spawn as cpSpawn, type ChildProcess } from "child_process";
import { existsSync, mkdirSync, readdirSync, readFileSync, unlinkSync } from "fs";
import { basename, join } from "path";
import { applyExtensionDefaults } from "./themeMap.ts";
// ── Constants ──────────────────────────────────────────────────────────────
const AGENT_TIMEOUT_MS = 10 * 60 * 1000; // 10 min per sub-agent
const WIDGET_THROTTLE_MS = 400;
const CONTEXT_WARN_PCT = 70; // suggest offload above this
const MAX_RESULT_LENGTH = 12000; // truncate sub-agent results
// ── Types ──────────────────────────────────────────────────────────────────
type AgentMode = "interactive" | "delegator" | "hybrid";
type SubStatus = "queued" | "running" | "done" | "error" | "killed";
interface SubAgent {
id: number;
status: SubStatus;
task: string;
role: string; // "general", "scout", "builder", etc.
tools: string; // comma-separated tool list
textChunks: string[];
toolCount: number;
elapsed: number;
startTime: number;
sessionFile: string;
turnCount: number;
proc?: ChildProcess;
timer?: ReturnType<typeof setInterval>;
exitCode?: number;
// Context tracking
inputTokens: number;
outputTokens: number;
cost: number;
}
interface AgentDef {
name: string;
description: string;
tools: string;
systemPrompt: string;
}
// ── Agent Definitions (built-in roles) ─────────────────────────────────────
const BUILTIN_ROLES: AgentDef[] = [
{
name: "general",
description: "General-purpose coding agent",
tools: "read,bash,edit,write,grep,find,ls",
systemPrompt: "You are a focused coding agent. Complete the given task efficiently. Be thorough but concise in your output.",
},
{
name: "scout",
description: "Fast recon and codebase exploration (read-only)",
tools: "read,grep,find,ls",
systemPrompt: "You are a scout agent. Investigate the codebase quickly and report findings concisely. Do NOT modify any files. Focus on structure, patterns, and key entry points.",
},
{
name: "builder",
description: "Implementation and code generation",
tools: "read,write,edit,bash,grep,find,ls",
systemPrompt: "You are a builder agent. Implement the requested changes thoroughly. Write clean, minimal code. Follow existing patterns in the codebase. Test your work when possible.",
},
{
name: "reviewer",
description: "Code review and quality analysis (read-only)",
tools: "read,grep,find,ls",
systemPrompt: "You are a reviewer agent. Analyze code for bugs, security issues, performance problems, and style inconsistencies. Be specific about line numbers and suggest fixes.",
},
{
name: "tester",
description: "Test writing and execution",
tools: "read,write,edit,bash,grep,find,ls",
systemPrompt: "You are a testing agent. Write and run tests for the specified code. Cover edge cases. Use the project's existing test framework and patterns.",
},
];
// ── Auto-delegation patterns ───────────────────────────────────────────────
const OFFLOAD_PATTERNS = [
/\b(across|entire|whole|every|all)\s+(files?|codebase|project|modules?|components?)\b/i,
/\b(refactor|migrate|rewrite|overhaul)\s+(the\s+)?(entire|whole|full)\b/i,
/\b(search|find|grep)\s+(and\s+)?(replace|update|change)\s+(across|in all|everywhere)\b/i,
/\b(background|async|offload|delegate|spawn)\b/i,
/\bstep\s+[5-9]\b/i, // multi-step plan indicator
/\b(in parallel|simultaneously|concurrently)\b/i,
];
function shouldSuggestOffload(prompt: string): boolean {
return OFFLOAD_PATTERNS.some(p => p.test(prompt));
}
// ── Extension ──────────────────────────────────────────────────────────────
export default function hyperloop(pi: ExtensionAPI) {
const agents: Map<number, SubAgent> = new Map();
const activeProcesses: Set<ChildProcess> = new Set();
let nextId = 1;
let widgetCtx: any = null;
let mode: AgentMode = "hybrid";
let autoDelegate = true;
let sessionDir = "";
let customRoles: AgentDef[] = [];
// ── Widget Throttle ────────────────────────────────────────────────────
let widgetDirty = false;
let widgetTimer: ReturnType<typeof setTimeout> | null = null;
function scheduleWidget() {
widgetDirty = true;
if (widgetTimer) return;
widgetTimer = setTimeout(() => {
widgetTimer = null;
if (widgetDirty) {
widgetDirty = false;
renderWidget();
}
}, WIDGET_THROTTLE_MS);
}
function flushWidget() {
if (widgetTimer) {
clearTimeout(widgetTimer);
widgetTimer = null;
}
widgetDirty = false;
renderWidget();
}
// ── Load custom roles from .pi/agents/ ─────────────────────────────────
function loadCustomRoles(cwd: string) {
const dirs = [
join(cwd, ".pi", "agents"),
join(cwd, "agents"),
];
customRoles = [];
const seen = new Set(BUILTIN_ROLES.map(r => r.name));
for (const dir of dirs) {
if (!existsSync(dir)) continue;
try {
for (const file of readdirSync(dir)) {
if (!file.endsWith(".md")) continue;
const raw = readFileSync(join(dir, file), "utf-8");
const match = raw.match(/^---\n([\s\S]*?)\n---\n([\s\S]*)$/);
if (!match) continue;
const fm: Record<string, string> = {};
for (const line of match[1].split("\n")) {
const idx = line.indexOf(":");
if (idx > 0) fm[line.slice(0, idx).trim()] = line.slice(idx + 1).trim();
}
if (!fm.name || seen.has(fm.name)) continue;
seen.add(fm.name);
customRoles.push({
name: fm.name,
description: fm.description || "",
tools: fm.tools || "read,grep,find,ls",
systemPrompt: match[2].trim(),
});
}
} catch {}
}
}
function getAllRoles(): AgentDef[] {
return [...BUILTIN_ROLES, ...customRoles];
}
function findRole(name: string): AgentDef {
const all = getAllRoles();
return all.find(r => r.name.toLowerCase() === name.toLowerCase()) || BUILTIN_ROLES[0];
}
// ── Session File Management ────────────────────────────────────────────
function makeSessionFile(id: number): string {
if (!existsSync(sessionDir)) mkdirSync(sessionDir, { recursive: true });
return join(sessionDir, `hyperloop-${id}-${Date.now()}.jsonl`);
}
// ── Widget Rendering ───────────────────────────────────────────────────
function renderWidget() {
if (!widgetCtx) return;
if (agents.size === 0) {
widgetCtx.ui.setWidget("hyperloop", undefined);
return;
}
widgetCtx.ui.setWidget("hyperloop", (_tui: any, theme: any) => {
const container = new Container();
const content = new Text("", 0, 0);
container.addChild(content);
return {
render(width: number): string[] {
const lines: string[] = [];
const modeLabel = mode === "hybrid" ? "⚡ hybrid"
: mode === "delegator" ? "📡 delegator" : "💬 interactive";
lines.push(
theme.fg("dim", "─".repeat(width))
);
lines.push(
theme.fg("accent", " ◉ Hyperloop") +
theme.fg("dim", ` [${modeLabel}]`) +
theme.fg("dim", ` · ${agents.size} agent${agents.size !== 1 ? "s" : ""}`) +
(autoDelegate ? theme.fg("success", " · auto") : theme.fg("dim", " · manual"))
);
for (const [, agent] of agents) {
const statusIcon = agent.status === "queued" ? "◌"
: agent.status === "running" ? "●"
: agent.status === "done" ? "✓"
: agent.status === "killed" ? "⊘" : "✗";
const statusColor = agent.status === "running" ? "accent"
: agent.status === "done" ? "success"
: agent.status === "queued" ? "dim" : "error";
const elapsed = agent.status === "running"
? Math.round((Date.now() - agent.startTime) / 1000)
: Math.round(agent.elapsed / 1000);
const taskPreview = agent.task.length > 50
? agent.task.slice(0, 47) + "..."
: agent.task;
const turnLabel = agent.turnCount > 1 ? ` t${agent.turnCount}` : "";
// Main status line
lines.push(
theme.fg(statusColor, ` ${statusIcon} #${agent.id}`) +
theme.fg("dim", ` [${agent.role}${turnLabel}]`) +
theme.fg("dim", ` ${elapsed}s`) +
theme.fg("dim", ` · ${agent.toolCount} tools`) +
(agent.cost > 0 ? theme.fg("warning", ` · $${agent.cost.toFixed(4)}`) : "")
);
// Task description
lines.push(
theme.fg("muted", ` ${taskPreview}`)
);
// Live output (last line) for running agents
if (agent.status === "running" && agent.textChunks.length > 0) {
const fullText = agent.textChunks.join("");
const lastLine = fullText.split("\n").filter((l: string) => l.trim()).pop() || "";
if (lastLine) {
const trimmed = lastLine.length > width - 6
? lastLine.slice(0, width - 9) + "..."
: lastLine;
lines.push(theme.fg("dim", `${trimmed}`));
}
}
}
lines.push(theme.fg("dim", "─".repeat(width)));
content.setText(lines.join("\n"));
return container.render(width);
},
invalidate() { container.invalidate(); },
};
});
}
// ── Process JSON Stream from Sub-Agent ─────────────────────────────────
function processLine(agent: SubAgent, line: string) {
if (!line.trim()) return;
try {
const event = JSON.parse(line);
if (event.type === "message_update") {
const delta = event.assistantMessageEvent;
if (delta?.type === "text_delta") {
agent.textChunks.push(delta.delta || "");
scheduleWidget();
}
} else if (event.type === "tool_execution_start") {
agent.toolCount++;
scheduleWidget();
} else if (event.type === "message_end" || event.type === "agent_end") {
const msg = event.message || (event.messages || []).reverse().find((m: any) => m.role === "assistant");
if (msg?.usage) {
agent.inputTokens = msg.usage.input || 0;
agent.outputTokens = msg.usage.output || 0;
agent.cost = msg.usage.cost?.total || 0;
scheduleWidget();
}
}
} catch {}
}
// ── Spawn Sub-Agent Process ────────────────────────────────────────────
function spawnSubAgent(
agent: SubAgent,
prompt: string,
ctx: ExtensionContext,
isContinuation: boolean,
): Promise<{ output: string; exitCode: number }> {
agent.status = "running";
agent.startTime = Date.now();
scheduleWidget();
const role = findRole(agent.role);
// Use a cheaper model for sub-agents to save cost
const model = ctx.model
? `${ctx.model.provider}/${ctx.model.id}`
: "anthropic/claude-sonnet-4-6";
const args = [
"--mode", "json",
"-p",
"--no-extensions",
"--no-skills",
"--model", model,
"--tools", role.tools,
"--thinking", "low",
"--append-system-prompt", role.systemPrompt,
"--session", agent.sessionFile,
];
if (isContinuation) {
args.push("-c");
}
args.push(prompt);
return new Promise((resolve) => {
let resolved = false;
const safeResolve = (val: { output: string; exitCode: number }) => {
if (resolved) return;
resolved = true;
resolve(val);
};
const proc = cpSpawn("pi", args, {
stdio: ["ignore", "pipe", "pipe"],
env: { ...process.env },
});
agent.proc = proc;
activeProcesses.add(proc);
agent.timer = setInterval(() => {
agent.elapsed = Date.now() - agent.startTime;
scheduleWidget();
}, 1000);
const timeout = setTimeout(() => {
try { proc.kill("SIGTERM"); } catch {}
setTimeout(() => { try { proc.kill("SIGKILL"); } catch {} }, 3000);
}, AGENT_TIMEOUT_MS);
let buffer = "";
proc.stdout!.setEncoding("utf-8");
proc.stdout!.on("data", (chunk: string) => {
buffer += chunk;
const lines = buffer.split("\n");
buffer = lines.pop() || "";
for (const line of lines) processLine(agent, line);
});
proc.stderr!.setEncoding("utf-8");
proc.stderr!.on("data", () => {});
proc.on("close", (code) => {
clearTimeout(timeout);
activeProcesses.delete(proc);
agent.proc = undefined;
if (agent.timer) clearInterval(agent.timer);
agent.elapsed = Date.now() - agent.startTime;
agent.exitCode = code ?? 1;
if (buffer.trim()) processLine(agent, buffer);
const timedOut = agent.elapsed >= AGENT_TIMEOUT_MS;
agent.status = timedOut ? "error" : (code === 0 ? "done" : "error");
flushWidget();
const output = agent.textChunks.join("");
safeResolve({ output, exitCode: code ?? 1 });
});
proc.on("error", (err) => {
clearTimeout(timeout);
activeProcesses.delete(proc);
agent.proc = undefined;
if (agent.timer) clearInterval(agent.timer);
agent.status = "error";
flushWidget();
safeResolve({ output: `Error: ${err.message}`, exitCode: 1 });
});
});
}
// ── Fire-and-forget spawn (delivers result as follow-up) ───────────────
function spawnAndDeliver(agent: SubAgent, prompt: string, ctx: ExtensionContext, isContinuation: boolean) {
spawnSubAgent(agent, prompt, ctx, isContinuation).then(({ output, exitCode }) => {
const status = exitCode === 0 ? "✓ done" : "✗ error";
const elapsed = Math.round(agent.elapsed / 1000);
const turnLabel = agent.turnCount > 1 ? ` (Turn ${agent.turnCount})` : "";
const truncated = output.length > MAX_RESULT_LENGTH
? output.slice(0, MAX_RESULT_LENGTH) + "\n\n... [truncated — full output in sub-agent session]"
: output;
ctx.ui.notify(
`Sub-agent #${agent.id} [${agent.role}] ${status} in ${elapsed}s`,
exitCode === 0 ? "info" : "error",
);
pi.sendMessage({
customType: "hyperloop-result",
content: `**Sub-agent #${agent.id}** [${agent.role}]${turnLabel}${status} in ${elapsed}s | ${agent.toolCount} tool calls | $${agent.cost.toFixed(4)}\n\n${truncated}`,
display: "assistant",
}, { deliverAs: "followUp", triggerTurn: true });
});
}
// ── LLM Tools ──────────────────────────────────────────────────────────
pi.registerTool({
name: "hyperloop_spawn",
label: "Spawn Sub-Agent",
description: `Spawn a background sub-agent to execute a task without consuming main chat context. The sub-agent runs asynchronously — you can continue chatting while it works. Results are delivered automatically when finished.
Available roles: ${BUILTIN_ROLES.map(r => `${r.name} (${r.description})`).join(", ")}. Custom roles from .pi/agents/*.md are also available.
Use this for:
- Complex multi-file operations that would flood the context
- Long-running tasks (tests, builds, migrations)
- Parallel independent tasks (spawn multiple)
- When context usage is high and you need to preserve it`,
promptGuidelines: [
"Spawn sub-agents for heavy/multi-file work to preserve main context",
"Use role='scout' for exploration, 'builder' for implementation, 'reviewer' for code review, 'tester' for tests",
"You can spawn multiple sub-agents in parallel for independent tasks",
"Sub-agent results are delivered automatically — continue chatting while they work",
],
parameters: Type.Object({
task: Type.String({ description: "Complete task description. Be specific — the sub-agent has no context from this conversation." }),
role: Type.Optional(Type.String({ description: "Agent role: general, scout, builder, reviewer, tester, or custom role name. Default: general" })),
}),
async execute(_callId, params, _signal, onUpdate, ctx) {
widgetCtx = ctx;
const task = params.task;
const role = params.role || "general";
const id = nextId++;
const agent: SubAgent = {
id,
status: "queued",
task,
role,
tools: findRole(role).tools,
textChunks: [],
toolCount: 0,
elapsed: 0,
startTime: Date.now(),
sessionFile: makeSessionFile(id),
turnCount: 1,
inputTokens: 0,
outputTokens: 0,
cost: 0,
};
agents.set(id, agent);
if (onUpdate) {
onUpdate({
content: [{ type: "text", text: `Spawning sub-agent #${id} [${role}]...` }],
details: { id, role, task, status: "spawning" },
});
}
// Fire and forget — result delivered via sendMessage
spawnAndDeliver(agent, task, ctx, false);
return {
content: [{ type: "text", text: `Sub-agent #${id} [${role}] spawned and running in background. You'll receive results automatically when it finishes. Continue chatting normally.` }],
details: { id, role, task, status: "running" },
};
},
renderCall(args, theme) {
const role = (args as any).role || "general";
const task = (args as any).task || "";
const preview = task.length > 55 ? task.slice(0, 52) + "..." : task;
return new Text(
theme.fg("toolTitle", theme.bold("hyperloop_spawn ")) +
theme.fg("accent", `[${role}] `) +
theme.fg("muted", preview),
0, 0,
);
},
renderResult(result, options, theme) {
const d = result.details as any;
if (!d) return undefined;
if (options.isPartial || d.status === "spawning") {
return new Text(theme.fg("accent", `● #${d.id} [${d.role}]`) + theme.fg("dim", " spawning..."), 0, 0);
}
return new Text(
theme.fg("success", `◉ #${d.id}`) +
theme.fg("dim", ` [${d.role}] running in background`),
0, 0,
);
},
});
pi.registerTool({
name: "hyperloop_continue",
label: "Continue Sub-Agent",
description: "Continue a finished sub-agent's conversation with follow-up instructions. The sub-agent retains its full conversation history.",
parameters: Type.Object({
id: Type.Number({ description: "Sub-agent ID to continue" }),
prompt: Type.String({ description: "Follow-up instructions" }),
}),
async execute(_callId, params, _signal, _onUpdate, ctx) {
widgetCtx = ctx;
const agent = agents.get(params.id);
if (!agent) {
return { content: [{ type: "text", text: `No sub-agent #${params.id} found.` }] };
}
if (agent.status === "running") {
return { content: [{ type: "text", text: `Sub-agent #${params.id} is still running. Wait for it to finish.` }] };
}
agent.textChunks = [];
agent.toolCount = 0;
agent.elapsed = 0;
agent.turnCount++;
spawnAndDeliver(agent, params.prompt, ctx, true);
return {
content: [{ type: "text", text: `Sub-agent #${params.id} continuing (Turn ${agent.turnCount}). Results will be delivered when ready.` }],
};
},
});
pi.registerTool({
name: "hyperloop_status",
label: "Sub-Agent Status",
description: "Check status of all sub-agents.",
parameters: Type.Object({}),
async execute() {
if (agents.size === 0) {
return { content: [{ type: "text", text: "No sub-agents." }] };
}
const lines: string[] = [];
for (const [, a] of agents) {
const elapsed = a.status === "running"
? Math.round((Date.now() - a.startTime) / 1000)
: Math.round(a.elapsed / 1000);
const turnLabel = a.turnCount > 1 ? ` (Turn ${a.turnCount})` : "";
lines.push(
`#${a.id} [${a.role}${turnLabel}] ${a.status.toUpperCase()}${elapsed}s, ${a.toolCount} tools, $${a.cost.toFixed(4)}`,
` Task: ${a.task}`,
);
}
return { content: [{ type: "text", text: lines.join("\n") }] };
},
});
pi.registerTool({
name: "hyperloop_kill",
label: "Kill Sub-Agent",
description: "Kill a running sub-agent or remove a finished one.",
parameters: Type.Object({
id: Type.Number({ description: "Sub-agent ID" }),
}),
async execute(_callId, params) {
const agent = agents.get(params.id);
if (!agent) {
return { content: [{ type: "text", text: `No sub-agent #${params.id} found.` }] };
}
if (agent.proc && agent.status === "running") {
try { agent.proc.kill("SIGTERM"); } catch {}
agent.status = "killed";
}
if (agent.timer) clearInterval(agent.timer);
if (widgetCtx) widgetCtx.ui.setWidget(`sub-${params.id}`, undefined);
agents.delete(params.id);
flushWidget();
return { content: [{ type: "text", text: `Sub-agent #${params.id} removed.` }] };
},
});
pi.registerTool({
name: "hyperloop_collect",
label: "Collect Results",
description: "Collect and summarize results from all finished sub-agents. Useful after spawning multiple parallel agents.",
parameters: Type.Object({}),
async execute() {
const finished = Array.from(agents.values()).filter(a => a.status === "done" || a.status === "error");
if (finished.length === 0) {
const running = Array.from(agents.values()).filter(a => a.status === "running");
if (running.length > 0) {
return { content: [{ type: "text", text: `${running.length} sub-agent(s) still running. Wait for them to finish.` }] };
}
return { content: [{ type: "text", text: "No sub-agent results to collect." }] };
}
const parts: string[] = [];
let totalCost = 0;
for (const a of finished) {
const output = a.textChunks.join("");
const truncated = output.length > 6000
? output.slice(0, 6000) + "\n... [truncated]"
: output;
const status = a.status === "done" ? "✓" : "✗";
parts.push(`## ${status} Sub-agent #${a.id} [${a.role}] — ${Math.round(a.elapsed / 1000)}s\nTask: ${a.task}\n\n${truncated}`);
totalCost += a.cost;
}
return {
content: [{
type: "text",
text: `Collected ${finished.length} results (total cost: $${totalCost.toFixed(4)})\n\n${parts.join("\n\n---\n\n")}`,
}],
};
},
});
// ── Auto-Delegation (hybrid mode) ──────────────────────────────────────
pi.on("before_agent_start", async (event, ctx) => {
if (!autoDelegate || mode === "interactive") return;
// Check context pressure
const usage = ctx.getContextUsage();
if (usage && usage.percent && usage.percent > CONTEXT_WARN_PCT) {
ctx.ui.setStatus("hyperloop-warn", `⚠️ Context ${Math.round(usage.percent)}% — consider offloading heavy tasks`);
} else {
ctx.ui.setStatus("hyperloop-warn", undefined);
}
// In hybrid mode, nudge the system prompt to encourage delegation
if (mode === "hybrid" || mode === "delegator") {
const shouldOffload = shouldSuggestOffload(event.prompt);
const contextHigh = usage && usage.percent && usage.percent > CONTEXT_WARN_PCT;
if (shouldOffload || contextHigh) {
const roles = getAllRoles().map(r => `${r.name}: ${r.description}`).join("\n");
return {
systemPrompt: event.systemPrompt + `\n\n## Hyperloop Sub-Agent System
You have access to a sub-agent system (hyperloop_spawn, hyperloop_continue, hyperloop_status, hyperloop_kill, hyperloop_collect).
**The current task appears complex or context-heavy.** Consider spawning sub-agents for:
- Multi-file operations (use role="builder")
- Codebase exploration (use role="scout")
- Code review (use role="reviewer")
- Test writing (use role="tester")
- Any task that would generate lots of context
${contextHigh ? `⚠️ CONTEXT IS ${Math.round(usage!.percent!)}% FULL — strongly prefer sub-agents for any significant work.\n` : ""}
Available roles:\n${roles}
Sub-agents run in background. You can spawn multiple in parallel. Results auto-deliver as follow-up messages. Keep your main responses concise.`,
};
}
}
});
// ── /hl Command ────────────────────────────────────────────────────────
pi.registerCommand("hl", {
description: "Hyperloop controls: /hl [spawn|kill|clear|auto|mode]",
getArgumentCompletions: (prefix: string): AutocompleteItem[] | null => {
const items = [
{ value: "spawn ", label: "spawn <task> — Spawn a sub-agent" },
{ value: "kill ", label: "kill <id> — Kill a sub-agent" },
{ value: "clear", label: "clear — Remove all sub-agents" },
{ value: "auto on", label: "auto on — Enable auto-delegation" },
{ value: "auto off", label: "auto off — Disable auto-delegation" },
{ value: "mode interactive", label: "mode interactive — Manual only" },
{ value: "mode hybrid", label: "mode hybrid — Smart auto-offload" },
{ value: "mode delegator", label: "mode delegator — Prefer delegation" },
];
return items.filter(i => i.value.startsWith(prefix));
},
async handler(args, ctx) {
widgetCtx = ctx;
const parts = (args || "").trim().split(/\s+/);
const sub = parts[0]?.toLowerCase();
if (!sub || sub === "status") {
// Show dashboard
const modeLabel = mode === "hybrid" ? "⚡ hybrid" : mode === "delegator" ? "📡 delegator" : "💬 interactive";
const autoLabel = autoDelegate ? "on" : "off";
const agentList = agents.size === 0
? " No sub-agents"
: Array.from(agents.values()).map(a => {
const elapsed = a.status === "running"
? Math.round((Date.now() - a.startTime) / 1000)
: Math.round(a.elapsed / 1000);
return ` #${a.id} [${a.role}] ${a.status}${elapsed}s, ${a.toolCount} tools, $${a.cost.toFixed(4)}\n ${a.task}`;
}).join("\n");
const usage = ctx.getContextUsage();
const pct = usage?.percent ? Math.round(usage.percent) : "?";
pi.sendMessage({
customType: "hyperloop-dashboard",
content: `\n◉ Hyperloop Dashboard\n Mode: ${modeLabel} | Auto: ${autoLabel} | Context: ${pct}%\n Agents: ${agents.size}\n\n${agentList}\n\n Commands: /hl spawn|kill|clear|auto|mode`,
display: "assistant",
});
return;
}
if (sub === "spawn") {
const task = parts.slice(1).join(" ").trim();
if (!task) {
ctx.ui.notify("Usage: /hl spawn <task>", "error");
return;
}
const id = nextId++;
const agent: SubAgent = {
id,
status: "queued",
task,
role: "general",
tools: BUILTIN_ROLES[0].tools,
textChunks: [],
toolCount: 0,
elapsed: 0,
startTime: Date.now(),
sessionFile: makeSessionFile(id),
turnCount: 1,
inputTokens: 0,
outputTokens: 0,
cost: 0,
};
agents.set(id, agent);
spawnAndDeliver(agent, task, ctx, false);
ctx.ui.notify(`Sub-agent #${id} spawned`, "info");
return;
}
if (sub === "kill") {
const id = parseInt(parts[1], 10);
if (isNaN(id)) {
ctx.ui.notify("Usage: /hl kill <id>", "error");
return;
}
const agent = agents.get(id);
if (!agent) {
ctx.ui.notify(`No sub-agent #${id}`, "error");
return;
}
if (agent.proc) try { agent.proc.kill("SIGTERM"); } catch {}
if (agent.timer) clearInterval(agent.timer);
agents.delete(id);
flushWidget();
ctx.ui.notify(`Sub-agent #${id} killed`, "info");
return;
}
if (sub === "clear") {
for (const [, a] of agents) {
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
}
agents.clear();
nextId = 1;
flushWidget();
ctx.ui.notify("All sub-agents cleared", "info");
return;
}
if (sub === "auto") {
const val = parts[1]?.toLowerCase();
if (val === "on") { autoDelegate = true; ctx.ui.notify("Auto-delegation ON", "info"); }
else if (val === "off") { autoDelegate = false; ctx.ui.notify("Auto-delegation OFF", "info"); }
else ctx.ui.notify("Usage: /hl auto on|off", "error");
return;
}
if (sub === "mode") {
const val = parts[1]?.toLowerCase() as AgentMode;
if (["interactive", "delegator", "hybrid"].includes(val)) {
mode = val;
ctx.ui.notify(`Mode: ${val}`, "info");
flushWidget();
} else {
ctx.ui.notify("Usage: /hl mode interactive|hybrid|delegator", "error");
}
return;
}
ctx.ui.notify("Unknown command. Try: /hl spawn|kill|clear|auto|mode", "error");
},
});
// ── Session Lifecycle ──────────────────────────────────────────────────
pi.on("session_start", async (_event, ctx) => {
applyExtensionDefaults(import.meta.url, ctx);
widgetCtx = ctx;
sessionDir = join(ctx.cwd, ".pi", "agent-sessions", "hyperloop");
loadCustomRoles(ctx.cwd);
// Clean up any previous agents
for (const [, a] of agents) {
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
}
agents.clear();
nextId = 1;
// Footer
ctx.ui.setFooter((_tui, theme, footerData) => {
const unsub = footerData.onBranchChange(() => _tui.requestRender());
return {
dispose: unsub,
invalidate() {},
render(width: number): string[] {
const model = ctx.model?.id || "no-model";
const usage = ctx.getContextUsage();
const pct = usage?.percent ?? 0;
const filled = Math.round(pct / 10) || 1;
const bar = "#".repeat(filled) + "-".repeat(10 - filled);
const running = Array.from(agents.values()).filter(a => a.status === "running").length;
const total = agents.size;
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
let tokIn = 0, tokOut = 0, cost = 0;
for (const entry of ctx.sessionManager.getBranch()) {
if (entry.type === "message" && entry.message.role === "assistant") {
const m = entry.message as AssistantMessage;
tokIn += m.usage.input;
tokOut += m.usage.output;
cost += m.usage.cost.total;
}
}
// Add sub-agent costs
for (const [, a] of agents) cost += a.cost;
const fmt = (n: number) => n < 1000 ? `${n}` : `${(n / 1000).toFixed(1)}k`;
const l1Left =
theme.fg("dim", ` ${model} `) +
theme.fg("warning", "[") +
theme.fg("success", "#".repeat(filled)) +
theme.fg("dim", "-".repeat(10 - filled)) +
theme.fg("warning", "]") +
theme.fg("dim", " ") +
theme.fg("accent", `${Math.round(pct)}%`);
const l1Right =
theme.fg("success", `${fmt(tokIn)}`) +
theme.fg("dim", " in ") +
theme.fg("accent", `${fmt(tokOut)}`) +
theme.fg("dim", " out ") +
theme.fg("warning", `$${cost.toFixed(4)}`) +
theme.fg("dim", " ");
const pad1 = " ".repeat(Math.max(1, width - visibleWidth(l1Left) - visibleWidth(l1Right)));
const line1 = truncateToWidth(l1Left + pad1 + l1Right, width, "");
const dir = basename(ctx.cwd);
const branch = footerData.getGitBranch();
const l2Left =
theme.fg("dim", ` ${dir}`) +
(branch ? theme.fg("dim", " ") + theme.fg("warning", "(") + theme.fg("success", branch) + theme.fg("warning", ")") : "") +
theme.fg("dim", ` · ${modeIcon} ${mode}`);
const agentStatus = total > 0
? (running > 0
? theme.fg("accent", `${running} running`) + theme.fg("dim", ` / ${total} total `)
: theme.fg("dim", `${total} agents `))
: theme.fg("dim", "no agents ");
const pad2 = " ".repeat(Math.max(1, width - visibleWidth(l2Left) - visibleWidth(agentStatus)));
const line2 = truncateToWidth(l2Left + pad2 + agentStatus, width, "");
return [line1, line2];
},
};
});
const roles = getAllRoles().map(r => r.name).join(", ");
ctx.ui.notify(
`◉ Hyperloop active [${mode} mode]\n` +
`Roles: ${roles}\n` +
`/hl — Dashboard & controls`,
"info",
);
});
// ── Cleanup ────────────────────────────────────────────────────────────
function killAll() {
for (const proc of activeProcesses) {
try { proc.kill("SIGTERM"); } catch {}
}
setTimeout(() => {
for (const proc of activeProcesses) {
try { proc.kill("SIGKILL"); } catch {}
}
}, 3000);
}
pi.on("session_shutdown", async () => { killAll(); });
process.on("exit", killAll);
process.on("SIGINT", () => { killAll(); process.exit(0); });
process.on("SIGTERM", () => { killAll(); process.exit(0); });
}
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/**
* Model Router — LLM-powered automatic model selection
*
* Uses Haiku (~200ms, ~$0.001/call) to classify every prompt's complexity,
* then routes to the optimal model + thinking level. No regex guessing.
*
* Tiers:
* ⚡ Haiku — Simple Q&A, file reads, small edits, quick lookups
* ⚖️ Sonnet — Code generation, debugging, refactoring, multi-file work
* 🧠 Opus — Architecture, complex reasoning, large-scale changes
*
* Mid-turn escalation:
* - 4+ edits/writes → escalate to Opus
* - 2+ consecutive errors → escalate (model struggling)
* - 6+ tool calls in one turn → escalate to at least Sonnet
*
* Usage: pi -e extensions/model-router.ts
*
* Commands:
* /router — Show routing state & stats
* /router lock — Lock current model (disable auto-routing)
* /router unlock — Re-enable auto-routing
* /router tier <n> — Force tier: 1=haiku, 2=sonnet, 3=opus
*/
import type { AssistantMessage } from "@mariozechner/pi-ai";
import { complete } from "@mariozechner/pi-ai";
import type { ExtensionAPI, ExtensionContext } from "@mariozechner/pi-coding-agent";
import { truncateToWidth, visibleWidth } from "@mariozechner/pi-tui";
import { basename } from "node:path";
import { applyExtensionDefaults } from "./themeMap.ts";
// ── Model Tiers ────────────────────────────────────────────────────────────
interface ModelTier {
name: string;
icon: string;
provider: string;
modelId: string;
thinking: "off" | "low" | "medium" | "high";
inputCost: number;
outputCost: number;
}
const TIERS: ModelTier[] = [
{ name: "Haiku", icon: "⚡", provider: "anthropic", modelId: "claude-haiku-4-5", thinking: "off", inputCost: 0.80, outputCost: 4.00 },
{ name: "Sonnet", icon: "⚖️", provider: "anthropic", modelId: "claude-sonnet-4-6", thinking: "low", inputCost: 3.00, outputCost: 15.00 },
{ name: "Opus", icon: "🧠", provider: "anthropic", modelId: "claude-opus-4-6", thinking: "high", inputCost: 15.00, outputCost: 75.00 },
];
// ── LLM Classifier ────────────────────────────────────────────────────────
const CLASSIFIER_PROMPT = `You are a task complexity classifier for a coding assistant. Given a user prompt, respond with ONLY a JSON object (no markdown, no explanation):
{"tier": <1|2|3>, "reason": "<5 words max>"}
TIER 1 (simple): Quick questions, yes/no, read/list/check files, small edits, conversational ("thanks", "ok"), simple lookups.
TIER 2 (medium): Write functions/classes, fix bugs, refactor single files, write tests, create endpoints, docker/CI config.
TIER 3 (complex): Architecture design, multi-file refactoring/migration, security audits, performance optimization, complex algorithms, system design from scratch.`;
interface Classification { tier: number; reason: string }
const cache = new Map<string, { result: Classification; ts: number }>();
const CACHE_TTL = 60_000;
async function classify(prompt: string, ctx: ExtensionContext): Promise<Classification> {
const key = prompt.trim().toLowerCase().slice(0, 200);
const c = cache.get(key);
if (c && Date.now() - c.ts < CACHE_TTL) return c.result;
const model = ctx.modelRegistry.find("anthropic", "claude-haiku-4-5");
if (!model) return { tier: 2, reason: "no classifier" };
const apiKey = await ctx.modelRegistry.getApiKey(model);
if (!apiKey) return { tier: 2, reason: "no key" };
try {
const resp = await complete(model, {
systemPrompt: CLASSIFIER_PROMPT,
messages: [{ role: "user" as const, content: prompt, timestamp: Date.now() }],
}, { reasoning: "off" });
const text = resp.content
.filter((c): c is { type: "text"; text: string } => c.type === "text")
.map(c => c.text).join("");
const json = text.replace(/```json?\n?/g, "").replace(/```/g, "").trim();
const parsed = JSON.parse(json);
const result: Classification = {
tier: Math.max(1, Math.min(3, parsed.tier || 2)),
reason: String(parsed.reason || "classified").slice(0, 50),
};
cache.set(key, { result, ts: Date.now() });
return result;
} catch {
return { tier: 2, reason: "classify failed" };
}
}
// ── Router State ───────────────────────────────────────────────────────────
interface RouterState {
currentTier: number;
locked: boolean;
totalSwitches: number;
turnsSinceLast: number;
consecutiveErrors: number;
toolCallsThisTurn: number;
editWriteThisTurn: number;
totalToolCalls: number;
totalErrors: number;
tierHistory: Array<{ tier: number; reason: string; turn: number }>;
turnCount: number;
savedVsAlwaysOpus: number;
classifierCost: number;
}
// ── Extension ──────────────────────────────────────────────────────────────
export default function modelRouter(pi: ExtensionAPI) {
const state: RouterState = {
currentTier: 1,
locked: false,
totalSwitches: 0,
turnsSinceLast: 0,
consecutiveErrors: 0,
toolCallsThisTurn: 0,
editWriteThisTurn: 0,
totalToolCalls: 0,
totalErrors: 0,
tierHistory: [],
turnCount: 0,
savedVsAlwaysOpus: 0,
classifierCost: 0,
};
async function switchToTier(tierIndex: number, reason: string, ctx?: ExtensionContext) {
const clamped = Math.max(0, Math.min(2, tierIndex));
if (clamped === state.currentTier) return;
const tier = TIERS[clamped];
const model = ctx?.modelRegistry.find(tier.provider, tier.modelId);
if (!model) return;
const success = await pi.setModel(model);
if (!success) return;
pi.setThinkingLevel(tier.thinking);
const prev = state.currentTier;
state.currentTier = clamped;
state.totalSwitches++;
state.turnsSinceLast = 0;
state.tierHistory.push({
tier: clamped,
reason: `${TIERS[prev].icon}${tier.icon} ${reason}`,
turn: state.turnCount,
});
}
// ── LLM Classification on every prompt ─────────────────────────────────
pi.on("before_agent_start", async (event, ctx) => {
if (state.locked) return;
ctx.ui.setWorkingMessage("classifying...");
const result = await classify(event.prompt, ctx);
ctx.ui.setWorkingMessage();
// Track classifier cost (~180 tokens per call at Haiku rates)
state.classifierCost += (150 * 0.80 + 30 * 4.00) / 1_000_000;
let target = result.tier - 1; // 1-3 → 0-2
// Context-aware overrides
if (target === 0 && state.totalToolCalls > 10) target = 1;
if (state.consecutiveErrors >= 2 && target < 2) target = Math.min(target + 1, 2);
if (target !== state.currentTier) {
await switchToTier(target, result.reason, ctx);
}
});
// ── Turn & Tool Tracking ───────────────────────────────────────────────
pi.on("turn_start", async () => {
state.toolCallsThisTurn = 0;
state.editWriteThisTurn = 0;
state.turnCount++;
state.turnsSinceLast++;
});
pi.on("tool_execution_start", async (event) => {
state.toolCallsThisTurn++;
state.totalToolCalls++;
if (event.toolName === "edit" || event.toolName === "write") state.editWriteThisTurn++;
});
pi.on("tool_execution_end", async (event, ctx) => {
if (event.isError) {
state.consecutiveErrors++;
state.totalErrors++;
if (state.consecutiveErrors >= 2 && !state.locked && state.currentTier < 2) {
await switchToTier(state.currentTier + 1, `${state.consecutiveErrors} errors`, ctx);
}
} else {
state.consecutiveErrors = 0;
}
});
pi.on("turn_end", async (_event, ctx) => {
if (!state.locked) {
if (state.editWriteThisTurn >= 4 && state.currentTier < 2) {
await switchToTier(2, `heavy: ${state.editWriteThisTurn} edits`, ctx);
} else if (state.toolCallsThisTurn >= 6 && state.currentTier < 1) {
await switchToTier(1, `busy: ${state.toolCallsThisTurn} tools`, ctx);
}
}
const opusCost = (2000 * TIERS[2].inputCost + 1000 * TIERS[2].outputCost) / 1e6;
const actualCost = (2000 * TIERS[state.currentTier].inputCost + 1000 * TIERS[state.currentTier].outputCost) / 1e6;
state.savedVsAlwaysOpus += opusCost - actualCost;
});
// ── Session Start ──────────────────────────────────────────────────────
pi.on("session_start", async (_event, ctx) => {
applyExtensionDefaults(import.meta.url, ctx);
const initialTier = TIERS[1];
const model = ctx.modelRegistry.find(initialTier.provider, initialTier.modelId);
if (model) {
await pi.setModel(model);
pi.setThinkingLevel(initialTier.thinking);
}
ctx.ui.setFooter((tui, theme, footerData) => {
const unsub = footerData.onBranchChange(() => tui.requestRender());
return {
dispose: unsub,
invalidate() {},
render(width: number): string[] {
const tier = TIERS[state.currentTier];
const lockIcon = state.locked ? " 🔒" : "";
let tokIn = 0, tokOut = 0, cost = 0;
for (const entry of ctx.sessionManager.getBranch()) {
if (entry.type === "message" && entry.message.role === "assistant") {
const m = entry.message as AssistantMessage;
tokIn += m.usage.input;
tokOut += m.usage.output;
cost += m.usage.cost.total;
}
}
cost += state.classifierCost;
const fmt = (n: number) => n < 1000 ? `${n}` : `${(n / 1000).toFixed(1)}k`;
const usage = ctx.getContextUsage();
const pct = usage?.percent ?? 0;
const filled = Math.round(pct / 10) || 1;
const l1Left =
theme.fg("dim", " ") +
theme.fg("accent", `${tier.icon} ${tier.name}`) +
theme.fg("dim", ` [${tier.thinking}]${lockIcon} `) +
theme.fg("warning", "[") +
theme.fg("success", "#".repeat(filled)) +
theme.fg("dim", "-".repeat(10 - filled)) +
theme.fg("warning", "]") +
theme.fg("dim", " ") +
theme.fg("accent", `${Math.round(pct)}%`);
const l1Right =
theme.fg("success", `${fmt(tokIn)}`) +
theme.fg("dim", " in ") +
theme.fg("accent", `${fmt(tokOut)}`) +
theme.fg("dim", " out ") +
theme.fg("warning", `$${cost.toFixed(4)}`) +
theme.fg("dim", " ");
const pad1 = " ".repeat(Math.max(1, width - visibleWidth(l1Left) - visibleWidth(l1Right)));
const line1 = truncateToWidth(l1Left + pad1 + l1Right, width, "");
const dir = basename(ctx.cwd);
const branch = footerData.getGitBranch();
const lastReason = state.tierHistory.length > 0
? state.tierHistory[state.tierHistory.length - 1].reason
: "start: balanced";
const l2Left =
theme.fg("dim", ` ${dir}`) +
(branch ? theme.fg("dim", " ") + theme.fg("warning", "(") + theme.fg("success", branch) + theme.fg("warning", ")") : "") +
theme.fg("dim", " · ") +
theme.fg("accent", `${state.totalSwitches}`) +
theme.fg("dim", " switches") +
(state.savedVsAlwaysOpus > 0 ? theme.fg("dim", " · saved ") + theme.fg("success", `$${state.savedVsAlwaysOpus.toFixed(4)}`) : "");
const l2Right = theme.fg("dim", truncateToWidth(lastReason, Math.floor(width * 0.4), "…") + " ");
const pad2 = " ".repeat(Math.max(1, width - visibleWidth(l2Left) - visibleWidth(l2Right)));
const line2 = truncateToWidth(l2Left + pad2 + l2Right, width, "");
return [line1, line2];
},
};
});
ctx.ui.notify(
`Model Router active — LLM-powered (Haiku classifier)\n` +
`Start: ${TIERS[1].icon} ${TIERS[1].name} · Auto-routes per prompt\n` +
`/router — Status & controls`,
"info",
);
});
// ── /router Command ────────────────────────────────────────────────────
pi.registerCommand("router", {
description: "Model router status & controls. Usage: /router [lock|unlock|tier 1|2|3]",
async handler(args: string, ctx) {
const parts = args.trim().split(/\s+/);
const sub = parts[0]?.toLowerCase();
if (sub === "lock") { state.locked = true; ctx.ui.notify("🔒 Locked", "info"); return; }
if (sub === "unlock") { state.locked = false; ctx.ui.notify("🔓 Unlocked", "info"); return; }
if (sub === "tier") {
const n = parseInt(parts[1], 10);
if (n >= 1 && n <= 3) {
await switchToTier(n - 1, `manual /router tier ${n}`, ctx);
ctx.ui.notify(`${TIERS[n - 1].icon} ${TIERS[n - 1].name}`, "info");
return;
}
ctx.ui.notify("Usage: /router tier 1|2|3", "warning"); return;
}
const tier = TIERS[state.currentTier];
const history = state.tierHistory.length > 0
? state.tierHistory.slice(-5).map(h => ` Turn ${h.turn}: ${h.reason}`).join("\n")
: " (none)";
pi.sendMessage({
customType: "router-status",
content: [
``,
` ┌─── Model Router (LLM-powered) ───┐`,
` │ Current: ${tier.icon} ${tier.name.padEnd(22)}`,
` │ Thinking: ${tier.thinking.padEnd(21)}`,
` │ Locked: ${(state.locked ? "yes 🔒" : "no").padEnd(23)}`,
` │ Switches: ${String(state.totalSwitches).padEnd(21)}`,
` │ Turns: ${String(state.turnCount).padEnd(23)}`,
` │ Tool calls: ${String(state.totalToolCalls).padEnd(18)}`,
` │ Errors: ${String(state.totalErrors).padEnd(22)}`,
` │ Saved vs Opus: $${state.savedVsAlwaysOpus.toFixed(4).padEnd(14)}`,
` │ Classifier cost: $${state.classifierCost.toFixed(4).padEnd(12)}`,
` └────────────────────────────────────┘`,
``,
` Recent routing:`,
history,
``,
` /router lock | unlock | tier 1|2|3`,
``,
].join("\n"),
display: "assistant",
});
},
});
}
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/**
* Nexus — The unified Pi intelligence layer
*
* Combines model routing + sub-agent orchestration into one seamless system.
* The main agent stays fast and interactive. Complex work is automatically
* offloaded to sub-agents. The model auto-adapts to task complexity.
*
* Model routing uses a REAL LLM call (Haiku, ~200ms) to classify task
* complexity — no brittle regex patterns. The classifier returns a tier
* (1-3) and whether to offload to a sub-agent.
*
* Features:
* ✦ LLM-powered task classification (Haiku as router brain)
* ✦ Auto model routing (Haiku → Sonnet → Opus based on classification)
* ✦ Sub-agent spawning for heavy work (preserves main context)
* ✦ Auto-delegation when classifier says to offload
* ✦ Context pressure monitoring (warns & suggests offload at 70%+)
* ✦ Mid-turn escalation on errors/heavy tool usage
* ✦ Live dashboard widget showing all agents
* ✦ Cost tracking across main + sub-agents
* ✦ Persistent sub-agent sessions for multi-turn continuations
*
* Usage:
* pi -e extensions/nexus.ts
* alias pn='pi -e extensions/nexus.ts'
*
* Commands:
* /nx — Full dashboard
* /nx spawn <task> — Manual sub-agent spawn
* /nx kill <id> — Kill sub-agent
* /nx clear — Clear all sub-agents
* /nx mode <m> — interactive | hybrid | delegator
* /nx auto on|off — Toggle auto-delegation
* /nx lock — Lock model (disable auto-routing)
* /nx unlock — Unlock model
* /nx tier 1|2|3 — Force model tier
*/
import type { AssistantMessage as AssistantMsg } from "@mariozechner/pi-ai";
import { complete, getModel } from "@mariozechner/pi-ai";
import type { ExtensionAPI, ExtensionContext } from "@mariozechner/pi-coding-agent";
import { DynamicBorder } from "@mariozechner/pi-coding-agent";
import { Container, Text, truncateToWidth, visibleWidth, type AutocompleteItem } from "@mariozechner/pi-tui";
import { Type } from "@sinclair/typebox";
import { spawn as cpSpawn, type ChildProcess } from "child_process";
import { existsSync, mkdirSync, readdirSync, readFileSync } from "fs";
import { basename, join } from "path";
import { applyExtensionDefaults } from "./themeMap.ts";
// ══════════════════════════════════════════════════════════════════════════
// CONSTANTS
// ══════════════════════════════════════════════════════════════════════════
const AGENT_TIMEOUT_MS = 10 * 60 * 1000;
const WIDGET_THROTTLE_MS = 400;
const CONTEXT_WARN_PCT = 70;
const MAX_RESULT_LEN = 12000;
// ══════════════════════════════════════════════════════════════════════════
// MODEL TIERS
// ══════════════════════════════════════════════════════════════════════════
interface Tier {
name: string;
icon: string;
provider: string;
modelId: string;
thinking: "off" | "low" | "medium" | "high";
inputCost: number;
outputCost: number;
}
const TIERS: Tier[] = [
{ name: "Haiku", icon: "⚡", provider: "anthropic", modelId: "claude-haiku-4-5", thinking: "off", inputCost: 0.80, outputCost: 4.00 },
{ name: "Sonnet", icon: "⚖️", provider: "anthropic", modelId: "claude-sonnet-4-6", thinking: "low", inputCost: 3.00, outputCost: 15.00 },
{ name: "Opus", icon: "🧠", provider: "anthropic", modelId: "claude-opus-4-6", thinking: "high", inputCost: 15.00, outputCost: 75.00 },
];
// ══════════════════════════════════════════════════════════════════════════
// LLM-POWERED TASK CLASSIFIER
// ══════════════════════════════════════════════════════════════════════════
const CLASSIFIER_SYSTEM_PROMPT = `You are a task complexity classifier for a coding assistant. Given a user prompt, respond with ONLY a JSON object (no markdown, no explanation):
{"tier": <1|2|3>, "thinking": "<off|low|medium|high>", "offload": <true|false>, "reason": "<brief reason>"}
Classification rules:
TIER 1 (simple — use cheapest model):
- Quick questions, yes/no answers, explanations
- Reading/viewing files, checking status, listing things
- Small single-line edits, formatting, renaming
- Conversational responses (thanks, ok, etc.)
- Simple lookups or searches
TIER 2 (medium — use balanced model):
- Writing new functions, classes, or components
- Debugging, fixing bugs, error resolution
- Refactoring single files
- Writing tests for specific code
- Database queries, API endpoint creation
- Docker/CI configuration changes
TIER 3 (complex — use most powerful model):
- Architecture design, system planning
- Multi-file refactoring or migrations
- Security audits, performance optimization
- Complex algorithmic problems
- Designing new systems from scratch
- Tasks requiring deep reasoning or trade-off analysis
THINKING LEVEL (extended reasoning budget — set independently of tier):
- "off" → Simple/conversational. No benefit from reasoning.
- "low" → Moderate task. Light reasoning helpful (most Tier 2).
- "medium" → Tricky bug, subtle logic, multi-step plan (upper Tier 2 / lower Tier 3).
- "high" → Architecture, security audit, complex algorithm, deep trade-offs (Tier 3).
Rule of thumb: Tier 1 → "off". Tier 2 → "low" or "medium". Tier 3 → "medium" or "high".
Only use "high" when extended chain-of-thought would meaningfully improve correctness.
OFFLOAD (spawn sub-agent instead of inline):
- Set true when the task would generate lots of context (multi-file changes, codebase-wide operations)
- Set true when the task is independent and can run in background
- Set true when "across all files", "entire codebase", parallel work is mentioned
- Set false for conversational, quick, or interactive tasks
- Set false when user needs immediate back-and-forth
Be concise. The "reason" should be under 10 words.`;
interface ClassificationResult {
tier: number;
thinking: "off" | "low" | "medium" | "high";
offload: boolean;
reason: string;
}
// Cache recent classifications to avoid duplicate calls
const classificationCache = new Map<string, { result: ClassificationResult; timestamp: number }>();
const CACHE_TTL_MS = 60_000; // 1 minute
async function classifyWithLLM(
prompt: string,
ctx: ExtensionContext,
contextPercent: number | null,
): Promise<ClassificationResult> {
// Check cache (normalize by trimming + lowercasing)
const cacheKey = prompt.trim().toLowerCase().slice(0, 200);
const cached = classificationCache.get(cacheKey);
if (cached && Date.now() - cached.timestamp < CACHE_TTL_MS) {
return cached.result;
}
// Use Haiku for classification — fast and cheap (~0.001 cents per classification)
const classifier = ctx.modelRegistry.find("anthropic", "claude-haiku-4-5");
if (!classifier) {
// Fallback: simple heuristic if Haiku unavailable
return { tier: 2, thinking: "low", offload: false, reason: "classifier unavailable" };
}
const apiKey = await ctx.modelRegistry.getApiKey(classifier);
if (!apiKey) {
return { tier: 2, thinking: "low", offload: false, reason: "no API key" };
}
// Build context message with additional signals
let userMsg = prompt;
if (contextPercent !== null && contextPercent > CONTEXT_WARN_PCT) {
userMsg += `\n\n[SYSTEM NOTE: Main context is at ${Math.round(contextPercent)}% capacity. Prefer offload=true for heavy tasks.]`;
}
try {
const response = await complete(classifier, {
systemPrompt: CLASSIFIER_SYSTEM_PROMPT,
messages: [{
role: "user" as const,
content: userMsg,
timestamp: Date.now(),
}],
}, {
reasoning: "off",
});
// Extract text from response
const text = response.content
.filter((c): c is { type: "text"; text: string } => c.type === "text")
.map(c => c.text)
.join("");
// Parse JSON from response (handle potential markdown wrapping)
const jsonStr = text.replace(/```json?\n?/g, "").replace(/```/g, "").trim();
const parsed = JSON.parse(jsonStr);
const validThinking = ["off", "low", "medium", "high"];
const result: ClassificationResult = {
tier: Math.max(1, Math.min(3, parsed.tier || 2)),
thinking: validThinking.includes(parsed.thinking) ? parsed.thinking : "low",
offload: Boolean(parsed.offload),
reason: String(parsed.reason || "classified").slice(0, 50),
};
// Cache it
classificationCache.set(cacheKey, { result, timestamp: Date.now() });
return result;
} catch (err: any) {
// On any failure, default to Sonnet, no offload
return { tier: 2, thinking: "low", offload: false, reason: `classify error: ${err?.message?.slice(0, 30)}` };
}
}
// ══════════════════════════════════════════════════════════════════════════
// SUB-AGENT TYPES
// ══════════════════════════════════════════════════════════════════════════
type AgentMode = "interactive" | "delegator" | "hybrid";
type SubStatus = "queued" | "running" | "done" | "error" | "killed";
interface SubAgent {
id: number;
status: SubStatus;
task: string;
role: string;
tools: string;
textChunks: string[];
toolCount: number;
elapsed: number;
startTime: number;
sessionFile: string;
turnCount: number;
proc?: ChildProcess;
timer?: ReturnType<typeof setInterval>;
inputTokens: number;
outputTokens: number;
cost: number;
}
interface RoleDef {
name: string;
description: string;
tools: string;
systemPrompt: string;
}
const ROLES: RoleDef[] = [
{ name: "general", description: "General-purpose coding agent", tools: "read,bash,edit,write,grep,find,ls", systemPrompt: "You are a focused coding agent. Complete the given task efficiently. Be thorough but concise." },
{ name: "scout", description: "Fast recon (read-only)", tools: "read,grep,find,ls", systemPrompt: "You are a scout. Investigate the codebase quickly and report findings. Do NOT modify files." },
{ name: "builder", description: "Implementation & code generation", tools: "read,write,edit,bash,grep,find,ls", systemPrompt: "You are a builder. Implement changes thoroughly. Clean, minimal code. Follow existing patterns." },
{ name: "reviewer", description: "Code review (read-only)", tools: "read,grep,find,ls", systemPrompt: "You are a reviewer. Analyze code for bugs, security, performance, style. Be specific about line numbers." },
{ name: "tester", description: "Test writing & execution", tools: "read,write,edit,bash,grep,find,ls", systemPrompt: "You are a tester. Write and run tests. Cover edge cases. Use the project's existing test framework." },
];
// ══════════════════════════════════════════════════════════════════════════
// EXTENSION
// ══════════════════════════════════════════════════════════════════════════
export default function nexus(pi: ExtensionAPI) {
// ── Router State ───────────────────────────────────────────────────────
let currentTier = 1;
let lastThinking: "off" | "low" | "medium" | "high" = "low";
let tierLocked = false;
let totalSwitches = 0;
let turnsSinceSwitch = 0;
let consecutiveErrors = 0;
let totalToolCalls = 0;
let editWriteThisTurn = 0;
let toolsThisTurn = 0;
let turnCount = 0;
let savedVsOpus = 0;
let classifierCost = 0; // Track cost of Haiku classifier calls
const tierHistory: Array<{ tier: number; reason: string; turn: number }> = [];
// ── Agent State ────────────────────────────────────────────────────────
const agents: Map<number, SubAgent> = new Map();
const activeProcs: Set<ChildProcess> = new Set();
let nextId = 1;
let widgetCtx: ExtensionContext | null = null;
let mode: AgentMode = "hybrid";
let autoDelegate = true;
let sessionDir = "";
let customRoles: RoleDef[] = [];
// ── Widget throttle ────────────────────────────────────────────────────
let wDirty = false;
let wTimer: ReturnType<typeof setTimeout> | null = null;
function scheduleWidget() {
wDirty = true;
if (wTimer) return;
wTimer = setTimeout(() => { wTimer = null; if (wDirty) { wDirty = false; renderWidget(); } }, WIDGET_THROTTLE_MS);
}
function flushWidget() {
if (wTimer) { clearTimeout(wTimer); wTimer = null; }
wDirty = false;
renderWidget();
}
// ── Helpers ────────────────────────────────────────────────────────────
function getAllRoles(): RoleDef[] { return [...ROLES, ...customRoles]; }
function findRole(name: string): RoleDef {
return getAllRoles().find(r => r.name.toLowerCase() === name.toLowerCase()) || ROLES[0];
}
function makeSessionFile(id: number): string {
if (!existsSync(sessionDir)) mkdirSync(sessionDir, { recursive: true });
return join(sessionDir, `nexus-${id}-${Date.now()}.jsonl`);
}
function loadCustomRoles(cwd: string) {
customRoles = [];
const seen = new Set(ROLES.map(r => r.name));
for (const dir of [join(cwd, ".pi", "agents"), join(cwd, "agents")]) {
if (!existsSync(dir)) continue;
try {
for (const file of readdirSync(dir)) {
if (!file.endsWith(".md")) continue;
const raw = readFileSync(join(dir, file), "utf-8");
const m = raw.match(/^---\n([\s\S]*?)\n---\n([\s\S]*)$/);
if (!m) continue;
const fm: Record<string, string> = {};
for (const line of m[1].split("\n")) {
const i = line.indexOf(":");
if (i > 0) fm[line.slice(0, i).trim()] = line.slice(i + 1).trim();
}
if (!fm.name || seen.has(fm.name)) continue;
seen.add(fm.name);
customRoles.push({ name: fm.name, description: fm.description || "", tools: fm.tools || "read,grep,find,ls", systemPrompt: m[2].trim() });
}
} catch {}
}
}
// ── Model Switching ────────────────────────────────────────────────────
async function switchTier(target: number, reason: string, ctx?: ExtensionContext, thinkingOverride?: "off" | "low" | "medium" | "high") {
const t = Math.max(0, Math.min(2, target));
const tier = TIERS[t];
const model = ctx?.modelRegistry.find(tier.provider, tier.modelId);
if (!model) return;
const thinking = thinkingOverride ?? tier.thinking;
const tierChanged = t !== currentTier;
const thinkingChanged = thinking !== lastThinking;
if (!tierChanged && !thinkingChanged) return;
if (tierChanged) {
const ok = await pi.setModel(model);
if (!ok) return;
}
pi.setThinkingLevel(thinking);
lastThinking = thinking;
const prev = currentTier;
currentTier = t;
if (tierChanged) totalSwitches++;
turnsSinceSwitch = 0;
const thinkTag = thinkingOverride ? ` 🧠${thinking}` : "";
tierHistory.push({ tier: t, reason: `${TIERS[prev].icon}${tier.icon} ${reason}${thinkTag}`, turn: turnCount });
}
// ── Widget Rendering ───────────────────────────────────────────────────
function renderWidget() {
if (!widgetCtx) return;
if (agents.size === 0) {
widgetCtx.ui.setWidget("nexus-agents", undefined);
return;
}
widgetCtx.ui.setWidget("nexus-agents", (_tui: any, theme: any) => {
const container = new Container();
const content = new Text("", 0, 0);
container.addChild(content);
return {
render(width: number): string[] {
const lines: string[] = [];
const tier = TIERS[currentTier];
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
lines.push(theme.fg("dim", "─".repeat(width)));
lines.push(
theme.fg("accent", ` ✦ Nexus`) +
theme.fg("dim", ` ${tier.icon} ${tier.name} · ${modeIcon} ${mode} · `) +
theme.fg("accent", `${agents.size}`) +
theme.fg("dim", " agents")
);
for (const [, a] of agents) {
const icon = a.status === "running" ? "●" : a.status === "done" ? "✓" : a.status === "queued" ? "◌" : "✗";
const color = a.status === "running" ? "accent" : a.status === "done" ? "success" : a.status === "queued" ? "dim" : "error";
const elapsed = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
const task = a.task.length > 50 ? a.task.slice(0, 47) + "..." : a.task;
const turn = a.turnCount > 1 ? ` t${a.turnCount}` : "";
lines.push(
theme.fg(color, ` ${icon} #${a.id}`) +
theme.fg("dim", ` [${a.role}${turn}] ${elapsed}s · ${a.toolCount} tools`) +
(a.cost > 0 ? theme.fg("warning", ` $${a.cost.toFixed(4)}`) : "")
);
lines.push(theme.fg("muted", ` ${task}`));
if (a.status === "running" && a.textChunks.length > 0) {
const last = a.textChunks.join("").split("\n").filter((l: string) => l.trim()).pop() || "";
if (last) lines.push(theme.fg("dim", `${last.slice(0, width - 8)}`));
}
}
lines.push(theme.fg("dim", "─".repeat(width)));
content.setText(lines.join("\n"));
return container.render(width);
},
invalidate() { container.invalidate(); },
};
});
}
// ── Sub-Agent Process ──────────────────────────────────────────────────
function processLine(a: SubAgent, line: string) {
if (!line.trim()) return;
try {
const e = JSON.parse(line);
if (e.type === "message_update" && e.assistantMessageEvent?.type === "text_delta") {
a.textChunks.push(e.assistantMessageEvent.delta || "");
scheduleWidget();
} else if (e.type === "tool_execution_start") {
a.toolCount++;
scheduleWidget();
} else if (e.type === "message_end" || e.type === "agent_end") {
const msg = e.message || (e.messages || []).reverse().find((m: any) => m.role === "assistant");
if (msg?.usage) {
a.inputTokens = msg.usage.input || 0;
a.outputTokens = msg.usage.output || 0;
a.cost = msg.usage.cost?.total || 0;
scheduleWidget();
}
}
} catch {}
}
function spawnProcess(a: SubAgent, prompt: string, ctx: ExtensionContext, isCont: boolean): Promise<{ output: string; exitCode: number }> {
a.status = "running";
a.startTime = Date.now();
scheduleWidget();
const role = findRole(a.role);
// Sub-agents use Sonnet for balanced cost/performance
const model = "anthropic/claude-sonnet-4-6";
const args = [
"--mode", "json", "-p", "--no-extensions", "--no-skills",
"--model", model, "--tools", role.tools, "--thinking", "low",
"--append-system-prompt", role.systemPrompt,
"--session", a.sessionFile,
];
if (isCont) args.push("-c");
args.push(prompt);
return new Promise(resolve => {
let done = false;
const fin = (val: { output: string; exitCode: number }) => { if (!done) { done = true; resolve(val); } };
const proc = cpSpawn("pi", args, { stdio: ["ignore", "pipe", "pipe"], env: { ...process.env } });
a.proc = proc;
activeProcs.add(proc);
a.timer = setInterval(() => { a.elapsed = Date.now() - a.startTime; scheduleWidget(); }, 1000);
const timeout = setTimeout(() => {
try { proc.kill("SIGTERM"); } catch {}
setTimeout(() => { try { proc.kill("SIGKILL"); } catch {} }, 3000);
}, AGENT_TIMEOUT_MS);
let buf = "";
proc.stdout!.setEncoding("utf-8");
proc.stdout!.on("data", (chunk: string) => {
buf += chunk;
const lines = buf.split("\n");
buf = lines.pop() || "";
for (const l of lines) processLine(a, l);
});
proc.stderr!.setEncoding("utf-8");
proc.stderr!.on("data", () => {});
proc.on("close", code => {
clearTimeout(timeout);
activeProcs.delete(proc);
a.proc = undefined;
if (a.timer) clearInterval(a.timer);
a.elapsed = Date.now() - a.startTime;
if (buf.trim()) processLine(a, buf);
a.status = a.elapsed >= AGENT_TIMEOUT_MS ? "error" : (code === 0 ? "done" : "error");
flushWidget();
fin({ output: a.textChunks.join(""), exitCode: code ?? 1 });
});
proc.on("error", err => {
clearTimeout(timeout);
activeProcs.delete(proc);
a.proc = undefined;
if (a.timer) clearInterval(a.timer);
a.status = "error";
flushWidget();
fin({ output: `Error: ${err.message}`, exitCode: 1 });
});
});
}
function spawnAndDeliver(a: SubAgent, prompt: string, ctx: ExtensionContext, isCont: boolean) {
spawnProcess(a, prompt, ctx, isCont).then(({ output, exitCode }) => {
const status = exitCode === 0 ? "✓" : "✗";
const elapsed = Math.round(a.elapsed / 1000);
const turn = a.turnCount > 1 ? ` (Turn ${a.turnCount})` : "";
const truncated = output.length > MAX_RESULT_LEN ? output.slice(0, MAX_RESULT_LEN) + "\n\n... [truncated]" : output;
ctx.ui.notify(`#${a.id} [${a.role}] ${status} ${elapsed}s`, exitCode === 0 ? "info" : "error");
pi.sendMessage({
customType: "nexus-result",
content: `**Sub-agent #${a.id}** [${a.role}]${turn}${status} ${elapsed}s | ${a.toolCount} tools | $${a.cost.toFixed(4)}\n\n${truncated}`,
display: "assistant",
}, { deliverAs: "followUp", triggerTurn: true });
});
}
// ── LLM Tools ──────────────────────────────────────────────────────────
const roleList = ROLES.map(r => `${r.name} (${r.description})`).join(", ");
pi.registerTool({
name: "nexus_spawn",
label: "Spawn Sub-Agent",
description: `Spawn a background sub-agent for heavy tasks. Preserves main chat context. Results auto-deliver when done.\n\nRoles: ${roleList}. Custom roles from .pi/agents/*.md also available.`,
promptGuidelines: [
"Spawn sub-agents for multi-file, long-running, or context-heavy work",
"Use role='scout' for exploration, 'builder' for code, 'reviewer' for review, 'tester' for tests",
"Spawn multiple agents in parallel for independent tasks",
"Continue chatting while sub-agents work — results arrive automatically",
],
parameters: Type.Object({
task: Type.String({ description: "Complete task description — sub-agent has no context from this conversation" }),
role: Type.Optional(Type.String({ description: "Agent role. Default: general" })),
}),
async execute(_id, params, _sig, onUpdate, ctx) {
widgetCtx = ctx;
const id = nextId++;
const a: SubAgent = {
id, status: "queued", task: params.task, role: params.role || "general",
tools: findRole(params.role || "general").tools, textChunks: [], toolCount: 0,
elapsed: 0, startTime: Date.now(), sessionFile: makeSessionFile(id),
turnCount: 1, inputTokens: 0, outputTokens: 0, cost: 0,
};
agents.set(id, a);
if (onUpdate) onUpdate({ content: [{ type: "text", text: `Spawning #${id} [${a.role}]...` }], details: { id, role: a.role } });
spawnAndDeliver(a, params.task, ctx, false);
return { content: [{ type: "text", text: `Sub-agent #${id} [${a.role}] running in background. Continue chatting.` }], details: { id, role: a.role } };
},
renderCall(args, theme) {
const r = (args as any).role || "general";
const t = ((args as any).task || "").slice(0, 55);
return new Text(theme.fg("toolTitle", theme.bold("nexus_spawn ")) + theme.fg("accent", `[${r}] `) + theme.fg("muted", t), 0, 0);
},
renderResult(result, opts, theme) {
const d = result.details as any;
if (!d) return undefined;
return new Text(theme.fg("success", `◉ #${d.id}`) + theme.fg("dim", ` [${d.role}] background`), 0, 0);
},
});
pi.registerTool({
name: "nexus_continue",
label: "Continue Sub-Agent",
description: "Continue a finished sub-agent's conversation with follow-up instructions.",
parameters: Type.Object({
id: Type.Number({ description: "Sub-agent ID" }),
prompt: Type.String({ description: "Follow-up instructions" }),
}),
async execute(_cid, params, _sig, _upd, ctx) {
widgetCtx = ctx;
const a = agents.get(params.id);
if (!a) return { content: [{ type: "text", text: `No #${params.id} found.` }] };
if (a.status === "running") return { content: [{ type: "text", text: `#${params.id} still running.` }] };
a.textChunks = []; a.toolCount = 0; a.elapsed = 0; a.turnCount++;
spawnAndDeliver(a, params.prompt, ctx, true);
return { content: [{ type: "text", text: `#${params.id} continuing (Turn ${a.turnCount}).` }] };
},
});
pi.registerTool({
name: "nexus_status",
label: "Agent Status",
description: "Check all sub-agents.",
parameters: Type.Object({}),
async execute() {
if (agents.size === 0) return { content: [{ type: "text", text: "No sub-agents." }] };
const lines = Array.from(agents.values()).map(a => {
const e = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
return `#${a.id} [${a.role}] ${a.status}${e}s, ${a.toolCount} tools, $${a.cost.toFixed(4)}\n ${a.task}`;
});
return { content: [{ type: "text", text: lines.join("\n") }] };
},
});
pi.registerTool({
name: "nexus_kill",
label: "Kill Sub-Agent",
description: "Kill/remove a sub-agent.",
parameters: Type.Object({ id: Type.Number() }),
async execute(_cid, params) {
const a = agents.get(params.id);
if (!a) return { content: [{ type: "text", text: `No #${params.id}.` }] };
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
agents.delete(params.id);
flushWidget();
return { content: [{ type: "text", text: `#${params.id} removed.` }] };
},
});
pi.registerTool({
name: "nexus_collect",
label: "Collect Results",
description: "Collect results from all finished sub-agents.",
parameters: Type.Object({}),
async execute() {
const done = Array.from(agents.values()).filter(a => a.status === "done" || a.status === "error");
if (done.length === 0) return { content: [{ type: "text", text: "No results to collect." }] };
let totalCost = 0;
const parts = done.map(a => {
const out = a.textChunks.join("");
const trunc = out.length > 6000 ? out.slice(0, 6000) + "\n... [truncated]" : out;
totalCost += a.cost;
return `## ${a.status === "done" ? "✓" : "✗"} #${a.id} [${a.role}] ${Math.round(a.elapsed / 1000)}s\n${a.task}\n\n${trunc}`;
});
return { content: [{ type: "text", text: `${done.length} results ($${totalCost.toFixed(4)})\n\n${parts.join("\n\n---\n\n")}` }] };
},
});
// ══════════════════════════════════════════════════════════════════════
// CORE ROUTING LOGIC — LLM-POWERED
// ══════════════════════════════════════════════════════════════════════
pi.on("before_agent_start", async (event, ctx) => {
widgetCtx = ctx;
const usage = ctx.getContextUsage();
const contextPct = usage?.percent ?? null;
// ── Step 1: LLM Classification ─────────────────────────────────────
let classification: ClassificationResult | null = null;
if (!tierLocked || (autoDelegate && mode !== "interactive")) {
ctx.ui.setWorkingMessage("classifying task...");
classification = await classifyWithLLM(event.prompt, ctx, contextPct);
ctx.ui.setWorkingMessage(); // restore default
// Track classifier cost (Haiku: ~150 input + ~30 output tokens per call)
classifierCost += (150 * 0.80 + 30 * 4.00) / 1_000_000;
}
// ── Step 2: Model Routing ──────────────────────────────────────────
if (!tierLocked && classification) {
let target = classification.tier - 1; // Convert 1-3 to 0-2
let thinking = classification.thinking;
// Context-aware adjustments
// If we've been doing heavy tool work, don't drop to Haiku
if (target === 0 && totalToolCalls > 10) target = 1;
// Error escalation override
if (consecutiveErrors >= 2 && target < 2) {
target = Math.min(target + 1, 2);
if (thinking === "off" || thinking === "low") thinking = "medium";
}
// Context pressure: bump tier if context is getting full
if (contextPct !== null && contextPct > 80 && target < 1) {
target = 1; // At least Sonnet when context is pressured
}
await switchTier(target, classification.reason, ctx, thinking);
}
// ── Step 3: Auto-Delegation ────────────────────────────────────────
if (classification?.offload && autoDelegate && (mode === "hybrid" || mode === "delegator")) {
// Context pressure warning
if (contextPct !== null && contextPct > CONTEXT_WARN_PCT) {
ctx.ui.setStatus("nexus-ctx", `⚠️ Context ${Math.round(contextPct)}%`);
} else {
ctx.ui.setStatus("nexus-ctx", undefined);
}
const roles = getAllRoles().map(r => `${r.name}: ${r.description}`).join("\n");
const contextWarn = (contextPct !== null && contextPct > CONTEXT_WARN_PCT)
? `\n⚠️ CONTEXT AT ${Math.round(contextPct)}% — strongly prefer sub-agents for this work.\n`
: "";
return {
systemPrompt: event.systemPrompt + `\n\n## Nexus: Sub-Agent Delegation Recommended
The task classifier determined this task should be **offloaded to a sub-agent** (reason: "${classification.reason}").
You have these tools: nexus_spawn, nexus_continue, nexus_status, nexus_kill, nexus_collect.
${contextWarn}
**Strongly prefer spawning a sub-agent** for this task rather than doing it inline. This preserves the main chat context for continued interaction.
Available roles:\n${roles}
Sub-agents run in background with their own context. You can spawn multiple for parallel work. Results auto-deliver. Keep your main response brief — explain what you're delegating and why.`,
};
} else {
ctx.ui.setStatus("nexus-ctx", undefined);
}
});
// ── Turn & Tool Tracking (mid-conversation escalation) ─────────────────
pi.on("turn_start", async () => {
toolsThisTurn = 0;
editWriteThisTurn = 0;
turnCount++;
turnsSinceSwitch++;
});
pi.on("tool_execution_start", async (event) => {
toolsThisTurn++;
totalToolCalls++;
if (event.toolName === "edit" || event.toolName === "write") editWriteThisTurn++;
});
pi.on("tool_execution_end", async (event, ctx) => {
if (event.isError) {
consecutiveErrors++;
// Mid-turn escalation on repeated errors
if (consecutiveErrors >= 2 && !tierLocked && currentTier < 2) {
await switchTier(currentTier + 1, `${consecutiveErrors} consecutive errors`, ctx);
}
} else {
consecutiveErrors = 0;
}
});
pi.on("turn_end", async (_event, ctx) => {
if (!tierLocked) {
// Escalate on heavy tool usage
if (editWriteThisTurn >= 4 && currentTier < 2) {
await switchTier(2, `heavy: ${editWriteThisTurn} edits/writes`, ctx);
} else if (toolsThisTurn >= 6 && currentTier < 1) {
await switchTier(1, `busy: ${toolsThisTurn} tool calls`, ctx);
}
// De-escalate after quiet period (but only if classifier agrees next time)
// We just track turns since switch — the classifier handles de-escalation naturally
}
// Cost savings estimate
const opusCost = (2000 * TIERS[2].inputCost + 1000 * TIERS[2].outputCost) / 1e6;
const actualCost = (2000 * TIERS[currentTier].inputCost + 1000 * TIERS[currentTier].outputCost) / 1e6;
savedVsOpus += opusCost - actualCost;
});
// ── /nx Command ────────────────────────────────────────────────────────
pi.registerCommand("nx", {
description: "Nexus controls: /nx [spawn|kill|clear|mode|auto|lock|unlock|tier]",
getArgumentCompletions: (prefix: string): AutocompleteItem[] | null => {
const items = [
{ value: "spawn ", label: "spawn <task>" },
{ value: "kill ", label: "kill <id>" },
{ value: "clear", label: "clear all agents" },
{ value: "mode hybrid", label: "mode hybrid" },
{ value: "mode interactive", label: "mode interactive" },
{ value: "mode delegator", label: "mode delegator" },
{ value: "auto on", label: "auto on" },
{ value: "auto off", label: "auto off" },
{ value: "lock", label: "lock model" },
{ value: "unlock", label: "unlock model" },
{ value: "tier ", label: "tier 1|2|3" },
];
return items.filter(i => i.value.startsWith(prefix));
},
async handler(args, ctx) {
widgetCtx = ctx;
const parts = (args || "").trim().split(/\s+/);
const sub = parts[0]?.toLowerCase();
if (!sub) {
const tier = TIERS[currentTier];
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
const usage = ctx.getContextUsage();
const pct = usage?.percent ? Math.round(usage.percent) : "?";
const agentLines = agents.size === 0 ? " (none)" : Array.from(agents.values()).map(a => {
const e = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
return ` #${a.id} [${a.role}] ${a.status} ${e}s $${a.cost.toFixed(4)}${a.task.slice(0, 50)}`;
}).join("\n");
const lastRoute = tierHistory.length > 0
? tierHistory.slice(-3).map(h => ` Turn ${h.turn}: ${h.reason}`).join("\n")
: " (none yet)";
pi.sendMessage({
customType: "nexus-dashboard",
content: [
``,
`✦ Nexus Dashboard`,
` Model: ${tier.icon} ${tier.name} [${lastThinking}]${tierLocked ? " 🔒" : ""}`,
` Mode: ${modeIcon} ${mode} | Auto: ${autoDelegate ? "on" : "off"} | Context: ${pct}%`,
` Switches: ${totalSwitches} | Saved: $${savedVsOpus.toFixed(4)} | Classifier: $${classifierCost.toFixed(4)}`,
``,
` Sub-Agents (${agents.size}):`,
agentLines,
``,
` Recent Routing:`,
lastRoute,
``,
` /nx spawn|kill|clear|mode|auto|lock|unlock|tier`,
``,
].join("\n"),
display: "assistant",
});
return;
}
if (sub === "spawn") {
const task = parts.slice(1).join(" ").trim();
if (!task) { ctx.ui.notify("Usage: /nx spawn <task>", "error"); return; }
const id = nextId++;
const a: SubAgent = { id, status: "queued", task, role: "general", tools: ROLES[0].tools, textChunks: [], toolCount: 0, elapsed: 0, startTime: Date.now(), sessionFile: makeSessionFile(id), turnCount: 1, inputTokens: 0, outputTokens: 0, cost: 0 };
agents.set(id, a);
spawnAndDeliver(a, task, ctx, false);
ctx.ui.notify(`#${id} spawned`, "info");
} else if (sub === "kill") {
const id = parseInt(parts[1], 10);
const a = agents.get(id);
if (!a) { ctx.ui.notify(`No #${id}`, "error"); return; }
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
agents.delete(id);
flushWidget();
ctx.ui.notify(`#${id} killed`, "info");
} else if (sub === "clear") {
for (const [, a] of agents) {
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
}
agents.clear();
nextId = 1;
flushWidget();
ctx.ui.notify("Cleared", "info");
} else if (sub === "mode") {
const v = parts[1]?.toLowerCase() as AgentMode;
if (["interactive", "hybrid", "delegator"].includes(v)) { mode = v; ctx.ui.notify(`Mode: ${v}`, "info"); }
else ctx.ui.notify("Usage: /nx mode interactive|hybrid|delegator", "error");
} else if (sub === "auto") {
if (parts[1] === "on") { autoDelegate = true; ctx.ui.notify("Auto ON", "info"); }
else if (parts[1] === "off") { autoDelegate = false; ctx.ui.notify("Auto OFF", "info"); }
else ctx.ui.notify("Usage: /nx auto on|off", "error");
} else if (sub === "lock") {
tierLocked = true; ctx.ui.notify("🔒 Model locked", "info");
} else if (sub === "unlock") {
tierLocked = false; ctx.ui.notify("🔓 Model unlocked", "info");
} else if (sub === "tier") {
const n = parseInt(parts[1], 10);
if (n >= 1 && n <= 3) {
await switchTier(n - 1, `manual /nx tier ${n}`, ctx);
ctx.ui.notify(`${TIERS[n - 1].icon} ${TIERS[n - 1].name}`, "info");
} else ctx.ui.notify("Usage: /nx tier 1|2|3", "error");
} else {
ctx.ui.notify("Unknown. Try: /nx spawn|kill|clear|mode|auto|lock|unlock|tier", "error");
}
},
});
// ── Session Start ──────────────────────────────────────────────────────
pi.on("session_start", async (_event, ctx) => {
applyExtensionDefaults(import.meta.url, ctx);
widgetCtx = ctx;
sessionDir = join(ctx.cwd, ".pi", "agent-sessions", "nexus");
loadCustomRoles(ctx.cwd);
// Cleanup previous
for (const [, a] of agents) {
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
if (a.timer) clearInterval(a.timer);
}
agents.clear();
nextId = 1;
// Set initial model (Sonnet = balanced start)
const init = TIERS[1];
const model = ctx.modelRegistry.find(init.provider, init.modelId);
if (model) {
await pi.setModel(model);
pi.setThinkingLevel(init.thinking);
}
currentTier = 1;
// Footer
ctx.ui.setFooter((_tui, theme, footerData) => {
const unsub = footerData.onBranchChange(() => _tui.requestRender());
return {
dispose: unsub,
invalidate() {},
render(width: number): string[] {
const tier = TIERS[currentTier];
const lockStr = tierLocked ? " 🔒" : "";
const usage = ctx.getContextUsage();
const pct = usage?.percent ?? 0;
const filled = Math.round(pct / 10) || 1;
let tokIn = 0, tokOut = 0, cost = 0;
for (const entry of ctx.sessionManager.getBranch()) {
if (entry.type === "message" && entry.message.role === "assistant") {
const m = entry.message as AssistantMsg;
tokIn += m.usage.input;
tokOut += m.usage.output;
cost += m.usage.cost.total;
}
}
// Add sub-agent costs + classifier cost
for (const [, a] of agents) cost += a.cost;
cost += classifierCost;
const fmt = (n: number) => n < 1000 ? `${n}` : `${(n / 1000).toFixed(1)}k`;
const l1L = theme.fg("dim", " ") + theme.fg("accent", `${tier.icon} ${tier.name}`) +
theme.fg("dim", ` [${lastThinking}]${lockStr} `) +
theme.fg("warning", "[") + theme.fg("success", "#".repeat(filled)) +
theme.fg("dim", "-".repeat(10 - filled)) + theme.fg("warning", "]") +
theme.fg("dim", " ") + theme.fg("accent", `${Math.round(pct)}%`);
const l1R = theme.fg("success", fmt(tokIn)) + theme.fg("dim", " in ") +
theme.fg("accent", fmt(tokOut)) + theme.fg("dim", " out ") +
theme.fg("warning", `$${cost.toFixed(4)} `);
const p1 = " ".repeat(Math.max(1, width - visibleWidth(l1L) - visibleWidth(l1R)));
const dir = basename(ctx.cwd);
const branch = footerData.getGitBranch();
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
const running = Array.from(agents.values()).filter(a => a.status === "running").length;
const l2L = theme.fg("dim", ` ${dir}`) +
(branch ? theme.fg("dim", " ") + theme.fg("warning", "(") + theme.fg("success", branch) + theme.fg("warning", ")") : "") +
theme.fg("dim", ` · ${modeIcon} ${mode}`);
const l2R = (running > 0 ? theme.fg("accent", `${running} running `) : "") +
(agents.size > 0 ? theme.fg("dim", `${agents.size} agents `) : "") +
(savedVsOpus > 0 ? theme.fg("success", `saved $${savedVsOpus.toFixed(3)} `) : "");
const p2 = " ".repeat(Math.max(1, width - visibleWidth(l2L) - visibleWidth(l2R)));
return [
truncateToWidth(l1L + p1 + l1R, width, ""),
truncateToWidth(l2L + p2 + l2R, width, ""),
];
},
};
});
const roles = getAllRoles().map(r => r.name).join(", ");
ctx.ui.notify(
`✦ Nexus active [${mode}] — LLM-powered routing\n` +
`Model: ${TIERS[1].icon} ${TIERS[1].name} (Haiku classifies → auto-routes)\n` +
`Roles: ${roles}\n` +
`/nx — Dashboard & controls`,
"info",
);
});
// ── Cleanup ────────────────────────────────────────────────────────────
function killAll() {
for (const p of activeProcs) try { p.kill("SIGTERM"); } catch {}
setTimeout(() => { for (const p of activeProcs) try { p.kill("SIGKILL"); } catch {} }, 3000);
}
pi.on("session_shutdown", async () => killAll());
process.on("exit", killAll);
process.on("SIGINT", () => { killAll(); process.exit(0); });
process.on("SIGTERM", () => { killAll(); process.exit(0); });
}
+3
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@@ -39,6 +39,9 @@ export const THEME_MAP: Record<string, string> = {
"tool-counter": "synthwave", // techy metrics
"tool-counter-widget":"synthwave", // same family
"easymode": "catppuccin-mocha", // soft, welcoming for beginners
"model-router": "cyberpunk", // adaptive routing, futuristic
"hyperloop": "midnight-ocean", // deep orchestration, async vibes
"nexus": "tokyo-night", // unified intelligence layer
};
// ── Helpers ───────────────────────────────────────────────────────────────
+4
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@@ -93,6 +93,10 @@ ext-easymode:
ext-easymode-themed:
pi -e extensions/easymode.ts -e extensions/theme-cycler.ts
# 21. Model Router: LLM-powered automatic model selection
ext-model-router:
pi -e extensions/model-router.ts -e extensions/theme-cycler.ts
# utils
# Open pi with one or more stacked extensions in a new terminal: just open minimal tool-counter
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@@ -44,3 +44,22 @@ Network error: The operation timed out.
Network error: The socket connection was closed unexpectedly. For more information, pass `verbose: true` in the sec
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The socket connection was closed unexpectedly. For more information, pass `verbose: true` in the sec
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.
Network error: The operation timed out.