feat(aircoding): AirCoding V2 baseline — deterministic multi-agent architecture

Forked from OpenCode v1.17.4 with multi-agent system:
- 5 agents: aircoding, scheduler, worker, architect, reviewer
- Deterministic DAG scheduling engine (coordinator_tick)
- Tool whitelists as hard enforcement
- AirCoding validation plugin
- System prompt injection for routing
- V1 requirements: C4 docs, ADR, AGENTS.md, debug-log.md
- Design documents in docs/

packages/app/src/components/session/session-context-breakdown.test.ts

@@ -0,0 +1,61 @@
+import { describe, expect, test } from "bun:test"
+import type { Message, Part } from "@opencode-ai/sdk/v2/client"
+import { estimateSessionContextBreakdown } from "./session-context-breakdown"
+
+const user = (id: string) => {
+  return {
+    id,
+    role: "user",
+    time: { created: 1 },
+  } as unknown as Message
+}
+
+const assistant = (id: string) => {
+  return {
+    id,
+    role: "assistant",
+    time: { created: 1 },
+  } as unknown as Message
+}
+
+describe("estimateSessionContextBreakdown", () => {
+  test("estimates tokens and keeps remaining tokens as other", () => {
+    const messages = [user("u1"), assistant("a1")]
+    const parts = {
+      u1: [{ type: "text", text: "hello world" }] as unknown as Part[],
+      a1: [{ type: "text", text: "assistant response" }] as unknown as Part[],
+    }
+
+    const output = estimateSessionContextBreakdown({
+      messages,
+      parts,
+      input: 20,
+      systemPrompt: "system prompt",
+    })
+
+    const map = Object.fromEntries(output.map((segment) => [segment.key, segment.tokens]))
+    expect(map.system).toBe(4)
+    expect(map.user).toBe(3)
+    expect(map.assistant).toBe(5)
+    expect(map.other).toBe(8)
+  })
+
+  test("scales segments when estimates exceed input", () => {
+    const messages = [user("u1"), assistant("a1")]
+    const parts = {
+      u1: [{ type: "text", text: "x".repeat(400) }] as unknown as Part[],
+      a1: [{ type: "text", text: "y".repeat(400) }] as unknown as Part[],
+    }
+
+    const output = estimateSessionContextBreakdown({
+      messages,
+      parts,
+      input: 10,
+      systemPrompt: "z".repeat(200),
+    })
+
+    const total = output.reduce((sum, segment) => sum + segment.tokens, 0)
+    expect(total).toBeLessThanOrEqual(10)
+    expect(output.every((segment) => segment.width <= 100)).toBeTrue()
+  })
+})