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/llm/test/provider/openai-responses-cache.recorded.test.ts

@@ -0,0 +1,46 @@
+import { describe, expect } from "bun:test"
+import { Effect } from "effect"
+import { LLM } from "../../src"
+import { LLMClient } from "../../src/route"
+import * as OpenAI from "../../src/providers/openai"
+import { LARGE_CACHEABLE_SYSTEM } from "../recorded-scenarios"
+import { recordedTests } from "../recorded-test"
+
+const model = OpenAI.configure({
+  apiKey: process.env.OPENAI_API_KEY ?? "fixture",
+}).responses("gpt-4.1-mini")
+
+// OpenAI caches prefixes automatically once they cross the 1024-token threshold;
+// `CacheHint` is a no-op for the wire body. The stable signal is the
+// `prompt_cache_key` routing hint, which keeps repeated calls on the same shard
+// so cache hits are observable.
+const cacheRequest = LLM.request({
+  id: "recorded_openai_responses_cache",
+  model,
+  system: LARGE_CACHEABLE_SYSTEM,
+  prompt: "Say hi.",
+  generation: { maxTokens: 16, temperature: 0 },
+  providerOptions: { openai: { promptCacheKey: "recorded-cache-test" } },
+})
+
+const recorded = recordedTests({
+  prefix: "openai-responses-cache",
+  provider: "openai",
+  protocol: "openai-responses",
+  requires: ["OPENAI_API_KEY"],
+  // Two identical requests in one cassette — replay walks the cassette in
+  // recording order so the second call replays the cached-hit interaction,
+  // not the cold-miss one.
+})
+
+describe("OpenAI Responses cache recorded", () => {
+  recorded.effect.with("reports cached_tokens on identical second call", { tags: ["cache"] }, () =>
+    Effect.gen(function* () {
+      const first = yield* LLMClient.generate(cacheRequest)
+      expect(first.usage?.cacheReadInputTokens ?? 0).toBeGreaterThanOrEqual(0)
+
+      const second = yield* LLMClient.generate(cacheRequest)
+      expect(second.usage?.cacheReadInputTokens ?? 0).toBeGreaterThan(0)
+    }),
+  )
+})