Introduces examples/acp-agent/src/llm-replay.ts, a function/namespace plugin
that installs a single llm/stream waterfall listener. In record mode it tees
the real model's StreamChunks into a per-scenario llm.json (flushed atomically
after EACH stream, since the snapshot subprocess is SIGKILLed and start.ts has
no disposal path). In replay mode it short-circuits the waterfall and serves
recorded streams back positionally — the Nth stream() call gets the Nth entry —
so a snapshot test can drive the real agent with no API key.
Each fixture entry is a discriminated record {chunks|throw|hang} so it can
replay BOTH branches of the LLM failure contract (throw from stream() vs a
finish-error chunk) plus cancellation. A throw entry carries the prefix chunks
emitted before the throw, replayed before the error, so a mid-stream failure
(partial output then STREAM_CLOSED) reproduces what the loop saw live.
Fail-loud on a missing or exhausted fixture (never a silent skip). Unit tests
drive the real LlmService waterfall (record tee, ordered replay, the three
entry kinds, partial-then-throw, fail-loud, event-driven abort, HMR-safety).
Broadens the unit vitest include to examples/*/tests and registers the plugin
+ snapshot tests as knip entries. Per docs/rfc/implemented/2026-06-19.
acp-agent example
The DeepSeek Harness coding agent exposed as an Agent Client Protocol (ACP) server over JSON-RPC stdio — drive it from Zed or any other ACP client.
pnpm run demo:acp # needs DEEPSEEK_API_KEY (repo-root .env or env)
This boots @deepseek-ai/dsh-acp over the shared provider/tool core (../base.yml), with agent-loop configured with no pre-created agents (ACP session/new creates them on demand) and JSONL session persistence (so session/load works).
stdout is the protocol
This example loads no stdout logger — stdout carries the JSON-RPC frames, and any other write corrupts them. Do not add @cordisjs/plugin-logger-console or a stdio UI here. Use a stderr exporter if you need logs.
Zed configuration
Add to your Zed settings.json under agent_servers:
{
"agent_servers": {
"DeepSeek Harness": {
"command": "pnpm",
"args": ["run", "demo:acp"],
"env": { "DEEPSEEK_API_KEY": "sk-…" }
}
}
}
The editor sets each session's cwd to the project it opens; the agent's bash tools run there (see the per-session cwd note in packages/acp), so the server does not need to be launched in the workspace.
Snapshot tests (record-once / replay-deterministic)
This example is the home of the harness's snapshot tests — they boot this server as a real subprocess, drive it with a deterministic input script, and diff its normalized stdout transcript against a committed golden file. The model is made deterministic by src/llm-replay.ts, a function/namespace plugin that installs an llm/stream waterfall listener: in record mode it tees the real model's StreamChunks into a per-scenario llm.json (flushed atomically after each call); in replay mode it short-circuits the waterfall and serves those chunks back, so replay needs no API key. Each fixture entry is a discriminated record — { kind: 'chunks' | 'throw' | 'hang' } — so both LLM failure branches (throw vs. finish-error) and cancellation replay faithfully. See docs/rfc/implemented/2026-06-19-acp-snapshot-tests.md for the full design.
MVP limitations
The bridge supports N concurrent sessions per connection, each in its own workspace cwd (RFC 011). Remaining limits: text-only prompts, additionalDirectories rejected (a session operates in its single cwd), and the tool-permission gate is deferred (TODO(rfc010-permission-gate) — tools run with the executor's full authority). See packages/acp/README.md for the full contract.