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docs: sync implementation docs and doc gates

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kingwl
2026-06-30 20:07:52 +08:00
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4
examples/acp-agent/README.md
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@@ -6,7 +6,7 @@ The DeepSeek Harness coding agent exposed as an **Agent Client Protocol (ACP)**
pnpm run demo:acp # needs DEEPSEEK_API_KEY (repo-root .env or env)
```
This example is just a leaf `cordis.yml`: it loads the [`@deepseek-ai/dsh-acp-agent`](../../packages/ui/acp-agent) app (which bundles the [`@deepseek-ai/dsh-agent-core`](../../packages/core/agent-core) spine, JSONL session persistence, and the `@deepseek-ai/dsh-acp` bridge — with **no pre-created agents**, since ACP `session/new` creates them on demand) plus the two swappable backends (`llm-deepseek`, `bash-local`). The app package bakes in the no-stdout-logger cluster, so a leaf has no logger entry to get wrong by default — keeping stdout pure for JSON-RPC.
This example is just a leaf `cordis.yml`: it loads the [`@deepseek-ai/dsh-acp-agent`](../../packages/ui/acp-agent) app (which bundles the [`@deepseek-ai/dsh-agent-core`](../../packages/core/agent-core) spine, JSONL session persistence, and the `@deepseek-ai/dsh-acp` bridge — with **no pre-created agents**, since ACP `session/new` creates them on demand), the swappable DeepSeek and bash backends, and the optional model-facing `subagent`/`subagent_fork`/`todo_write` tool entries. The app package bakes in the no-stdout-logger cluster, so a leaf has no logger entry to get wrong by default — keeping stdout pure for JSON-RPC.
## stdout is the protocol
@@ -32,7 +32,7 @@ The editor sets each session's `cwd` to the project it opens; the agent's bash t
## 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 output against committed golden files. The model is made deterministic by `@deepseek-ai/dsh-llm-replay`, a function/namespace plugin that installs an `llm/stream` waterfall listener and short-circuits it, serving model streams reconstructed from a recorded **session JSONL** fixture (`<scenario>/session.jsonl`) — so replay needs no API key. The fixture IS the persisted session log: its `assistant/chunk` events carry every `StreamChunk`, so grouping them by `(turn, step)` reconstructs each `stream()` call (one model call per loop step). Recording is therefore "run the real agent once and harvest the `.jsonl`". The two failure modes not expressible as logged chunks — a pure throw before any chunk, and cancel/hang — use an optional `<scenario>/replay.override.json` sidecar (a `ReplayEntry[]` that replaces the derived script). A scenario that needs the agent to operate on existing files ships an optional `<scenario>/workspace/` directory — the harness copies its contents into the temp cwd before the run (see `workspace-edit`). See [docs/rfc/implemented/2026-06-19-acp-snapshot-tests.md](../../docs/rfc/implemented/2026-06-19-acp-snapshot-tests.md) for the full design.
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 output against committed golden files. The model is made deterministic by `@deepseek-ai/dsh-llm-replay`, a function/namespace plugin that installs an `llm/stream` waterfall listener and short-circuits it, serving model streams reconstructed from a recorded **session JSONL** fixture (`<scenario>/session.jsonl`) — so replay needs no API key. The fixture IS the persisted session log: its `assistant/chunk` events carry every `StreamChunk`, so grouping them by `(turn, step)` reconstructs each `stream()` call (one model call per loop step). Recording is therefore "run the real agent once and harvest the `.jsonl`". The two failure modes not expressible as logged chunks — a pure throw before any chunk, and cancel/hang — use an optional `<scenario>/replay.override.json` sidecar (a `ReplayEntry[]` that replaces the derived script). A scenario that needs the agent to operate on existing files ships an optional `<scenario>/workspace/` directory — the harness copies its contents into the temp cwd before the run (see `workspace-edit`). See [the ACP snapshot tests RFC](../../docs/rfc/implemented/testing/2026-06-19-acp-snapshot-tests.md) for the full design.
## MVP limitations

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examples/acp-agent/cordis.yml
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@@ -1,9 +1,8 @@
# The acp-agent plugin tree: the ACP server. Also the snapshot RECORD config
# (the dsh-acp-agent bin selects it for DSH_SNAPSHOT=record): a real llm-deepseek
# run whose persisted log the snapshot harness harvests. Just the two swappable
# backends — the DeepSeek adapter and the local bash executor — plus the ACP
# server app (@deepseek-ai/dsh-acp-agent), which bundles the agent-core spine,
# JSONL persistence, and the ACP bridge.
# run whose persisted log the snapshot harness harvests. The swappable DeepSeek
# adapter and local bash executor, the ACP server app (@deepseek-ai/dsh-acp-agent),
# and the optional model-facing subagent/todo tools loaded below.
#
# CRITICAL: this tree loads NO stdout logger and NO hmr — stdout is reserved for
# the ACP JSON-RPC protocol (see packages/ui/acp). That guarantee is now a