Tianyi Cui
4036300353
Two pieces of dsh-acp surface were unreachable from any shipped config:
- AcpConfig.agentName/agentVersion: the app package hands the bridge only
{ model, systemPrompt }, so no leaf cordis.yml could set them; they were
settable only by direct-mounting the bridge (a unit test). Hardcode
agentInfo at the initialize site and delete the fields, their schema
defaults, the ?? fallbacks, and the TODO(double-default) whose subject
vanishes. The handshake wire value is unchanged (all snapshot initialize
lines byte-identical).
- The toolKindFor name heuristic special-cased bash*/read*/write/edit*
names in the generic-fallback path, violating the bridge's own design
rule ("the bridge never special-cases tool names"). Every first-party
tool ships its kind via presentCall; the fallback now renders the
neutral kind 'other'. The fallback is reachable when a presentCall
throws OR when model args fail the tool schema (defineTool's presentCall
wrapper returns undefined on violations) — the latter shows up in one
committed golden (hook-codex-posttool-block: three bash calls missing
the required description), whose kind cells flip execute->other. That
3-line golden refresh is the whole transcript delta.
The empty-arguments branch of parseToolArguments lost its only exercise
with the deleted heuristic test; it is live behavior (JSON.parse('')
throws, so the guard is what renders a zero-arg call as rawInput {}), so
it gets a dedicated pin instead of deletion.
RFC moved to docs/rfc/implemented/simplification/ and amended to shipped
reality: fallback reachability includes schema-invalid args, and the
golden churn is exactly the three kind cells (the original zero-churn
claim held only for the branding half).
acp-agent example
The DeepSeek Harness agent demo 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 example is just a leaf cordis.yml: it loads the @deepseek-ai/dsh-acp-agent app (which bundles the @deepseek-ai/dsh-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, bash, and filesystem backends, and the model-facing read/write/edit/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
This example loads no stdout logger — stdout carries the JSON-RPC frames, and any other write corrupts them. @deepseek-ai/dsh-acp-agent includes no logger entry, so this leaf has none to get wrong by default; do not add one (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": ["--dir", "/path/to/deepseek-harness", "run", "demo:acp"],
"env": { "DEEPSEEK_API_KEY": "sk-…" }
}
}
}
The editor sets each session's cwd to the project it opens; both the agent's bash tools and the read/write/edit filesystem tools resolve relative paths against that per-session workspace (see the per-session cwd note in packages/ui/acp and the per-session cwd RFC), so the server can be launched anywhere and each session still acts on its own project directory.
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 the ACP snapshot tests RFC for the full design.
MVP limitations
The bridge supports N concurrent sessions per connection, each in its own workspace cwd (RFC 011). Remaining limits: prompts support ACP's baseline text and resource_link blocks only, additionalDirectories and mcpServers are rejected, and the tool-permission gate is deferred (TODO(rfc010-permission-gate) — tools run with the executor's full authority). See packages/ui/acp/README.md for the full contract.