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deepseek-harness/examples/acp-agent/cordis.snapshot.yml
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Tianyi Cui 34f6f28716 Make fork reachable by the model in the acp-agent demo (review feedback)
The acp-agent cordis configs loaded the fork backend but bound only one
dsh-tool-subagent (to spawn), so the comment's claim that a multi-child scenario
could exercise both transports was false — fork was loaded but unreachable by
the model. Register a second dsh-tool-subagent bound to fork with a distinct
toolName (subagent_fork), matching the coding-agent demo, in both cordis.yml
(record/demo) and cordis.snapshot.yml (replay). Snapshot goldens are unchanged
(the transcript does not capture the available-tool list).
2026-06-22 17:00:59 +08:00

73 lines
2.8 KiB
YAML

# Snapshot-test REPLAY config: the acp-agent plugin tree with the model backend
# swapped to llm-replay (serves a recorded session JSONL — no API key, no
# network). The dsh-acp-agent bin selects this file for DSH_SNAPSHOT=replay.
#
# Same app as cordis.yml (@deepseek-ai/dsh-acp-agent: the agent-core spine +
# JSONL persistence + the ACP bridge) — only the LLM backend differs: llm-replay
# here, llm-deepseek there. It can't reuse the real adapter because llm-deepseek's
# apply() throws without DEEPSEEK_API_KEY, killing a keyless replay run at boot.
#
# stdout is reserved for the ACP JSON-RPC protocol — no stdout logger (the app
# package omits it). The replay fixture path comes from $DSH_SNAPSHOT_FILE (and
# an optional $DSH_SNAPSHOT_OVERRIDE sidecar), set by the snapshot harness.
# The replay adapter: short-circuits llm/stream with the recorded log's chunks,
# in place of llm-deepseek.
- id: llm-replay
name: '@deepseek-ai/dsh-llm-replay'
# Local bash executor (the agent's only tool, via agent-core's tool-bash schema).
- id: bash
name: '@deepseek-ai/dsh-bash-local'
config:
timeoutMs: 60000
# The ACP server app — identical to cordis.yml's entry.
- id: acp-agent
name: '@deepseek-ai/dsh-acp-agent'
config:
model: deepseek-v4-flash
persistenceRoot: !!js process.env.DSH_SNAPSHOT_SESSIONS_ROOT ?? './.sessions'
systemPrompt: |
You are a coding assistant driven over the Agent Client Protocol.
Your tools are bash (plus bash_output/bash_kill for background tasks)
and subagent. Do ALL file operations through bash: read with
cat/sed/head, search with grep, write with heredocs (cat <<'EOF' >
file), edit with sed or a rewrite. Each bash call runs in a fresh
shell — pass workdir instead of cd. Check the [exit code: N] marker;
verify your work. Keep answers brief and factual.
Use the subagent tool to delegate a focused, self-contained subtask to
a fresh child agent (it works in its own context and returns only its
final result) — give it a complete, standalone instruction.
# The subagent seam + both in-process backends + two model-facing tools —
# identical to cordis.yml's wiring (only the LLM backend differs above): spawn
# and fork are each reachable via a dsh-tool-subagent bound to it with a distinct
# toolName (subagent → spawn, subagent_fork → fork).
- id: subagent
name: '@deepseek-ai/dsh-subagent'
- id: subagent-spawn
name: '@deepseek-ai/dsh-subagent-spawn'
config:
providerName: spawn
- id: subagent-fork
name: '@deepseek-ai/dsh-subagent-fork'
config:
providerName: fork
- id: tool-subagent
name: '@deepseek-ai/dsh-tool-subagent'
config:
provider: spawn
toolName: subagent
- id: tool-subagent-fork
name: '@deepseek-ai/dsh-tool-subagent'
config:
provider: fork
toolName: subagent_fork