# The coding-agent plugin tree: the real coding agent. The two swappable
# backends — the DeepSeek adapter and the local bash executor — plus `hmr` for
# the dev/demo reload loop, then the stdio chat app (@deepseek-ai/dsh-stdio-
# agent), which bundles the whole agent-core spine (timer, llm, sessions,
# system-prompt, tools, agents, invariants, tool-bash, agent-loop), the console
# logger, JSONL persistence, the readline UI, and a pre-created `main` agent.
#
# `hmr` is a leaf entry (not baked into dsh-stdio-agent): it is a Loader-only
# dev plugin that needs `--expose-internals` — the `demo:coding` script passes
# it. Requires DEEPSEEK_API_KEY (and optionally DEEPSEEK_BASE_URL) in the
# environment — the dsh-stdio-agent bin loads the gitignored repo-root .env
# first. cordis.yml reads them via the `!!js` tag.

# Hot-module reload for the dev/demo loop (needs `node --expose-internals`).
- id: hmr
  name: '@cordisjs/plugin-hmr'
  config:
    root: ['.']

# The DeepSeek adapter. Swap to '@deepseek-ai/dsh-llm-pi-ai' for the pi-ai-backed
# twin (same config shape; `reasoning: high` replaces thinking/reasoningEffort).
- id: llm-deepseek
  name: '@deepseek-ai/dsh-llm-deepseek'
  config:
    apiKey: !!js process.env.DEEPSEEK_API_KEY
    baseURL: !!js process.env.DEEPSEEK_BASE_URL
    models:
      - deepseek-v4-flash
      - deepseek-v4-pro

# Local bash executor (the model's only tool, via agent-core's tool-bash schema).
- id: bash
  name: '@deepseek-ai/dsh-bash-local'
  config:
    timeoutMs: 60000

# The stdio chat app: the whole spine + front-door cluster, configured for a
# real coding agent driving a pre-created `main` agent.
- id: stdio-agent
  name: '@deepseek-ai/dsh-stdio-agent'
  config:
    model: deepseek-v4-flash
    # Set RESUME_SESSION_ID to continue a prior persisted session (the ids live
    # under ./.sessions); unset starts a fresh session each run.
    resumeSessionId: !!js process.env.RESUME_SESSION_ID
    persistenceRoot: './.sessions'
    welcome: 'coding-agent ready. Give it a coding task (its tools are bash and subagent).'
    systemPrompt: |
      You are coding-agent, a CLI coding assistant.

      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, and never rely on shell state
      between calls.

      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. Use
      subagent_fork instead when the subtask needs THIS conversation's
      context: the child inherits the log so far.

      Check the [exit code: N] marker on every command; investigate
      failures before moving on. Verify your work by running the code or
      tests. Keep answers brief and factual.

# The subagent seam + BOTH in-process backends + two model-facing tools, as leaf
# entries after the app (which provides ctx.agents/ctx.tools). spawn (a fresh
# child) and fork (a child seeded with the parent's completed-turn prefix) are
# independent backends over the shared dsh-subagent-inprocess driver. Exposing
# both transports is pure config: load each backend, then load dsh-tool-subagent
# once per backend with a distinct toolName (the tool registry rejects a
# duplicate name) — no code change.
- 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