deepseek-harness/examples/coding-agent/cordis.yml

# The coding-agent plugin tree: the REPL agent demo. 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:repl` 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-pro
      - deepseek-v4-flash

# Local bash executor for agent-core's tool-bash schema (one of several tool
# stacks in this tree: filesystem, subagent, and todo_write load below).
- id: bash
  name: '@deepseek-ai/dsh-bash-local'
  config:
    timeoutMs: 60000

# The stdio chat app: the whole spine + front-door cluster, configured for a
# REPL agent demo 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: 'agent REPL ready. Give it a coding task.'
    # The persona: identity + behavior only, nothing about transports or
    # tooling — tool guidance lives with each tool plugin (descriptions +
    # prompt sections). {{model}} is the prompt variable the agent loop
    # resolves from this agent's configured model.
    persona: |
      You are coding-agent, a coding assistant powered by the {{model}} model.

      Verify your work by running the code or tests. Keep answers brief and
      factual.

# Automatic context compaction: when the derived history approaches the model's
# context window, summarize an older range into a checkpoint so a long-running
# or tool-heavy session keeps fitting. A leaf entry (needs ctx.llm + the
# agent-loop's `agent/pre-step` seam from the app above).
- id: compact-basic
  name: '@deepseek-ai/dsh-compact-basic'
  config:
    contextWindow: 128000
    thresholdRatio: 0.8
    retainTokens: 20480
    summarizationModel: ''
    maxTokens: 8192
    compactionRetries: 1

# 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

# The model-facing todo_write tool: whole-list task tracking written to the
# session log (todo/write), rendered as a stdio checklist / ACP plan.
- id: tool-todo
  name: '@deepseek-ai/dsh-tool-todo'

# Filesystem capability stack: local provider, read-before-write/edit policy
# gate, then the model-facing read/write/edit tools. stdio-agent is a single
# session, so relative paths resolve from the process cwd (the workspace).
- id: fs-local
  name: '@deepseek-ai/dsh-fs-local'
  config:
    cwd: !!js process.cwd()

- id: fs-policy
  name: '@deepseek-ai/dsh-fs-policy'

- id: tool-fs
  name: '@deepseek-ai/dsh-tool-fs'

# Bash-backed discovery tools (glob/grep): fixed ripgrep commands through the
# local bash executor above — not ctx.fs. Capped results save the complete
# formatted list through the spill backend below (ctx.spillFiles, optional).
- id: tool-fs-search
  name: '@deepseek-ai/dsh-tool-fs-search'

# The tool-call timeout enforcer: arms each declared ToolDefinition.timeoutMs
# (the search tools above declare 30s) as a deadline on exec.signal. Without
# it a declared budget is advisory and only the bash executor's own timeout
# backstop applies.
- id: timeout-policy
  name: '@deepseek-ai/dsh-timeout-policy'

# Tool-output spill stack: a local backend that saves oversized tool text under
# a private session-scoped dir, and the tools/post-execute policy that replaces
# an over-budget plain-text result with a preview + the spill path (the model
# reads the full result later). A leaf pair after the app (needs ctx.tools). The
# policy is a no-op until a tool returns more than maxInlineBytes of plain text.
- id: spill-local
  name: '@deepseek-ai/dsh-spill-local'

- id: spill-policy
  name: '@deepseek-ai/dsh-spill-policy'
  config:
    maxInlineBytes: 50000