Tianyi Cui
46e31d8481
Add @deepseek-ai/dsh-tool-todo (a new packages/todo/ group): a model-facing
todo_write(todos: [{content, status}]) tool with whole-list-replace semantics.
Each call appends the full list as a todo/write event to the calling agent's
session log; the current list is the most recent such event (last-write-wins).
Single-owner — a non-agent caller is rejected. Beyond the schema's
type/required/enum checks, execute rejects empty/duplicate content and more than
one in_progress task, narrowing the loosely-typed args into a real TodoItem[].
Both UIs render off the existing session/event: the stdio UI prints a glyphed
checklist; the ACP bridge maps the list to a `plan` sessionUpdate (todosToPlan
synthesizes the priority ACP requires; status maps 1:1). Wired into the
coding-agent, acp-agent, and snapshot example configs with a system-prompt nudge.
Tests: unit (schema, validation, append/replace, no-agent rejection, presentCall,
HMR-safety, Loader export-shape guard), full-loop integration through the agent
loop, the ACP todosToPlan mapping + stream-update arm, the stdio render arm, and
a session/load replay that re-emits the plan. New-group TS wiring added to
tsconfig.base/json/build. RFC + a doc-inventory sweep (architecture, packages
README, AGENTS layout, cookbook group list, example READMEs) ship with it.
The todo-plan ACP snapshot scenario is recorded separately (needs an API key).
109 lines
4.5 KiB
YAML
109 lines
4.5 KiB
YAML
# The coding-agent plugin tree: the real coding agent. The two swappable
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# backends — the DeepSeek adapter and the local bash executor — plus `hmr` for
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# the dev/demo reload loop, then the stdio chat app (@deepseek-ai/dsh-stdio-
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# agent), which bundles the whole agent-core spine (timer, llm, sessions,
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# system-prompt, tools, agents, invariants, tool-bash, agent-loop), the console
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# logger, JSONL persistence, the readline UI, and a pre-created `main` agent.
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#
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# `hmr` is a leaf entry (not baked into dsh-stdio-agent): it is a Loader-only
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# dev plugin that needs `--expose-internals` — the `demo:coding` script passes
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# it. Requires DEEPSEEK_API_KEY (and optionally DEEPSEEK_BASE_URL) in the
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# environment — the dsh-stdio-agent bin loads the gitignored repo-root .env
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# first. cordis.yml reads them via the `!!js` tag.
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# Hot-module reload for the dev/demo loop (needs `node --expose-internals`).
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- id: hmr
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name: '@cordisjs/plugin-hmr'
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config:
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root: ['.']
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# The DeepSeek adapter. Swap to '@deepseek-ai/dsh-llm-pi-ai' for the pi-ai-backed
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# twin (same config shape; `reasoning: high` replaces thinking/reasoningEffort).
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- id: llm-deepseek
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name: '@deepseek-ai/dsh-llm-deepseek'
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config:
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apiKey: !!js process.env.DEEPSEEK_API_KEY
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baseURL: !!js process.env.DEEPSEEK_BASE_URL
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models:
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- deepseek-v4-flash
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- deepseek-v4-pro
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# Local bash executor (the model's only tool, via agent-core's tool-bash schema).
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- id: bash
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name: '@deepseek-ai/dsh-bash-local'
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config:
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timeoutMs: 60000
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# The stdio chat app: the whole spine + front-door cluster, configured for a
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# real coding agent driving a pre-created `main` agent.
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- id: stdio-agent
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name: '@deepseek-ai/dsh-stdio-agent'
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config:
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model: deepseek-v4-flash
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# Set RESUME_SESSION_ID to continue a prior persisted session (the ids live
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# under ./.sessions); unset starts a fresh session each run.
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resumeSessionId: !!js process.env.RESUME_SESSION_ID
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persistenceRoot: './.sessions'
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welcome: 'coding-agent ready. Give it a coding task (its tools are bash, subagent, and todo_write).'
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systemPrompt: |
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You are coding-agent, a CLI coding assistant.
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Your tools are bash (plus bash_output/bash_kill for background
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tasks) and subagent. Do ALL file operations through bash: read with
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cat/sed/head, search with grep, write with heredocs (cat <<'EOF' >
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file), edit with sed or a rewrite. Each bash call runs in a fresh
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shell — pass workdir instead of cd, and never rely on shell state
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between calls.
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Use the subagent tool to delegate a focused, self-contained subtask
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to a fresh child agent (it works in its own context and returns only
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its final result) — give it a complete, standalone instruction. Use
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subagent_fork instead when the subtask needs THIS conversation's
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context: the child inherits the log so far.
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Check the [exit code: N] marker on every command; investigate
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failures before moving on. Verify your work by running the code or
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tests. Keep answers brief and factual.
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For multi-step work, use the todo_write tool to track a task list:
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send the WHOLE list each call (it replaces the previous one), keep
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exactly one task in_progress, and mark a task completed as soon as it
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is done. Skip it for trivial single-step tasks.
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# The subagent seam + BOTH in-process backends + two model-facing tools, as leaf
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# entries after the app (which provides ctx.agents/ctx.tools). spawn (a fresh
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# child) and fork (a child seeded with the parent's completed-turn prefix) are
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# independent backends over the shared dsh-subagent-inprocess driver. Exposing
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# both transports is pure config: load each backend, then load dsh-tool-subagent
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# once per backend with a distinct toolName (the tool registry rejects a
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# duplicate name) — no code change.
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- id: subagent
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name: '@deepseek-ai/dsh-subagent'
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- id: subagent-spawn
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name: '@deepseek-ai/dsh-subagent-spawn'
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config:
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providerName: spawn
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- id: subagent-fork
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name: '@deepseek-ai/dsh-subagent-fork'
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config:
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providerName: fork
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- id: tool-subagent
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name: '@deepseek-ai/dsh-tool-subagent'
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config:
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provider: spawn
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toolName: subagent
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- id: tool-subagent-fork
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name: '@deepseek-ai/dsh-tool-subagent'
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config:
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provider: fork
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toolName: subagent_fork
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# The model-facing todo_write tool: whole-list task tracking written to the
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# session log (todo/write), rendered as a stdio checklist / ACP plan.
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- id: tool-todo
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name: '@deepseek-ai/dsh-tool-todo'
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