# @deepseek-ai/dsh-agent-spine-demo

The **default executor-less, UI-less agent spine** as ONE Cordis bundle plugin. It loads the fixed set of services every harness agent needs, including the local skill provider, and forwards the loop's `agents` list as its own config — so an app package composes a working agent by adding only a front door and the swappable backends.

Read this package for the whole plugin tree and its composition order.

## The tree it loads

`apply(ctx, config)` mounts each of these as a child of the bundle fiber:

```
@cordisjs/plugin-timer            timer service (writes nothing to stdout)
@deepseek-ai/dsh-llm              abstract LLM service + content-block vocabulary
@deepseek-ai/dsh-session          event-sourced session log + store
@deepseek-ai/dsh-system-prompt    prompt-section + tool-schema assembly
@deepseek-ai/dsh-tools            registry + guarded pre/around/post/final-result pipeline
@deepseek-ai/dsh-skill            skill provider registry
@deepseek-ai/dsh-skill-local      local filesystem skill provider
@deepseek-ai/dsh-agent            agent registry + initiator scope + agent/* events
@deepseek-ai/dsh-tasks            generic background-task registry
@deepseek-ai/dsh-invariants       dev-mode event-contract assertions
@deepseek-ai/dsh-tool-bash        the model-facing bash schema
@deepseek-ai/dsh-workspace-context  AGENTS.md/CLAUDE.md workspace context loader
@deepseek-ai/dsh-tool-skill       session-prefix skill catalog + model-facing loader schema
@deepseek-ai/dsh-tool-tasks       task_output/task_list/task_kill schemas + completion notices
@deepseek-ai/dsh-agent-loop       THE concrete loop (gets the forwarded `agents`)
                                  (dsh-system-prompt gets the forwarded `persona`)
```

## What it deliberately leaves OUTSIDE the bundle

The spine is everything COMMON to every front door. The swappable and front-door-coupled pieces stay out, picked by whatever loads the bundle:

- **the LLM adapter** — the bundle ships the abstract `llm` service; the leaf registers a concrete adapter on `ctx.llm` (`llm-deepseek`, `llm-pi-ai`, `llm-replay`).
- **the bash executor** — the bundle ships `tool-bash` (the consumer schema); the leaf provides `ctx.bash` (`bash-local` or a sandboxed impl).
- **non-local skill providers** — the bundle ships the skill registry, the local filesystem provider, and the `skill` tool; deployments can add other providers such as embedded or remote catalogs as siblings.
- **presentation + per-app infra** — the terminal (`dsh-tui` / `dsh-stdio`) or ACP front door and `hmr`. These form the coupled front-door cluster that the app packages ([`dsh-stdio-demo`](../../examples/stdio-demo/README.md), [`dsh-acp-demo`](../../examples/acp-demo/README.md)) bake in. `timer` is in the spine because it is common and stdout-silent; front doors own stdout and remain outside.

This is the [interface/implementation/consumer seam](../../../docs/rfc/implemented/architecture/2026-06-13-capability-seams.md) raised to the composition level: the bundle owns the shared spine, the leaf owns the backends, the app package owns the front door.

## Config

```ts
import type { Config } from '@deepseek-ai/dsh-agent-spine-demo'
// { agents?, maxParallelToolCalls?, persona?, toolOrder?, tools?, dshHome?, skills?, workspaceContext, toolBash?, toolTasks? }
// workspaceContext requires { maxBytes } or false; the other owner schemas supply defaults.
```

The bundle FORWARDS each field to the child that owns it: `agents` and `maxParallelToolCalls` to `agent-loop` (`agents` defaults to `[]`; the cap defaults there), so each app supplies its own pre-created agents — a stdio app pre-creates `main`, while the ACP app creates agents on demand at `session/new`; `persona` and `toolOrder` to `dsh-system-prompt`; `tools` to the tool registry for its presentation mode; `skills.registry`, `skills.local`, and `skills.tool` to the skill registry, local provider, and model-facing consumer; the required `workspaceContext` choice to `dsh-workspace-context` (`{ maxBytes }` enables loading and `false` disables it); and `toolBash`/`toolTasks` to the two model-facing tool plugins the bundle owns. It resolves `dshHome` once through [`@deepseek-ai/dsh-home`](../../util/home/README.md) and forwards that absolute value to tool-bash's managed environment and local skill discovery. An absent top-level `dshHome` adopts `skills.local.dshHome`; supplying both with different resolved paths fails loudly. `toolBash.enableRunInBackground` controls only the bash producer, while `toolTasks` controls generic `task_output` wait bounds; independently loaded producers keep their own config. Workspace instructions register before the skill catalog so their session-prefix message renders first. App packages use `pickSpineConfig()` to copy only these bundle-owned fields.

## Why a code bundle, not a shared YAML include

A YAML include can deduplicate config but cannot own a bin or provide front-door defaults. App packages make stdout-safe ACP wiring the default, though a leaf can still add an unsafe logger. Bundle children register services in the root isolate-keyed store, so injected leaf siblings see them without load-order coupling.

## Model Experience

Indirectly, through `dsh-system-prompt`, `dsh-tool-skill`, `dsh-tool-bash`, and `dsh-tools`, which this bundle mounts without adding model-bound wrapper content.

#### KV Cache effect

No direct invalidation; the named consumer owns any request-prefix changes.

## Known Limitations and Deferred Work

- **The spine set is fixed in code** — `apply()` mounts every child unconditionally (including `tool-bash`); no config excludes or replaces one, so swapping the loop or dropping a spine member means composing a different bundle.
- **`dsh-invariants` mounts unconditionally** — this bundle has no toggle, so every composition using it pays the dev-mode relational assertions; Session's always-on validation and freezing are separate.
