Overview
dsh-agent-spine-demo
agents list as its own config — so an app package composes a working agent by adding only an entry point and the swappable backends.This is an atomic module already shipped with Harness, not a standalone profile layer.
Capabilities
What it contributes
README / EN
Package documentation
@deepseek-ai/dsh-agent-spine-demo
English | 中文
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 an entry point 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:
@deepseek-ai/cordis-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-session-title log-backed title service + deterministic fallback
@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-filesystem local filesystem skill provider
@deepseek-ai/dsh-agent agent registry + initiator scope + agent/* events
@deepseek-ai/dsh-goal optional persisted same-session goal domain
@deepseek-ai/dsh-tool-goal optional model-facing goal controls
@deepseek-ai/dsh-goal-round-driver optional same-session goal-round driver
@deepseek-ai/dsh-llm-retry provider-routed request retry policy
@deepseek-ai/dsh-jobs-local generic background-job registry
@deepseek-ai/dsh-invariants configurable invariant registry service
@deepseek-ai/dsh-session/invariant
@deepseek-ai/dsh-agent/invariant
@deepseek-ai/dsh-scope/invariant
@deepseek-ai/dsh-agent-loop/invariant
package-owned relational checks
@deepseek-ai/dsh-tool-bash the model-facing bash schema (unless toolBash=false)
@deepseek-ai/dsh-agent-instructions AGENTS.md/CLAUDE.md workspace context loader
@deepseek-ai/dsh-tool-skill session-prefix skill catalog + model-facing loader schema
@deepseek-ai/dsh-tool-jobs job_output/job_list/job_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 entry point. The swappable and entry-point-coupled pieces stay out, picked by whatever loads the bundle:
- the LLM adapter — the bundle ships the abstract
llmservice; the leaf registers a concrete adapter onctx.llm(llm-deepseek,llm-pi-ai,llm-replay). - model-backed session-title providers — the bundle mounts the fallback service with overridable example limits (5 words, 40 fallback bytes, 80 accepted-title bytes); a leaf may opt into exactly one first-prompt or all-messages LLM provider.
- the bash executor — the bundle ships
tool-bash(the consumer schema); the leaf providesctx.shell(bash-localor a sandboxed impl). - non-local skill providers — the bundle ships the skill registry, the local filesystem provider, and the
skilltool; deployments can add other providers such as embedded or remote catalogs as siblings. - entry point + per-app infrastructure — headless, ACP, and JSON-RPC app packages own transport, stdout, and reload choices.
timerstays in the spine because it is common and stdout-silent.
This applies the Service Definition / Service Provider / Consumer separation at the composition level: the bundle owns the shared spine, the leaf owns the backends, the app package owns the entry point.
Config
import type { Config } from '@deepseek-ai/dsh-agent-spine-demo'
// { agents?, maxParallelToolCalls?, includeHarnessIdentity?, includeRuntimeContext?, persona?, toolOrder?, tools?, dshHome?, sessionTitle?, skills?, workspaceContext, toolBash?, jobs?, toolJobs?, goals?, invariants? }
// workspaceContext requires { maxBytes } or false; the other owner schemas supply defaults.
The bundle forwards each field to the child that owns it. App packages supply any pre-created agents: headless and JSON-RPC compositions create main, while the ACP app creates agents on demand at session/new. includeRuntimeContext: false is forwarded to dsh-system-prompt and suppresses all dynamic context snapshots for fresh sessions without disabling their policy services. Prompt, tool, title, skill, agent-instructions, invariant, goal, and task settings retain the schemas and defaults documented by their owning packages; jobs.maxConcurrentJobsPerOwner configures the local provider independently of the model-facing toolJobs controls. pickSpineConfig() copies only fields owned by this bundle, and conflicting dshHome values fail during composition.
For example, { invariants: { enabled: true, package_allowlist: ['^@deepseek-ai/dsh-'], package_blocklist: ['agent-loop$'] } } keeps the package-owned companions mounted but suppresses the blocked owner. Blocklist matches override allowlist matches; see dsh-invariants for regex and lifecycle rules.
Why a code bundle, not a shared YAML include
A YAML include can deduplicate config but cannot own a bin or provide entry-point defaults. The ACP app package makes protocol-pure stdout 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.
The retry policy may repeat a failed request in a new numbered step. Retry status, provider errors, and failed partial chunks stay outside model history; each provider attempt can still incur billing, always mode has no attempt limit, entry points derive usage across every logged step, and the reconstructed request preserves the prior prefix for provider cache reuse.
Model Experience
Indirectly, through dsh-system-prompt, dsh-tool-skill, dsh-tool-bash, dsh-tools, and dsh-llm-retry, plus dsh-tool-goal and goal-round prompts when goals is enabled. The bundle adds no model-bound wrapper content of its own.
KV Cache effect
No direct invalidation; the named consumer owns any request-prefix changes.
Known Limitations and Deferred Work
- Most of the spine set is fixed in code —
apply()always mounts the core services; config can omit bundled goals, skills, bash, and task-control tools, but swapping the loop or dropping another spine member means composing a different bundle. - The invariant service and companions remain fixed members —
invariants.enabled: falseor package filters suppress checks but do not remove the service or companion registrations; Session's always-on validation and freezing are separate.
LIMITATIONS
Known limitations
- **Most of the spine set is fixed in code** — `apply()` always mounts the core services; config can omit bundled goals, skills, bash, and task-control tools, but swapping the loop or dropping another spine member means composing a different bundle. - **The invariant service and companions remain fixed members** — `invariants.enabled: false` or package filters suppress checks but do not remove the service or companion registrations; Session's always-on validation and freezing are separate.
