5.1 KiB
5.1 KiB
Three-layer capability design
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When a capability is general enough to need replaceable implementations, such as Bash execution, Harness splits it into three packages: an interface, an implementation, and a consumer. Each layer can evolve or be replaced independently.
Bash example
The Bash execution capability consists of:
- Interface (
dsh-bash) — defines Bash request and result shapes - Implementation (
dsh-bash-local) — executes commands on the local machine - Consumer (
dsh-tool-bash) — exposes the capability as a model-callable tool
┌─────────────┐ ┌──────────────────┐ ┌──────────────┐
│ dsh-bash │────▶│ dsh-bash-local │ │ dsh-tool-bash│
│ (interface) │ │ (implementation) │ │(consumer/tool)│
└─────────────┘ └──────────────────┘ └──────────────┘
▲ │
└────────────────────────────────────────────┘
inject: ['bash']
Benefits of the split
Replace implementations
One interface can have multiple implementations selected through cordis.yml:
# Local execution
- name: '@deepseek-ai/dsh-bash-local'
# Or a future remote sandbox implementation
# - name: '@deepseek-ai/dsh-bash-remote'
# config:
# endpoint: 'https://sandbox.example.com'
The interface and tool remain unchanged while the implementation changes.
Evolve independently
- The interface changes rarely after its contract stabilizes.
- Implementations can improve performance and security independently.
- Consumers can change how they present the capability to the model.
Decouple dependencies
- The implementation depends on the interface.
- The consumer depends on the interface.
- The implementation and consumer do not depend on each other.
Built-in three-layer capabilities
| Capability | Interface | Implementation | Consumer |
|---|---|---|---|
| Bash | dsh-bash |
dsh-bash-local |
dsh-tool-bash |
| Filesystem | dsh-fs |
dsh-fs-local + dsh-fs-policy |
dsh-tool-fs |
| Web | dsh-web |
dsh-web-fetch-local / dsh-web-search-* |
dsh-tool-web |
| Subagent | dsh-subagent |
dsh-subagent-spawn / dsh-subagent-fork |
dsh-tool-subagent |
| Compaction | dsh-compact |
dsh-compact-basic |
The implementation consumes agent-loop extension events |
Develop a three-layer capability
Step 1: define the interface
// packages/my-cap/my-cap/src/index.ts
import { Service, type Context } from 'cordis'
declare module 'cordis' {
interface Context {
myCap: MyCapService
}
}
export abstract class MyCapService extends Service {
constructor(ctx: Context) {
super(ctx, 'myCap')
}
/** Execute the capability. */
abstract execute(request: MyCapRequest): Promise<MyCapResult>
}
export interface MyCapRequest {
input: string
}
export interface MyCapResult {
output: string
}
Step 2: write an implementation
// packages/my-cap/my-cap-local/src/index.ts
import type { Context } from 'cordis'
import { MyCapService, type MyCapRequest, type MyCapResult } from '@deepseek-ai/dsh-my-cap'
class MyCapLocal extends MyCapService {
async execute(request: MyCapRequest): Promise<MyCapResult> {
// Concrete implementation.
return { output: request.input.toUpperCase() }
}
}
export const name = 'my-cap-local'
export function apply(ctx: Context) {
ctx.plugin(MyCapLocal)
}
Step 3: write a consumer
// packages/my-cap/tool-my-cap/src/index.ts
import type { Context } from 'cordis'
import { defineTool } from '@deepseek-ai/dsh-tools'
export const name = 'tool-my-cap'
export const inject = ['tools', 'myCap']
export function apply(ctx: Context) {
ctx.tools.register(defineTool({
name: 'my_cap',
description: 'Execute my capability.',
parameters: {
input: { type: 'string', required: true },
},
output: {
schema: { type: 'string' },
render: (_args, value) => [{ type: 'text', text: value }],
},
async execute(args) {
const result = await ctx.myCap.execute({ input: args.input })
return result.output
},
}))
}
Compose them in cordis.yml
- name: '@deepseek-ai/dsh-my-cap-local'
- name: '@deepseek-ai/dsh-tool-my-cap'
Design points
- Do not split preemptively — use three packages only when the capability needs replaceable implementations. A simple tool plugin does not.
- The interface owns Request/Result types — implementations and consumers depend only on the interface package.
- Explicit > implicit — resolve defaults in an explicit
resolve(request): Specstep rather than hiding?? defaultexpressions insiderun().
Next steps
- LLM adapter — implement an LLM backend, a common capability interface extension