- AGENTS.md Commands: fix typecheck/build descriptions; add lint, lint:fix, test:coverage, knip, publint, hygiene (were undocumented). - Drop the bare `yarn demo` for explicit `demo:echo` + `demo:coding`; update README, examples READMEs (and document coding-agent in examples/README). - New cookbook guide: adding-a-vendored-package.md (the missing "add" half of vendor/README's update-only procedure). - architecture.md: add a table-of-contents and extract the Extension cookbook to docs/cookbook/extension-cookbook.md (link-preserving); drop the completed "restructure this document" TODO. - ADR 0009 (capability seams) + 0010 (twin LLM adapters), and a "when to write an ADR" standard in adr/README. - Add a committed dsh-code-review skill under .agents/skills, exposed to Claude Code via a tracked .claude/skills symlink (gitignore carve-out).
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Cookbook: adding a tool
How to give the model a new capability. Reference implementations: examples/echo-agent/src/echo-tool.ts (minimal) and packages/tool-bash (production-grade, three-package seam).
The minimal shape
import type { Context } from 'cordis'
import { defineTool } from '@deepseek-ai/dsh-tools'
export const name = 'my-tool'
export const inject = ['tools']
export function apply(ctx: Context) {
ctx.tools.register(defineTool({
name: 'read_file',
description: 'Read a file from disk.', // what the model sees
parameters: {
path: { type: 'string', required: true, description: 'Absolute path' },
limit: { type: 'number' }, // optional by default
},
async execute(args, exec) {
// args is TYPED from the schema: { path: string; limit?: number }
// exec carries { callId, name, arguments, agent?, signal? }
return [{ type: 'text', text: await readFile(args.path, 'utf8') }]
},
}))
}
Registration is effect-based: disposing the plugin fiber unregisters the tool (write the HMR test). Schemas flow into the system-prompt assembly automatically.
Rules of the execute() contract
- Validate args at runtime.
defineTool'sInferArgstyping is compile-time only; at runtimeargumentsis whatever JSON the model emitted. Check every field; throw a descriptive Error for bad input. - Throwing means isError. The registry catches anything
execute()throws and returns{isError: true}to the model. Use that for infrastructure failures (bad input, spawn errors, aborts) — but REPORT domain failures in the result text instead (e.g. tool-bash returns[exit code: 9]withisError: false: the model decides what a failing command means). - Honor
exec.signal. Cancel in-flight work when it fires. - Use
exec.agentfor async notifications.agent.inject(content, {source: {kind: 'plugin', plugin: '<name>'}})appends durable context the NEXT model request sees — it is not a wake-up (an idle agent stays idle). Guard against disposed agents (try/catch).
Long-running work
Follow tool-bash's background pattern: a run_in_background flag returns a task id immediately; companion tools poll incrementally and kill; completion notices arrive via agent.inject(). Bound buffers and spill full output to disk so nothing is silently lost.
TODO: each tool reimplements this background pattern by hand today. At some point we need a generic long-running-tool layer that handles task ids, incremental polling, kill, and completion notices uniformly.
Permissions / sandboxing
Prefer not to build policy into the tool. The seam is the tools/execute waterfall (veto or wrap — see the permission-gate example in extension-cookbook.md), or a sandboxing implementation behind the tool's executor seam.
Tests every tool needs
Arg-validation rejections, result shaping for every outcome, the HMR disposal test, and — for tools with side effects — an integration spec that drives the tool through the agent loop with a scripted MockAdapter (packages/agent-loop/tests/mock-adapter.ts), asserting the tool/call / tool/result session events.