trpc-router
The trpc-router skill provides a standardized development guide for building TRPC API endpoints in the LobHub server application. Use this when creating new routers in apps/server/src/routers/lambda, adding query and mutation procedures, or implementing server-side database operations, following patterns for middleware-based model injection, error handling, and input validation with Zod schemas.
git clone --depth 1 https://github.com/lobehub/lobehub /tmp/trpc-router && cp -r /tmp/trpc-router/.agents/skills/trpc-router ~/.claude/skills/trpc-routerSKILL.md
# TRPC Router Guide
## File Location
- Routers: `apps/server/src/routers/lambda/<domain>.ts`
- Helpers: `apps/server/src/routers/lambda/_helpers/`
- Schemas: `apps/server/src/routers/lambda/_schema/`
## Router Structure
### Imports
```typescript
import { TRPCError } from '@trpc/server';
import { z } from 'zod';
import { SomeModel } from '@/database/models/some';
import { authedProcedure, router } from '@/libs/trpc/lambda';
import { serverDatabase } from '@/libs/trpc/lambda/middleware';
```
### Middleware: Inject Models into ctx
**Always use middleware to inject models into `ctx`** instead of creating `new Model(ctx.serverDB, ctx.userId)` inside every procedure.
```typescript
const domainProcedure = authedProcedure.use(serverDatabase).use(async (opts) => {
const { ctx } = opts;
return opts.next({
ctx: {
fooModel: new FooModel(ctx.serverDB, ctx.userId),
barModel: new BarModel(ctx.serverDB, ctx.userId),
},
});
});
```
Then use `ctx.fooModel` in procedures:
```typescript
// Good
const model = ctx.fooModel;
// Bad - don't create models inside procedures
const model = new FooModel(ctx.serverDB, ctx.userId);
```
**Exception**: When a model needs a different `userId` (e.g., watchdog iterating over multiple users' tasks), create it inline.
### Procedure Pattern
```typescript
export const fooRouter = router({
// Query
find: domainProcedure.input(z.object({ id: z.string() })).query(async ({ input, ctx }) => {
try {
const item = await ctx.fooModel.findById(input.id);
if (!item) throw new TRPCError({ code: 'NOT_FOUND', message: 'Not found' });
return { data: item, success: true };
} catch (error) {
if (error instanceof TRPCError) throw error;
console.error('[foo:find]', error);
throw new TRPCError({
cause: error,
code: 'INTERNAL_SERVER_ERROR',
message: 'Failed to find item',
});
}
}),
// Mutation
create: domainProcedure.input(createSchema).mutation(async ({ input, ctx }) => {
try {
const item = await ctx.fooModel.create(input);
return { data: item, message: 'Created', success: true };
} catch (error) {
if (error instanceof TRPCError) throw error;
console.error('[foo:create]', error);
throw new TRPCError({
cause: error,
code: 'INTERNAL_SERVER_ERROR',
message: 'Failed to create',
});
}
}),
});
```
### Aggregated Detail Endpoint
For views that need multiple related data, create a single `detail` procedure that fetches everything in parallel:
```typescript
detail: domainProcedure.input(idInput).query(async ({ input, ctx }) => {
const item = await resolveOrThrow(ctx.fooModel, input.id);
const [children, related] = await Promise.all([
ctx.fooModel.findChildren(item.id),
ctx.barModel.findByFooId(item.id),
]);
return {
data: { ...item, children, related },
success: true,
};
}),
```
This avoids the CLI or frontend making N sequential requests.
## Conventions
- Return shape: `{ data, success: true }` for queries, `{ data?, message, success: true }` for mutations
- Error handling: re-throw `TRPCError`, wrap others with `console.error` + new `TRPCError`
- Input validation: use `zod` schemas, define at file top
- Router name: `export const fooRouter = router({ ... })`
- Procedure names: alphabetical order within the router object
- Log prefix: `[domain:procedure]` format, e.g. `[task:create]`Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Add server-side environment variables that control default values for user settings.
Agent runtime lifecycle hooks. Use for before/after tool or step hooks, tool mocks, human intervention, sub-agent calls, context compression, evals, tracing, callAgent, or lifecycle events.
Build or extend LobeHub Agent Signal pipelines. Use for signal sources, signal/action types, policies, middleware, workflow handoff, dedupe, scope behavior, or observability.
Agent tracing CLI for execution snapshots. Use for agent-tracing, traces, snapshots, LLM call inspection, context engine data, agent step analysis, or execution debugging.
Build LobeHub builtin tool packages. Use when adding agent-callable tools, manifests, executors, runtimes, inspectors, renders, placeholders, streaming, interventions, portals, or tool registries.
Build multi-platform chat bots with the chat SDK. Use for Slack, Teams, Google Chat, Discord, GitHub, Linear bots, webhooks, mentions, slash commands, cards, modals, or streaming responses.
>