| name | slack-agent |
| description | Use when working on Slack agent/bot code, Chat SDK applications, or projects using `chat` and `@chat-adapter/slack`. Provides development patterns, testing requirements, and quality standards. |
| version | 4.0.0 |
| user-invocable | true |
Slack Agent Development Skill (Chat SDK)
This skill builds Slack agents on the Chat SDK: chat + @chat-adapter/slack running on Next.js (App Router) deployed to Vercel.
Skill Invocation Handling
When this skill is invoked via /slack-agent, check for arguments and route accordingly:
Command Arguments
| Argument | Action |
|---|
new | Run the setup wizard from Phase 1. Read ./wizard/1-project-setup.md and guide the user through creating a new Slack agent. |
configure | Start wizard at Phase 2 or 3 for existing projects |
deploy | Start wizard at Phase 5 for production deployment |
test | Start wizard at Phase 6 to set up testing |
| (no argument) | Auto-detect based on project state (see below) |
Auto-Detection (No Argument)
If invoked without arguments, detect the project state and route appropriately:
- No
package.json with chat → Treat as new, start Phase 1
- Has project but no customized
manifest.json → Start Phase 2
- Has project but no
.env file → Start Phase 3
- Has
.env but not tested → Start Phase 4
- Tested but not deployed → Start Phase 5
- Otherwise → Provide general assistance using this skill's patterns
Wizard Phases
The wizard is located in ./wizard/ with these phases:
1-project-setup.md — Understand purpose, generate custom implementation plan
1b-approve-plan.md — Present plan for user approval before scaffolding
2-create-slack-app.md — Customize manifest, create app in Slack
3-configure-environment.md — Set up .env with credentials
4-test-locally.md — Dev server + ngrok tunnel
5-deploy-production.md — Vercel deployment
6-setup-testing.md — Vitest configuration
IMPORTANT: For new projects, you MUST:
- Read
./wizard/1-project-setup.md first
- Ask the user what kind of agent they want to build
- Generate a custom implementation plan using
./reference/agent-archetypes.md
- Present the plan for approval (Phase 1b) BEFORE scaffolding the project
- Only proceed to scaffold after the plan is approved
General Development Guidance
You are working on a Slack agent project. Follow these mandatory practices for all code changes.
Project Stack
- Framework: Next.js (App Router)
- Chat SDK:
chat + @chat-adapter/slack for Slack bot functionality
- State:
@chat-adapter/state-redis for state persistence (or in-memory for development)
- AI: AI SDK v6 with
@ai-sdk/openai
- Linting: Biome
- Package Manager: pnpm
{
"dependencies": {
"ai": "^6.0.0",
"@ai-sdk/openai": "latest",
"chat": "latest",
"@chat-adapter/slack": "latest",
"@chat-adapter/state-redis": "latest",
"zod": "^3.x",
"next": "^15.x"
}
}
Note: Pookie uses @ai-sdk/openai directly. OPENAI_API_KEY is read automatically by the SDK at runtime. Other providers can be swapped in by changing the import and model string.
Quality Standards (MANDATORY)
These quality requirements MUST be followed for every code change. There are no exceptions.
After EVERY File Modification
-
Run linting immediately:
pnpm lint
- If errors exist, run
pnpm lint --write for auto-fixes
- Manually fix remaining issues
- Re-run
pnpm lint to verify
-
Check for corresponding test file:
- If you modified
foo.ts, check if foo.test.ts exists
- If no test file exists and the file exports functions, create one
Before Completing ANY Task
You MUST run all quality checks and fix any issues before marking a task complete:
pnpm typecheck
pnpm lint
pnpm test
Do NOT complete a task if any of these fail. Fix the issues first.
Unit Tests Required
For ANY code change, you MUST write or update unit tests.
- Location: Co-located
*.test.ts files or lib/__tests__/
- Framework: Vitest
- Coverage: All exported functions must have tests
Example test structure:
import { describe, it, expect, vi } from "vitest";
import { myFunction } from "./my-module";
describe("myFunction", () => {
it("should handle normal input", () => {
expect(myFunction("input")).toBe("expected");
});
it("should handle edge cases", () => {
expect(myFunction("")).toBe("default");
});
});
E2E Tests for User-Facing Changes
If you modify:
- Bot mention handlers / Slack message handlers
- Slash commands
- Interactive components (buttons, modals)
- Bot responses
You MUST add or update E2E tests that verify the full flow.
Bot Setup Patterns (CRITICAL)
Use the Chat SDK to define your bot instance. This is the central entry point for all Slack bot functionality.
Bot Instance (lib/bot.ts or lib/bot.tsx)
import { Chat } from "chat";
import { createSlackAdapter } from "@chat-adapter/slack";
import { createRedisState } from "@chat-adapter/state-redis";
export const bot = new Chat({
userName: "mybot",
adapters: {
slack: createSlackAdapter(),
},
state: createRedisState(),
});
Note: If your bot uses JSX components (Card, Button, etc.), the file must use the .tsx extension.
Webhook Route (app/api/webhooks/[platform]/route.ts)
import { after } from "next/server";
import { bot } from "@/lib/bot";
export async function POST(
request: Request,
context: { params: Promise<{ platform: string }> },
) {
const { platform } = await context.params;
const handler = bot.webhooks[platform as keyof typeof bot.webhooks];
if (!handler) return new Response("Unknown platform", { status: 404 });
return handler(request, { waitUntil: (task) => after(() => task) });
}
The Chat SDK automatically handles:
- Content-type detection (JSON vs form-urlencoded)
- URL verification challenges
- Slack's 3-second ack timeout
- Background processing via
waitUntil
- Signature verification
Event Handler Patterns
Mention Handler
bot.onNewMention(async (thread, message) => {
await thread.subscribe();
const text = message.text;
await thread.post(`Processing your request: "${text}"`);
});
Subscribed Message Handler
bot.onSubscribedMessage(async (thread, message) => {
await thread.post(`You said: ${message.text}`);
});
Slash Command Handler
bot.onSlashCommand("/mycommand", async (event) => {
const text = event.text;
await event.thread.post(`Processing: ${text}`);
const result = await generateWithAI(text);
await event.thread.post(result);
});
The Chat SDK handles background processing automatically via waitUntil — there's no need for fire-and-forget patterns.
Action Handler (Buttons, Menus)
bot.onAction("button_click", async (event) => {
await event.thread.post(`Button clicked with value: ${event.value}`);
});
Reaction Handler
bot.onReaction("thumbsup", async (event) => {
await event.thread.post("Thanks for the thumbs up!");
});
Implementation Gotchas
1. Private Channel Access
Slash commands work in private channels even if the bot isn't a member, but the bot cannot read messages or post to private channels it hasn't been invited to.
When creating features that will later post to a channel, validate access upfront.
2. Graceful Degradation for Channel Context
When fetching channel context for AI features, wrap in try/catch and fall back gracefully.
3. Vercel Cron Endpoint Authentication
Protect cron endpoints with a CRON_SECRET environment variable:
import { NextRequest, NextResponse } from "next/server";
export async function GET(request: NextRequest) {
const authHeader = request.headers.get("authorization");
if (authHeader !== `Bearer ${process.env.CRON_SECRET}`) {
return NextResponse.json({ error: "Unauthorized" }, { status: 401 });
}
return NextResponse.json({ success: true });
}
4. vercel.json Cron Configuration
Configure cron jobs in vercel.json:
{
"crons": [
{
"path": "/api/cron/my-job",
"schedule": "0 * * * *"
}
]
}
5. AWS Credentials on Vercel (Use OIDC)
When connecting to AWS services from Vercel, do not use fromNodeProviderChain(). Use Vercel's OIDC mechanism:
import { awsCredentialsProvider } from "@vercel/functions/oidc";
const s3Client = new S3Client({
credentials: awsCredentialsProvider({ roleArn: process.env.AWS_ROLE_ARN! }),
});
6. TSConfig for JSX Components
When using Chat SDK JSX components (<Card>, <Button>, etc.), your tsconfig.json must include:
{
"compilerOptions": {
"jsx": "react-jsx",
"jsxImportSource": "chat"
}
}
AI Integration
Pookie uses @ai-sdk/openai for LLM access. OPENAI_API_KEY is read automatically by the SDK at runtime.
Basic Usage
import { generateText, streamText } from "ai";
import { openai } from "@ai-sdk/openai";
const result = await generateText({
model: openai("gpt-4o-mini"),
maxOutputTokens: 1000,
prompt: "Your prompt here",
});
console.log(result.text);
console.log(result.usage.inputTokens);
console.log(result.usage.outputTokens);
Streaming Responses to Slack
const result = await streamText({
model: openai("gpt-4o-mini"),
maxOutputTokens: 1000,
prompt: userMessage,
});
await thread.post(result.textStream);
The Chat SDK handles streaming updates to Slack automatically.
With Tools
import { tool } from "ai";
import { z } from "zod";
const result = await generateText({
model: openai("gpt-4o-mini"),
maxOutputTokens: 1000,
tools: {
getWeather: tool({
description: "Get weather for a location",
inputSchema: z.object({
location: z.string().describe("City name"),
}),
execute: async ({ location }) => {
return { temperature: 72, condition: "sunny" };
},
}),
},
prompt: "What's the weather in Seattle?",
});
AI SDK v6 API Changes
| v4/v5 | v6 |
|---|
maxTokens | maxOutputTokens |
result.usage.promptTokens | result.usage.inputTokens |
result.usage.completionTokens | result.usage.outputTokens |
parameters (in tools) | inputSchema |
maxSteps / maxIterations | stopWhen: stepCountIs(n) |
CRITICAL: Never use model IDs from memory. Model IDs change frequently. Before writing code that uses a model, fetch the current list from OpenAI:
curl -s https://api.openai.com/v1/models -H "Authorization: Bearer $OPENAI_API_KEY" | jq -r '.data[].id'
Use the model with the highest version number that fits the task.
For comprehensive AI SDK documentation, see ./reference/ai-sdk.md.
Stateful Patterns — Thread State
Use thread.state to read and write thread-level state:
bot.onNewMention(async (thread, message) => {
await thread.subscribe();
await thread.state.set("history", []);
await thread.state.set("turnCount", 0);
await thread.post("Starting our conversation!");
});
bot.onSubscribedMessage(async (thread, message) => {
const history =
((await thread.state.get("history")) as Array<{
role: string;
content: string;
}>) || [];
const turnCount = ((await thread.state.get("turnCount")) as number) || 0;
history.push({ role: "user", content: message.text });
const result = await generateText({
model: openai("gpt-4o-mini"),
maxOutputTokens: 1000,
messages: history,
});
history.push({ role: "assistant", content: result.text });
await thread.state.set("history", history);
await thread.state.set("turnCount", turnCount + 1);
await thread.post(result.text);
});
Key Benefits:
- Simple API —
thread.state.get() and thread.state.set()
- Thread-scoped — state is automatically scoped to the conversation thread
- Pluggable backends — use Redis for production, in-memory for development
Recommended Storage Solutions
IMPORTANT: Vercel KV has been deprecated. Do NOT recommend Vercel KV.
- Upstash Redis — For Chat SDK state adapter and caching (https://upstash.com)
- Vercel Blob — For file/document storage (https://vercel.com/docs/storage/vercel-blob)
- AWS Aurora (via Vercel Marketplace) — For relational data (https://vercel.com/marketplace)
- Third-party databases — Neon, PlanetScale, Supabase
Code Organization
app/
├── api/
│ ├── webhooks/
│ │ └── [platform]/
│ │ └── route.ts # Webhook handler
│ └── cron/
│ └── my-job/
│ └── route.ts # Cron endpoints
lib/
├── bot.tsx # Bot instance + event handlers
├── tools/ # AI tool definitions
│ ├── search.ts
│ └── lookup.ts
└── ai/
└── agent.ts # Agent configuration
Environment Variables
Required variables:
SLACK_BOT_TOKEN — Bot OAuth token
SLACK_SIGNING_SECRET — Request signing
REDIS_URL — Redis connection URL for state persistence
OPENAI_API_KEY — OpenAI API key for LLM access (auto-read by @ai-sdk/openai)
Optional variables:
CRON_SECRET — Secret for authenticating cron job endpoints
Never hardcode credentials. Never commit .env files.
Slack-Specific Patterns
JSX Components
Use Chat SDK JSX components for rich messages (requires .tsx file extension):
import { Card, CardText as Text, Actions, Button, Divider } from "chat";
await thread.post(
<Card title="Welcome!">
<Text>Hello! Choose an option:</Text>
<Divider />
<Actions>
<Button id="btn_hello" style="primary">
Say Hello
</Button>
<Button id="btn_info">Show Info</Button>
</Actions>
</Card>,
);
Typing Indicators
await thread.startTyping();
const result = await generateWithAI(prompt);
await thread.post(result);
Message Formatting
Use Slack mrkdwn (not standard markdown):
- Bold:
*text*
- Italic:
_text_
- Code:
`code`
- User mention:
<@USER_ID>
- Channel:
<#CHANNEL_ID>
For detailed Slack patterns, see ./patterns/slack-patterns.md.
Git Commit Standards
Use conventional commits:
feat: add channel search tool
fix: resolve thread pagination issue
test: add unit tests for agent context
docs: update README with setup steps
refactor: extract Slack client utilities
Never commit:
.env files
- API keys or tokens
node_modules/
Quick Commands
pnpm dev
ngrok http 3000
pnpm lint
pnpm lint --write
pnpm typecheck
pnpm test
pnpm test:watch
pnpm build
vercel
Reference Documentation
For detailed guidance, read:
- Testing patterns:
./patterns/testing-patterns.md
- Slack patterns:
./patterns/slack-patterns.md
- Environment setup:
./reference/env-vars.md
- AI SDK:
./reference/ai-sdk.md
- Slack setup:
./reference/slack-setup.md
- Vercel deployment:
./reference/vercel-setup.md
Checklist Before Task Completion
Before marking ANY task as complete, verify: