slack-agent

vercel-labs/slack-agent-skill · updated Apr 8, 2026

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$npx skills add https://github.com/vercel-labs/slack-agent-skill --skill slack-agent
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summary

This skill supports two frameworks for building Slack agents:

skill.md

Slack Agent Development Skill

This skill supports two frameworks for building Slack agents:

  • Chat SDK (Recommended for new projects) — chat + @chat-adapter/slack
  • Bolt for JavaScript (For existing Bolt projects) — @slack/bolt + @vercel/slack-bolt

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:

  1. No package.json with chat or @slack/bolt → Treat as new, start Phase 1
  2. Has project but no customized manifest.json → Start Phase 2
  3. Has project but no .env file → Start Phase 3
  4. Has .env but not tested → Start Phase 4
  5. Tested but not deployed → Start Phase 5
  6. Otherwise → Provide general assistance using this skill's patterns

Framework Detection

Detect which framework the project uses:

  • package.json contains "chat" → Chat SDK project
  • package.json contains "@slack/bolt" → Bolt project
  • Neither detected → New project, recommend Chat SDK (offer Bolt as alternative)

Store the detected framework and use it to show the correct patterns throughout the wizard and development guidance.

Wizard Phases

The wizard is located in ./wizard/ with these phases:

  • 1-project-setup.md - Understand purpose, choose framework, 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:

  1. Read ./wizard/1-project-setup.md first
  2. Ask the user what kind of agent they want to build
  3. Offer framework choice (Chat SDK recommended, Bolt as alternative)
  4. Generate a custom implementation plan using ./reference/agent-archetypes.md
  5. Present the plan for approval (Phase 1b) BEFORE scaffolding the project
  6. Only proceed to scaffold after the plan is approved

Framework Selection Guide

Aspect Chat SDK Bolt for JavaScript
Best for New projects Existing Bolt codebases
Packages chat, @chat-adapter/slack, @chat-adapter/state-redis @slack/bolt, @vercel/slack-bolt
Server Next.js App Router Nitro (H3-based)
Event handling bot.onNewMention(), bot.onSubscribedMessage() app.event(), app.command(), app.message()
Webhook route app/api/webhooks/[platform]/route.ts server/api/slack/events.post.ts
Message posting thread.post("text") / thread.post(<Card>...) client.chat.postMessage({ channel, text, blocks })
UI components JSX: <Card>, <Button>, <Actions> Raw Block Kit JSON
State @chat-adapter/state-redis / thread.state Manual / Vercel Workflow
Config new Chat({ adapters: { slack } }) new App({ token, signingSecret, receiver })

General Development Guidance

You are working on a Slack agent project. Follow these mandatory practices for all code changes.

Project Stack

If using Chat SDK

  • 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/gateway
  • Linting: Biome
  • Package Manager: pnpm
{
  "dependencies": {
    "ai": "^6.0.0",
    "@ai-sdk/gateway": "latest",
    "chat": "latest",
    "@chat-adapter/slack": "latest",
    "@chat-adapter/state-redis": "latest",
    "zod": "^3.x",
    "next": "^15.x"
  }
}

If using Bolt for JavaScript

  • Server: Nitro (H3-based) with file-based routing
  • Slack SDK: @vercel/slack-bolt for serverless Slack apps (wraps Bolt for JavaScript)
  • AI: AI SDK v6 with @ai-sdk/gateway
  • Workflows: Workflow DevKit for durable execution
  • Linting: Biome
  • Package Manager: pnpm
{
  "dependencies": {
    "ai": "^6.0.0",
    "@ai-sdk/gateway": "latest",
    "@slack/bolt": "^4.x",
    "@vercel/slack-bolt": "^1.0.2",
    "zod": "^3.x"
  }
}

Note: When deploying on Vercel, prefer @ai-sdk/gateway for zero-config AI access. Use direct provider SDKs (@ai-sdk/openai, @ai-sdk/anthropic, etc.) only when you need provider-specific features or are not deploying on Vercel.


Quality Standards (MANDATORY)

These quality requirements MUST be followed for every code change. There are no exceptions.

After EVERY File Modification

  1. 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
  2. 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:

# 1. TypeScript compilation - must pass
pnpm typecheck

# 2. Linting - must pass with no errors
pnpm lint

# 3. Tests - all tests must pass
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.

If using Chat SDK

  • Location: Co-located *.test.ts files or lib/__tests__/
  • Framework: Vitest
  • Coverage: All exported functions must have tests

If using Bolt for JavaScript

  • Location: Co-located *.test.ts files or server/__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)

If using Chat SDK

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

If using Bolt for JavaScript

Use @vercel/slack-bolt to handle all Slack events. This package automatically handles:

  • Content-type detection (JSON vs form-urlencoded)
  • URL verification challenges
  • 3-second ack timeout (built-in ackTimeoutMs: 3001)
  • Background processing via Vercel Fluid Compute's waitUntil

Bolt App Setup (server/bolt/app.ts)

how to use slack-agent

How to use slack-agent on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add slack-agent
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/vercel-labs/slack-agent-skill --skill slack-agent

The skills CLI fetches slack-agent from GitHub repository vercel-labs/slack-agent-skill and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/slack-agent

Reload or restart Cursor to activate slack-agent. Access the skill through slash commands (e.g., /slack-agent) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.830 reviews
  • Shikha Mishra· Dec 24, 2024

    Solid pick for teams standardizing on skills: slack-agent is focused, and the summary matches what you get after install.

  • Advait Haddad· Dec 24, 2024

    Keeps context tight: slack-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Yash Thakker· Nov 15, 2024

    We added slack-agent from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Min Dixit· Nov 15, 2024

    Registry listing for slack-agent matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Dhruvi Jain· Oct 6, 2024

    slack-agent fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Xiao Srinivasan· Oct 6, 2024

    slack-agent reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Olivia Iyer· Sep 25, 2024

    slack-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arjun Wang· Sep 17, 2024

    Solid pick for teams standardizing on skills: slack-agent is focused, and the summary matches what you get after install.

  • Anaya Srinivasan· Aug 16, 2024

    Solid pick for teams standardizing on skills: slack-agent is focused, and the summary matches what you get after install.

  • Isabella Okafor· Aug 8, 2024

    slack-agent has been reliable in day-to-day use. Documentation quality is above average for community skills.

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