slack-agent▌
vercel-labs/slack-agent-skill · updated Apr 8, 2026
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This skill supports two frameworks for building Slack agents:
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:
- No
package.jsonwithchator@slack/bolt→ Treat asnew, start Phase 1 - Has project but no customized
manifest.json→ Start Phase 2 - Has project but no
.envfile → Start Phase 3 - Has
.envbut not tested → Start Phase 4 - Tested but not deployed → Start Phase 5
- Otherwise → Provide general assistance using this skill's patterns
Framework Detection
Detect which framework the project uses:
package.jsoncontains"chat"→ Chat SDK projectpackage.jsoncontains"@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 plan1b-approve-plan.md- Present plan for user approval before scaffolding2-create-slack-app.md- Customize manifest, create app in Slack3-configure-environment.md- Set up .env with credentials4-test-locally.md- Dev server + ngrok tunnel5-deploy-production.md- Vercel deployment6-setup-testing.md- Vitest configuration
IMPORTANT: For new projects, you MUST:
- Read
./wizard/1-project-setup.mdfirst - Ask the user what kind of agent they want to build
- Offer framework choice (Chat SDK recommended, Bolt as alternative)
- 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
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/slackfor Slack bot functionality - State:
@chat-adapter/state-redisfor 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-boltfor 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
-
Run linting immediately:
pnpm lint- If errors exist, run
pnpm lint --writefor auto-fixes - Manually fix remaining issues
- Re-run
pnpm lintto verify
- If errors exist, run
-
Check for corresponding test file:
- If you modified
foo.ts, check iffoo.test.tsexists - If no test file exists and the file exports functions, create one
- If you modified
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.tsfiles orlib/__tests__/ - Framework: Vitest
- Coverage: All exported functions must have tests
If using Bolt for JavaScript
- Location: Co-located
*.test.tsfiles orserver/__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 on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches slack-agent from GitHub repository vercel-labs/slack-agent-skill and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★30 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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