
karpathytalk-community
Run and interact with KarpathyTalk, an open markdown-based developer social network with GitHub auth, SQLite, and an LLM-friendly JSON/markdown API.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/reason-machines/trending-skills --skill karpathytalk-community- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads karpathytalk-community automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
KarpathyTalk Community Skill
Skill by ara.so — Daily 2026 Skills collection.
KarpathyTalk is a Go-based developer social network (Twitter × GitHub Gists) where posts are plain markdown, the social layer supports likes/reposts/follows/replies, and all data is openly accessible via JSON and markdown APIs — designed for both humans and LLM agents.
What It Does
- GitHub OAuth sign-in (no new credentials)
- Posts are GFM markdown with syntax-highlighted code blocks and image uploads
- Social features: likes, reposts, quote posts, replies, follows
- REST API returns JSON (for agents/code) or markdown (for humans)
- Single Go binary + SQLite +
uploads/directory — trivial to self-host - Built with: Go, SQLite, htmx, goldmark
Installation & Local Setup
1. Create a GitHub OAuth App
Go to GitHub → Settings → Developer settings → OAuth Apps → New OAuth App:
| Field | Value |
|---|---|
| Application name | KarpathyTalk |
| Homepage URL | http://localhost:8080 |
| Authorization callback URL | http://localhost:8080/auth/callback |
Save the Client ID and Client Secret.
2. Clone & Build
git clone https://github.com/karpathy/KarpathyTalk.git
cd KarpathyTalk
go build -o karpathytalk ./cmd/karpathytalk
3. Configure Environment
export GITHUB_CLIENT_ID=$GITHUB_CLIENT_ID
export GITHUB_CLIENT_SECRET=$GITHUB_CLIENT_SECRET
export BASE_URL=http://localhost:8080 # optional, defaults to this
4. Run
./karpathytalk
# or with options:
./karpathytalk -addr :9090 -db ./data/karpathytalk.db
Visit http://localhost:8080.
CLI Flags
-addr string HTTP listen address (default ":8080")
-db string SQLite database path (default "karpathytalk.db")
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
GITHUB_CLIENT_ID | ✅ | — | GitHub OAuth client ID |
GITHUB_CLIENT_SECRET | ✅ | — | GitHub OAuth client secret |
BASE_URL | ❌ | http://localhost:8080 | Public URL of the deployed app |
Deployment (Production)
Build & Copy
# Build binary
go build -o karpathytalk ./cmd/karpathytalk
# Copy to server (adjust user/host)
scp karpathytalk schema.sql user@yourserver:~/karpathytalk/
scp -r templates static user@yourserver:~/karpathytalk/
Run on Server
ssh user@yourserver
cd ~/karpathytalk
export GITHUB_CLIENT_ID=$GITHUB_CLIENT_ID
export GITHUB_CLIENT_SECRET=$GITHUB_CLIENT_SECRET
export BASE_URL=https://yourdomain.com
./karpathytalk -addr :8080
Caddy TLS (recommended)
yourdomain.com {
reverse_proxy localhost:8080
}
nginx TLS
server {
listen 443 ssl;
server_name yourdomain.com;
ssl_certificate /etc/letsencrypt/live/yourdomain.com/fullchain.pem;
ssl_certificate_key /etc/letsencrypt/live/yourdomain.com/privkey.pem;
location / {
proxy_pass http://localhost:8080;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
}
systemd Service
[Unit]
Description=KarpathyTalk
After=network.target
[Service]
WorkingDirectory=/home/deploy/karpathytalk
ExecStart=/home/deploy/karpathytalk/karpathytalk -addr :8080
Restart=always
Environment=GITHUB_CLIENT_ID=$GITHUB_CLIENT_ID
Environment=GITHUB_CLIENT_SECRET=$GITHUB_CLIENT_SECRET
Environment=BASE_URL=https://yourdomain.com
[Install]
WantedBy=multi-user.target
API Usage
All data is open — no auth required for reads. The API returns JSON for programmatic access and markdown for human/agent reading.
Fetch Posts as JSON
# Timeline / recent posts
curl https://karpathytalk.com/api/posts
# Single post
curl https://karpathytalk.com/api/posts/{postID}
# User's posts
curl https://karpathytalk.com/api/users/{username}/posts
Fetch Posts as Markdown
# Human/agent-readable markdown
curl https://karpathytalk.com/api/posts/{postID}.md
Go Agent Example — Read Timeline
package main
import (
"encoding/json"
"fmt"
"io"
"net/http"
)
type Post struct {
ID int64 `json:"id"`
Username string `json:"username"`
Content string `json:"content"`
Likes int `json:"likes"`
Reposts int `json:"reposts"`
CreatedAt string `json:"created_at"`
}
func fetchTimeline(baseURL string) ([]Post, error) {
resp, err := http.Get(baseURL + "/api/posts")
if err != nil {
return nil, err
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
if err != nil {
return nil, err
}
var posts []Post
if err := json.Unmarshal(body, &posts); err != nil {
return nil, err
}
return posts, nil
}
func main() {
posts, err := fetchTimeline("https://karpathytalk.com")
if err != nil {
panic(err)
}
for _, p := range posts {
fmt.Printf("[%s] %s (👍 %d)\n", p.Username, p.Content[:min(80, len(p.Content))], p.Likes)
}
}
func min(a, b int) int {
if a < b {
return a
}
return b
}
Go Agent Example — Fetch User Posts as Markdown
package main
import (
"fmt"
"io"
"net/http"
)
func fetchUserPostsMarkdown(baseURL, username string) (string, error) {
url := fmt.Sprintf("%s/api/users/%s/posts.md", baseURL, username)
resp, err := http.Get(url)
if err != nil {
return "", err
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
return string(body), err
}
func main() {
md, err := fetchUserPostsMarkdown("https://karpathytalk.com", "karpathy")
if err != nil {
panic(err)
}
fmt.Println(md)
}
Content Limits
| Content Type | Max Length | Rate Limit |
|---|---|---|
| Posts | 10,000 characters | 30 per hour |
| Replies | 5,000 characters | 60 per hour |
| Images | 5 MB | PNG/JPEG/GIF/WebP only |
Database — Direct SQLite Access
The SQLite database is a single file. You can query it directly for analytics, backups, or migrations:
# Open database
sqlite3 karpathytalk.db
# List tables
.tables
# Recent posts
SELECT username, substr(content, 1, 80), created_at
FROM posts
ORDER BY created_at DESC
LIMIT 20;
# Most liked posts
SELECT username, likes, substr(content, 1, 60)
FROM posts
ORDER BY likes DESC
LIMIT 10;
# User follower counts
SELECT username, COUNT(*) as followers
FROM follows
GROUP BY username
ORDER BY followers DESC;
Backup
# Simple file copy (safe while running with WAL mode)
cp karpathytalk.db karpathytalk.db.backup
# Or use sqlite3 online backup
sqlite3 karpathytalk.db ".backup karpathytalk_backup.db"
Project Structure
KarpathyTalk/
├── cmd/
│ └── karpathytalk/ # main entrypoint
├── templates/ # HTML templates (htmx-powered)
├── static/ # CSS, JS assets
├── uploads/ # User image uploads
├── schema.sql # SQLite schema
└── karpathytalk.db # Database (created at runtime)
Common Patterns
Pattern: Agent That Monitors New Posts
package main
import (
"encoding/json"
"fmt"
"net/http"
"time"
)
type Post struct {
ID int64 `json:"id"`
Username string `json:"username"`
Content string `json:"content"`
CreatedAt string `json:"created_at"`
}
func pollNewPosts(baseURL string, sinceID int64) ([]Post, error) {
url := fmt.Sprintf("%s/api/posts?since_id=%d", baseURL, sinceID)
resp, err := http.Get(url)
if err != nil {
return nil, err
}
defer resp.Body.Close()
var posts []Post
json.NewDecoder(resp.Body).Decode(&posts)
return posts, nil
}
func main() {
var lastSeenID int64 = 0
for {
posts, err := pollNewPosts("https://karpathytalk.com", lastSeenID)
if err != nil {
fmt.Println("Error:", err)
} else {
for _, p := range posts {
fmt.Printf("New post by @%s: %s\n", p.Username, p.Content[:min(60, len(p.Content))])
if p.ID > lastSeenID {
lastSeenID = p.ID
}
}
}
time.Sleep(30 * time.Second)
}
}
func min(a, b int) int {
if a < b { return a }
return b
}
Pattern: Embedding KarpathyTalk Content in an LLM Prompt
package main
import (
"fmt"
"io"
"net/http"
)
// Fetch markdown content to inject into an LLM system prompt or context window
func getContextForLLM(baseURL, username string) (string, error) {
url := fmt.Sprintf("%s/api/users/%s/posts.md", baseURL, username)
resp, err := http.Get(url)
if err != nil {
return "", err
}
defer resp.Body.Close()
body, err := io.ReadAll(resp.Body)
return string(body), err
}
func main() {
context, _ := getContextForLLM("https://karpathytalk.com", "karpathy")
systemPrompt := fmt.Sprintf(`You are a helpful assistant. Here are recent posts from the community:
%s
Answer questions about these posts.`, context)
fmt.Println(systemPrompt)
}
Troubleshooting
| Problem | Cause | Fix |
|---|---|---|
GITHUB_CLIENT_ID not set | Missing env var | Export GITHUB_CLIENT_ID before running |
| OAuth callback fails | Callback URL mismatch | Ensure GitHub OAuth App callback URL exactly matches BASE_URL/auth/callback |
| Binary not found after build | Wrong output path | Run go build -o karpathytalk ./cmd/karpathytalk from repo root |
templates: no such file | Missing templates dir | Run the binary from the repo root, or copy templates/ and static/ next to the binary |
| Database locked | Concurrent writers | SQLite WAL mode is set by default; avoid multiple binary instances against same .db |
| Images not serving | Missing uploads/ dir | The directory is created automatically on first upload; check write permissions |
| Port already in use | Another process on 8080 | Use -addr :9090 to change the port |
Check the App is Running
curl -I http://localhost:8080/
# Expect: HTTP/1.1 200 OK
Rebuild After Code Changes
go build -o karpathytalk ./cmd/karpathytalk && ./karpathytalk
Run Tests
go test ./...
FAQ
What does the karpathytalk-community skill do?
Run and interact with KarpathyTalk, an open markdown-based developer social network with GitHub auth, SQLite, and an LLM-friendly JSON/markdown API.
How do I install karpathytalk-community?
Run npx skills add https://github.com/reason-machines/trending-skills --skill karpathytalk-community in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/karpathytalk-community/ (personal) or .claude/skills/karpathytalk-community/ (project).
Which AI agents can use karpathytalk-community?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is karpathytalk-community safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains karpathytalk-community?
It is published by reason-machines in reason-machines/trending-skills. It has 598 recorded installs.
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