XProLane

Turn X Pro into a signal dashboard.

Open-source X Pro setup assistant for builders, founders, and creators — generate X Pro columns, search queries, audience maps, lists, daily engagement workflows, and launch monitoring plans.

Why XProLane

Most people use X randomly. XProLane turns X Pro into a focused signal dashboard.

• No X API required — works entirely offline
• Local-first — your data stays on your machine
• Deterministic — same input, same output, every time
• Copy-ready — output is formatted for direct use in X Pro

How it works

Niche + goals + product
        ↓
XProLane setup generator
        ↓
Columns + searches + lists + workflow
        ↓
X Pro signal dashboard
        ↓
SkillLane / x-agent optional integrations

Install

npm install -g @talocode/xprolane

Or try without installing:

npx @talocode/xprolane@latest demo

Python:

pip install talocode-xprolane

Quickstart

xprolane init
xprolane setup --niche ai-builders --product ScreenLane --goals grow-audience,launch-product --minutes 30 --save
xprolane queries --niche ai-builders --product ScreenLane
xprolane workflow --niche ai-builders --minutes 30
xprolane export-skill --setup-id <id> --out ./xpro-skill

Setup generator

Generate a complete X Pro setup plan:

xprolane setup --niche ai-builders --product ScreenLane --goals grow-audience,launch-product --minutes 30

Output includes:

• Column plan with exact search queries
• Search query set for all goals
• List and account suggestion format
• Daily engagement workflow
• Launch monitoring plan
• Content angles
• Profile checklist
• Engagement rules

Niche/audience planner

xprolane niche ai-builders
xprolane niche custom --audience "Nigerian students learning AI" --goals grow-audience

Built-in niches: ai-builders, indie-hackers, founders, developers, traders, educators, students, local-businesses.

X Pro column planner

xprolane columns --niche ai-builders --goals grow-audience --keywords "AI agent,MCP"

Generates column types: Customer Pain, Builder Peers, Competitor Signals, Launch Monitoring, Learning Feed, Market News, Reply Opportunities, Brand Mentions.

Search query generator

xprolane queries --niche ai-builders --keywords "AI agent,MCP" --json

Query categories: pain discovery, buying intent, competitor monitoring, launch monitoring, trend monitoring, support keywords, community conversations, partnership opportunities.

List/account suggestion format

xprolane lists --niche ai-builders

Generates list categories and discovery queries for finding the right accounts to follow and engage with.

Daily engagement workflow

xprolane workflow --niche ai-builders --minutes 30

Supported budgets: 15, 30, 45, 60 minutes.

Launch monitoring

xprolane launch --product ScreenLane --niche ai-builders

Generates pre-launch, launch day, and post-launch query sets plus response playbook.

Profile checklist

xprolane profile --role founder --niche ai-builders --product ScreenLane

CLI

Full CLI reference: docs/CLI.md

All 21 commands: init, setup, niche, columns, queries, lists, workflow, launch, profile, show, list, export, export-skill, skilllane, x-agent, serve, mcp, doctor, demo, config.

SDK

import { XProLaneClient } from "@talocode/xprolane";

const client = new XProLaneClient();
const plan = client.generateSetup({
  niche: 'ai-builders',
  goals: ['grow-audience', 'launch-product'],
  products: ['ScreenLane'],
  dailyTimeBudgetMinutes: 30,
});

Full SDK reference: docs/SDK.md

API

xprolane serve
curl http://localhost:3100/health
curl -X POST http://localhost:3100/v1/xprolane/setup -H 'Content-Type: application/json' -d '{"niche":"ai-builders","goals":["grow-audience"]}'

Full API reference: docs/API.md

MCP tools

xprolane mcp

13 MCP tools: xprolane_setup, xprolane_niche, xprolane_columns, xprolane_queries, xprolane_lists, xprolane_workflow, xprolane_launch, xprolane_profile, xprolane_export_skill, xprolane_skilllane_status, xprolane_xagent_status, xprolane_doctor, xprolane_demo.

Full MCP reference: docs/MCP.md

Python package

pip install talocode-xprolane
xprolane-py demo

SkillLane integration

Optional. Export your setup as a SkillLane-compatible skill:

xprolane export-skill --setup-id <id> --out ./xpro-skill

SkillLane is optional. Install with: npm install -g @talocode/skilllane.

x-agent integration

Optional. Score posts, draft replies, analyze text:

xprolane x-agent status
xprolane x-agent score --text "Looking for an AI agent tool"

x-agent is optional. Install with: npm install -g @talocode/x-agent.

Storage

All data stored locally in ~/.xprolane/:

~/.xprolane/
  config.json
  setups/<setup-id>.json
  templates/
  exports/

No remote database. No telemetry.

Security/privacy

• Local-first: no data leaves your machine
• No API keys required for core features
• No X API access required
• No remote database
• See docs/SECURITY.md

Talocode ecosystem

| Product | Description | |---------|-------------| | Tera | AI chat, writing, and coding API | | Codra | Code generation and review | | GateLane | API gateway and rate limiting | | ContextLane | Context management | | ScreenLane | Screen recording and sharing | | MemoryLane | Memory and knowledge management | | x-agent | X/Twitter intelligence for agents | | SkillLane | AI skill pack management | | XProLane | (this repo) X Pro setup assistant |

More: github.com/talocode · talocode.site

Demo video

See demo/ for storyboard, script, and captions.

xprolane demo

Roadmap

See docs/ROADMAP.md.

Limitations

• v0.1 generates setup plans and workflows; it does not automatically configure X Pro
• No X API required for core features
• Account suggestions are category/criteria-based unless x-agent integration returns real data
• x-agent integration is optional
• SkillLane integration is optional
• Search queries should be copied manually into X Pro
• Growth results depend on consistency, niche quality, and execution

Contributing

1. Fork the repo
2. Create a feature branch
3. Make your changes
4. Run tests: npm test
5. Submit a pull request

License

MIT