DEV Community: Hélder Vasconcelos

Built a Visual Workbench Because Managing Claude Code Skills Was Driving Me Crazy

Hélder Vasconcelos — Sat, 14 Mar 2026 11:07:02 +0000

It started with a folder full of markdown files.

I'd been using Claude Code daily for months. It became my go-to coding partner pretty quickly. Early on, I discovered Skills: markdown files with YAML frontmatter that you drop into ~/.claude/skills/ to teach Claude how you want things done. Write a SKILL.md, describe when it should trigger, add your instructions, and Claude suddenly knows your deployment pipeline, your coding standards, your project's weird quirks.

I went deep. I wrote skills for everything. Code review guidelines. Database migration patterns. Component scaffolding. API endpoint boilerplate. Test generation strategies. Each one made Claude Code sharper, more tuned to how I actually work.

Then the problems started. 😅

The Skill Management Problem Nobody Talks About 🤯

Five skills in a folder? Totally fine. Thirty skills spread across multiple projects, each with slightly different versions? Absolute nightmare.

I kept hitting the same walls. I'd edit a skill's YAML frontmatter, deploy it, then discover a typo broke the trigger pattern. No validation anywhere. I'd copy a skill between projects, tweak it, then completely forget which version was current. No version history. I wanted to test whether a skill actually produced the output I expected before shipping it. No testing sandbox.

Sharing was the worst part. A teammate would ask for my code review skill. I'd send the file over. They'd ask which model it was tuned for. I couldn't remember. They'd deploy it, get so-so results, and write off skills entirely.

I was spending more time managing skills than writing code. I was using an AI agent to be more productive, but the tooling around that agent kept dragging me back. 🙃

Building What I Needed 🔨

So I did what any developer does when the tooling falls short: built my own.

The idea was straightforward. A visual editor where I can see YAML frontmatter and markdown instructions side by side. Real-time validation so I catch errors before deployment. A way to test a skill against actual models with streaming responses, so I can tweak the instructions until the output matches what I want. And when it's ready, one-click deploy instead of manually copying files around.

That project became uberSKILLS ⚡ an open-source visual workbench for designing, testing, and deploying agent skills.

The first version was rough. A Next.js app with a basic editor and a deploy button that wrote files to ~/.claude/skills/. But even that bare-bones version saved me hours. No more YAML syntax errors. No more blind deployments. No more wondering if a skill would actually work.

From Side Project to Multi-Agent Workbench 🚀

This is where things got interesting.

While I was building uberSKILLS for Claude Code, the agent ecosystem blew up. Cursor shipped their rules system. GitHub Copilot added custom instructions. Windsurf launched with its own skill format. Gemini CLI showed up with agent configuration. Codex, OpenCode, Antigravity... suddenly there were eight major code agents, all supporting some form of persistent instructions.

The problem I'd solved for Claude Code? It existed everywhere. Every agent had its own directory structure, its own conventions, its own deployment path. Developers using multiple agents were maintaining duplicate sets of instructions with zero shared tooling. 😩

So uberSKILLS grew. Today it deploys to eight agents 🎯:

Claude Code
Cursor
GitHub Copilot
Windsurf
Gemini CLI
Codex
OpenCode
Antigravity

Write your skill once, pick your targets, deploy everywhere. The skill format is standardized (YAML frontmatter for metadata and triggers, markdown body for instructions) and the engine handles translation to each agent's expected structure.

This matters more than it might sound. If you've spent time crafting a detailed code review prompt that works great with Claude, you should be able to use that same work with Copilot or Cursor without rewriting anything. Your prompt engineering expertise should be portable. 🔄

What It Actually Does ⚙️

Three steps: create, test, deploy.

✏️ Create

You can go manual with the structured editor and fill in metadata fields (name, description, trigger patterns, tags, model preferences). Or open the AI chat, describe what you want in plain language, and let it generate a complete skill for you. The AI creation flow has a live preview panel so you can watch the SKILL.md update as you refine your description through conversation.

🧪 Test

This is where uberSKILLS really pays for itself. The multi-model sandbox lets you pick any model available through OpenRouter (Claude, GPT, Gemini, Llama, dozens more) and run your skill against it with streaming responses. You see output in real time, plus metrics: token counts, latency, time to first token. Tweak the instructions, test again, compare outputs across models, and actually feel confident a skill works before it touches a real project. Every test run gets saved too, so you can track how instruction changes affect output quality over time. 📊

🚀 Deploy

One click. Pick your target agents from a dropdown, hit deploy, and uberSKILLS writes the files to the correct directory for each agent. Status updates to "deployed" so you can see at a glance what's live and what's still in draft.

Beyond those three steps: there's a skills library with search, status filtering, and sorting. Version history tracks every edit so you can roll back any revision. Import and export lets you pull skills from zip files or directories, and share them with your team. Settings panel covers API key management, theme preferences, and data backup. 📦

The Technical Choices 🛠️

For the curious, here's the stack: Turborepo monorepo with pnpm. Next.js 15 on the App Router with React 19, shadcn/ui, and Tailwind CSS v4. SQLite through Drizzle ORM for the database, so no external database server needed. Everything runs locally. AI integration uses the Vercel AI SDK with the OpenRouter provider for multi-model support.

SQLite was a deliberate choice. uberSKILLS is local-first. Your skills, test history, API keys... all of it stays on your machine. The API key gets encrypted with AES-256-GCM before storage. No cloud dependency, no account to create, no data leaving your laptop. 🔒

Getting started is one command:

npx @uberskillsdev/uberskills

It creates a ~/.uberskills/data/ directory, sets up the database, runs migrations, generates an encryption secret, and launches at localhost:3000. No Docker, no cloning, no configuration ceremony. ✨

Why Skills Are the Multiplier Most Developers Ignore 💡

I talk to developers every week who use Claude Code or Copilot and have never written a single skill. They're leaving a ton of productivity on the table.

A well-written skill turns a general-purpose agent into a specialist. Without skills, you repeat the same context in every conversation. With skills, that context loads automatically based on trigger patterns. Your agent already knows your database conventions, your error handling patterns, your test philosophy, your deployment checklist... before you type a word.

The developers getting the most out of code agents are the ones who invest time teaching them. Skills are how you do the teaching. uberSKILLS is how you manage all that teaching without going crazy. 🧠

What's Next 🗺️

uberSKILLS is open source under MIT and free forever. The roadmap includes a community skill marketplace where developers can share and discover skills, collaborative editing for teams, and deeper integrations as new agents keep showing up.

The agent ecosystem moves fast. New agents ship every month, existing ones pick up new capabilities every week. But one thing stays consistent: developers who customize their agents outperform those who don't. A proper workbench for that customization isn't optional anymore. It's infrastructure.

If you're still managing agent skills by hand-editing markdown files and copying them between directories, try uberSKILLS. Your future self, the one who isn't debugging YAML indentation at midnight, will appreciate it. 😄

GitHub: github.com/uberskillsdev/uberskills

npm: npx @uberskillsdev/uberskills

Best Crypto Pricing API in 2026: A Developer's Comparison Guide

Hélder Vasconcelos — Thu, 12 Feb 2026 12:54:00 +0000

Choosing the best crypto pricing API in 2026 is harder than it should be. There are aggregators, exchange-native market data endpoints, real-time streaming services, and multi-asset platforms, each with trade-offs that only become obvious after you've committed to an integration.

This guide focuses specifically on pricing and market data: the APIs you use to read ticker prices, exchange rates, volumes, and market pair information. We're not comparing trade execution APIs, order management systems, or brokerage platforms. If you need to place orders, that's a different category entirely.

We compare 15+ crypto data APIs organized into four categories: aggregated data providers, exchange market data endpoints, on-chain feeds, and multi-asset financial platforms. For each, we cover pricing, rate limits, SDK quality, and real-world developer experience. At the end, you'll find a feature matrix and a decision framework to match your use case to the right API.

🔍 How We Evaluated These APIs

We evaluated each API across seven criteria that matter most to developers building production applications:

💰 Pricing. Free tier generosity, paid plan value, and hidden costs.
🚦 Rate limits. Requests per minute and daily caps at each tier.
⚡ Latency. Time from request to response under normal load.
📦 SDK quality. Official SDKs, TypeScript support, and code generation.
🌐 Exchange coverage. Number and quality of supported exchanges.
📖 Documentation. Accuracy, examples, and time-to-first-request.
🛡️ Reliability. Uptime track record and failure handling.

No single API wins every category. The right choice depends on whether you need broad coin coverage, low-latency price feeds, multi-asset support, or developer-friendly tooling.

📊 Aggregated Crypto Pricing APIs

Aggregators collect data from multiple exchanges and normalize it into a single interface. They're the most popular choice for portfolio trackers, dashboards, and applications that need broad market coverage.

CoinGecko

The most widely used free crypto API. CoinGecko covers 14,000+ coins and 1,100+ exchanges, making it the default choice when you need breadth. The free tier is genuinely usable at 30 requests/minute with no daily cap, and the documentation is solid.

The catch is performance. Response times regularly exceed 500ms, and the free tier has no SLA. The Pro plan at $129/month unlocks higher rate limits and faster responses, but that's a steep jump from free. The API design is also showing its age: endpoints return large payloads with mixed concerns, and there's no official TypeScript SDK.

🎯 Best for: Side projects, research tools, and applications that need the widest coin coverage regardless of latency.

CoinMarketCap

The industry standard for market cap rankings and coin metadata. CoinMarketCap's API powers most "top 100 coins" displays you see on the web. Data quality for major coins is excellent, and the taxonomy system (categories, tags) is unmatched.

The free tier is restrictive, 333 requests/day with 10,000 credits/month and the credit system makes it hard to predict actual usage costs. The Basic plan starts at $79/month. API responses are well-structured but the authentication model uses a custom header (X-CMC_PRO_API_KEY) instead of standard Bearer tokens.

🎯 Best for: Market cap displays, coin metadata, and content sites that need broad taxonomy data.

CryptoCompare

CryptoCompare differentiates with social and sentiment data alongside standard price feeds. If you need on-chain metrics, social volume, or developer activity scores, it's one of the few APIs that bundles these together.

, inconsistent parameter naming, limited filtering options, and documentation that hasn't kept pace with newer endpoints. The free tier allows 100,000 calls/month. Paid plans start at $79.99/month.

🎯 Best for: Analytics platforms that need sentiment and social data alongside price data.

CoinAPI

Enterprise grade with FIX protocol support, making it one of the few crypto APIs that speaks the language of traditional finance. CoinAPI covers 350+ exchanges, offers WebSocket feeds, and includes OHLCV data. It also provides comprehensive historical data going back years.

The free tier is essentially a sandbox. At 100 requests/day, it's impractical for anything beyond evaluation. Paid plans start at $79/month but scale quickly into the hundreds for production workloads. If you're building for institutional clients who need FIX protocol, CoinAPI is one of the few options available.

🎯 Best for: Institutional and enterprise applications, particularly those needing FIX protocol or deep historical data.

Nomics ☠️

A cautionary tale for anyone evaluating API providers. Nomics was a well-regarded crypto data API that shut down in 2023 after its acquisition by CoinGecko. Developers who had built on the platform had to migrate with little notice. It's worth remembering that API provider viability matters just as much as features.

NOWMarket API

A newer entrant providing crypto and NFT market data. NOWMarket covers the basics (tickers, OHLCV, market pairs) with a clean REST interface. The ecosystem is still limited: no official SDKs, sparse community, and thinner documentation than established alternatives.

🎯 Best for: Projects that need a lightweight alternative to the larger aggregators with NFT data included.

🏦 Exchange Market Data APIs

Every major exchange exposes public market data endpoints alongside their trading APIs. These are primarily designed for traders who also execute on that exchange, but many developers use them purely as price data sources. Here, we evaluate them strictly as market data providers.

Binance

The highest-volume exchange with the freshest price data. Binance's public market data endpoints (ticker prices, order book snapshots, recent trades) are free and don't require authentication. WebSocket streams deliver sub-100ms price updates and the rate limits are generous at 1,200 requests/minute for market data.

The complexity cost is real when you use them purely for data. Symbol formatting is non-standard (BTCUSDT instead of BTC/USDT). Response shapes differ between spot and futures. And you're locked into one exchange's view of the market, so if Binance has an outage, your price feed goes dark.

OKX

Clean market data API with good WebSocket support for real-time tickers. OKX provides solid coverage for derivatives pricing (funding rates, mark prices, open interest) which is useful for analytics dashboards. Documentation is clear, though English translations occasionally lag behind the Chinese originals.

Bybit

The cleanest API design among the major exchanges. Bybit's V5 API provides a unified market data interface across spot, derivatives, and options. Rate limits are reasonable, documentation is above average, and the WebSocket ticker streams are reliable.

MEXC

The go-to exchange for early altcoin listings. MEXC lists tokens faster than most competitors, which makes its market data API valuable for projects tracking emerging assets. Reliability is a concern though. Occasional data gaps and slower API responses make it risky as a primary price data source.

The trade-off with exchange market data APIs is clear: each gives you fast, deep data for that single exchange, but N exchanges means N integrations, N data formats, and N failure modes to handle. For applications that need a consolidated view of prices across exchanges (portfolio trackers, price comparison tools, arbitrage monitors), this approach doesn't scale.

⛓️ On-Chain Price Feeds

Bitquery

Bitquery takes a fundamentally different approach: GraphQL queries against blockchain data. You can query DEX trades, token transfers, and smart contract events directly from on-chain data across 40+ blockchains.

This is powerful for DeFi analytics and on-chain research, but it's not a replacement for centralized exchange price data. Pricing starts at $500+/month for meaningful usage, and query latency depends on blockchain indexing speed. If your primary need is CEX ticker prices and market data, Bitquery is the wrong tool.

🎯 Best for: On-chain analytics, DEX price tracking, and blockchain data exploration.

📈 Multi-Asset Pricing APIs

These platforms provide pricing data for stocks, forex, and crypto under one roof. They're appealing if you're building a multi-asset dashboard or portfolio tracker, but crypto price coverage is typically an afterthought.

Finnhub

Broad coverage across US stocks, forex, ETFs, and crypto, with a generous free tier at 60 requests/minute. The WebSocket feed is well-implemented for stocks. Crypto support covers major pairs from a handful of exchanges, but depth and freshness lag behind dedicated crypto APIs.

Twelve Data

Excellent time-series API for stocks and forex with crypto as an add-on. The API design is clean, documentation is thorough, and the Python SDK is well-maintained. Crypto coverage is limited to major pairs, and real-time updates depend on your plan tier. Free tier allows 800 requests/day.

Alpha Vantage

The classic free financial data API. Alpha Vantage supports crypto alongside stocks and forex, but the free tier allows just 25 requests per day. That's not enough for anything beyond occasional lookups. The premium tier ($49.99/month) bumps this to 75 requests/minute. Data coverage for crypto is shallow.

Marketstack

Stock-first with crypto as a secondary feature. Marketstack covers 70+ stock exchanges and 170,000+ tickers, but its crypto support is limited to a handful of pairs. Not recommended as a primary crypto data source.

If crypto is your primary use case, multi-asset APIs won't cut it. They're designed for equities with crypto bolted on. You'll hit coverage gaps, latency issues, and rate limits that don't account for crypto's 24/7 nature.

🗂️ Crypto Pricing API Comparison Table

API	Type	Free Tier	Starting Price	Exchanges	Real-Time	SDK	Latency
CoinGecko	Aggregator	30 req/min	$129/mo	1,100+	Polling	Community	~500ms
CoinMarketCap	Aggregator	333 req/day	$79/mo	600+	Polling	Official	~300ms
CryptoCompare	Aggregator	100K calls/mo	$79.99/mo	150+	WebSocket	Community	~400ms
CoinAPI	Aggregator	100 req/day	$79/mo	350+	WebSocket	Multi-lang	~200ms
Binance	Exchange	1,200 req/min	Free	1	WebSocket	Official	~50ms
OKX	Exchange	600 req/min	Free	1	WebSocket	Official	~60ms
Bybit	Exchange	600 req/min	Free	1	WebSocket	Official	~70ms
Finnhub	Multi-Asset	60 req/min	$49.99/mo	8	WebSocket	Multi-lang	~300ms
Twelve Data	Multi-Asset	800 req/day	$29/mo	5	Polling	Python	~350ms
Alpha Vantage	Multi-Asset	25 req/day	$49.99/mo	3	Polling	Community	~500ms
Bitquery	On-Chain	Limited	$500+/mo	DEXs	GraphQL	GraphQL	~1-5s
Luzia	Aggregator	100 req/min, 5K/day	$22.99/mo	5 (Binance, Coinbase, Kraken, OKX, Bybit)	WebSocket	TypeScript	~100ms

🧭 When to Use What: Decision Matrix

Use Case	Best Fit	Why
Portfolio tracker (multi-exchange)	CoinGecko, Luzia	Broad exchange coverage, unified price format
Real-time price dashboard	Luzia, Binance	WebSocket streaming, low latency
Market cap rankings and coin metadata	CoinMarketCap	Best taxonomy and metadata
Sentiment and social analytics	CryptoCompare	Unique social data included
Multi-exchange price aggregation on a budget	Luzia	5 exchanges, $22.99/mo Pro, generous free tier
AI agent / MCP integration	Luzia	Only crypto pricing API with a production MCP server
On-chain and DEX price data	Bitquery	Direct blockchain data
Multi-asset dashboard (stocks + crypto)	Finnhub, Twelve Data	Unified pricing across asset classes

🔥 Where Luzia Fits: A Developer-First Pricing API

Luzia is a newer entrant built specifically for crypto pricing and market data. It won't win on coin coverage (it doesn't track 14,000 altcoins) and it doesn't provide on-chain data. What it does focus on is delivering clean, normalized price data from multiple exchanges with a developer experience and agentic tooling that the incumbents don't offer.

🧰 TypeScript SDK

Install the SDK and fetch your first ticker in under a minute:

import { Luzia } from '@luziadev/sdk'

const luzia = new Luzia({
  apiKey: 'lz_your_api_key',
})

const ticker = await luzia.tickers.get('binance', 'BTC/USDT')
console.log(`BTC/USDT: $${ticker.last}`)

// Get all tickers for an exchange
const { tickers, total } = await luzia.tickers.list('binance', { limit: 50 })
console.log(`Found ${total} tickers`)

The SDK includes automatic retries with exponential backoff, typed error handling, and rate limit headers exposed on every response.

🤖 MCP Server for AI Assistants

Luzia ships a Model Context Protocol server that lets AI assistants like Claude query live price data. No other crypto API offers this today. Add it to Claude Desktop or Claude Code:

{
  "mcpServers": {
    "luzia": {
      "command": "/path/to/bun",
      "args": ["x", "@luziadev/mcp-server", "--stdio"],
      "env": {
        "LUZIA_API_KEY": "lz_your_api_key"
      }
    }
  }
}

Once connected, Claude has access to tools like get_ticker, get_tickers, get_exchanges, and get_markets, plus analytical prompts like analyze_price_movement and compare_exchanges. You can ask "What's the BTC price across all exchanges right now?" and get a real-time answer grounded in live data.

⚡ WebSocket Streaming

Pro plan users get real-time WebSocket streaming across all supported exchanges:

const ws = luzia.createWebSocket()

ws.on('connected', (info) => {
  console.log(`Connected (${info.tier}), max subs: ${info.limits.maxSubscriptions}`)
  ws.subscribe(['ticker:binance:BTC/USDT', 'ticker:coinbase:ETH/USDT'])
})

ws.on('ticker', (data) => {
  console.log(`${data.exchange} ${data.symbol}: $${data.data.last}`)
})

ws.connect()

✅ Key Differentiators

🔄 Unified format. All exchanges return the same response shape. No more normalizing BTCUSDT vs BTC-USD vs XBT/USD.
🟦 TypeScript-first SDK. Full type coverage, automatic retries, and built-in rate limit awareness.
🤖 MCP server. The first crypto API with native AI assistant integration.
🛡️ Circuit breakers. If an exchange goes down, Luzia degrades gracefully instead of returning errors.
💸 Affordable pricing. Free tier at 100 req/min and 5,000/day. Pro at $22.99/month with 1,000 req/min, 20,000/day, and WebSocket access.

⚠️ Honest Limitations

Luzia is not the right choice for every project:

Limited coin coverage. Supports major pairs across 5 exchanges. If you need pricing data on 10,000+ altcoins, CoinGecko or CoinMarketCap are better fits.
No on-chain data. CEX price feeds only. For DEX pricing or blockchain analytics, look at Bitquery.
Pricing and market data only. No trade execution, no order management. Luzia is read-only by design, focused entirely on delivering accurate, real-time price and market data.
No stocks or forex. Crypto only. For multi-asset pricing, Finnhub or Twelve Data are better starting points.

👉 Get a free API key at luzia.dev and try it in under five minutes.

❓ Frequently Asked Questions

What is the best free crypto API in 2026?

For broad coin coverage, CoinGecko's free tier (30 requests/minute, no daily cap) remains the most generous. For multi-exchange aggregation with higher rate limits, Luzia's free tier offers 100 requests/minute and 5,000 requests/day across 5 major exchanges. If you only need a single exchange, Binance's free API has the highest limits at 1,200 requests/minute.

Which crypto API has the lowest latency?

Direct exchange APIs (Binance, OKX, Bybit) deliver the lowest latency at 50-70ms since there's no intermediary. Among aggregators, Luzia averages around 100ms due to its multi-level caching architecture. CoinGecko and CoinMarketCap typically range from 300-500ms.

Is there a crypto API with AI assistant support?

Luzia is currently the only crypto API that ships a Model Context Protocol (MCP) server for AI assistants. It works with Claude Desktop, Claude Code, and any MCP-compatible client. Other APIs can be used with AI through custom tool definitions, but Luzia provides this out of the box.

How do crypto API rate limits work?

Most APIs enforce two types of limits: per-minute (burst) and per-day (sustained). Per-minute limits prevent you from hammering the API, while daily limits cap total usage. When you exceed a limit, you'll receive a 429 status code with a Retry-After header. Good SDKs handle this automatically with exponential backoff.

Should I use an aggregator or connect directly to exchanges for price data?

Use an aggregator when you need price data from multiple exchanges, want a consistent data format, or don't want to maintain multiple integrations. Connect directly when you need the absolute lowest latency for a specific exchange or need exchange-specific market data like funding rates or detailed order book snapshots.

What is the best crypto price data API for trading bots?

Trading bots need two things: a price data feed and an execution layer. For the data feed, it depends on scope. Single-exchange bots can use that exchange's market data endpoints directly (Binance, OKX, Bybit). Bots that monitor prices across multiple exchanges for arbitrage detection or cross-exchange signals benefit from an aggregator like Luzia or CoinGecko. Luzia's WebSocket streaming and circuit breaker pattern make it particularly suited for bots that need reliable, real-time price feeds with fault tolerance.