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checkr

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Access real-time X/Twitter attention intelligence for Base chain tokens via the checkr API. Use when you need to know what is trending on CT, which tokens are spiking in social attention, get attention/price divergence signals, or fetch narrative summaries for specific Base tokens. Triggers: "what's trending on Base", "check attention for $TOKEN", "what's spiking right now", "social signal for X", any token research needing CT attention data. Payments via x402 — USDC on Base, no API key or account needed.

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checkr

Real-time X/Twitter attention intelligence for Base chain tokens.

Base URL: https://api.checkr.social
Docs: https://api.checkr.social/docs
Payment: x402 — USDC on Base mainnet, pay-per-call, no account needed.

Endpoints

EndpointPriceWhat it returns
GET /v1/leaderboard$0.02Top Base tokens ranked by social attention share
GET /v1/spikes$0.05Tokens currently velocity-spiking (the radar sweep)
GET /v1/token/{symbol}$0.50Deep dive: ATT deltas, price, divergence, narrative
GET /v1/bankr$0.02Attention leaderboard for the bankr agent ecosystem

Full response schemas and field definitions: https://api.checkr.social/docs

How to Call (x402)

x402 is pay-per-call. No API key or account. Wallet + USDC on Base is all you need.

Python:

from x402.client import x402_client

client = x402_client(wallet=YOUR_WALLET)

# What's spiking right now — $0.05
spikes = client.get("https://api.checkr.social/v1/spikes").json()

# Top tokens by attention — $0.02
leaderboard = client.get("https://api.checkr.social/v1/leaderboard").json()

# Deep dive on a token — $0.50
token = client.get("https://api.checkr.social/v1/token/BNKR").json()

TypeScript:

import { withPaymentInterceptor } from "x402-axios";
import axios from "axios";

const client = withPaymentInterceptor(axios.create(), walletClient);

const { data } = await client.get("https://api.checkr.social/v1/spikes");

Payment is handled automatically by the x402 client — it intercepts the 402, signs and sends payment, then retries with the receipt.

Practical Flow

Use spikes as your radar. Drill into token for context.

# 1. What's moving?
spikes = client.get("https://api.checkr.social/v1/spikes").json()
# → [{ symbol: "TIBBIR", velocity: 3.9, ATT_pct: 11.4, divergence: false, hawkes: {...} }]

# 2. Deep dive on the top spike
top = spikes["spikes"][0]["symbol"]
detail = client.get(f"https://api.checkr.social/v1/token/{top}").json()
# → full price, divergence, spike history, narrative

Key Fields

On every response:

  • data_age_minutes — how fresh the data is. Use before acting.

On spikes:

  • velocity — momentum multiplier vs baseline. 3.0+ = meaningful spike.
  • divergence — true = attention up, price flat/down. The alpha pattern.
  • hawkes.viral_class — BUILDING / SUSTAINED / FADING. Is this self-reinforcing?
  • rotating_from — tokens losing attention as this one gains.
  • narrative_summary — AI-generated 180-char brief. null if signal below confidence threshold.

On token deep dive:

  • ATT_delta_1h / ATT_delta_4h — attention share movement over time.
  • spike_history.hit_rate — % of past spikes with confirmed price follow-through.
  • narrative.type — infrastructure / ecosystem / fud_defense / meme / launch_hype.

Query Params

GET /v1/leaderboard?limit=10&sort_by=ATT_pct&min_mentions=5
GET /v1/spikes?min_velocity=3.0&min_mentions=10&divergence_only=false

Requirements

  • USDC on Base mainnet
  • Python: pip install x402
  • TypeScript: npm install x402-axios
  • Base gas for payment (~$0.01)