bankrbot/checkr

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

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