checkr

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• SKILL.md
• endpoints.md · references/

SKILL.md (first lines)

# 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:**
```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:**
```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.

```python
# 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)

From Eskyee/agentbot-opensource, MIT.

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