checkr
Skill17 starsChanged 5 months agoMITView on GitHub
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.
- Installs packages
2 other projects use a version of this.
Adopted by
Most recently taken up by
- BankrBot/openclaw-skillsword for word, first seen Oct 8, 2026
- BankrBot/skillsword for word, first seen Apr 28, 2026
Other versions2 projects use a version of this.
Word for word · 2
- BankrBot/openclaw-skills★ 1.2k100% same
- BankrBot/skills★ 1.2k100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository84 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/AGENTS.mdAGENTS.md
- .cursor/rules/codegraph.mdcCursor rule
- 0xworkSkill
- aeon-autoresearchSkill
- aeon-deal-flowSkill
- aeon-deep-researchSkill
- aeon-defi-monitorSkill
- aeon-defi-overviewSkill
- aeon-distribute-tokensSkill
- aeon-hacker-news-digestSkill
- aeon-huggingface-trendingSkill
- aeon-last30Skill
- aeon-monitor-kalshiSkill
- aeon-monitor-polymarketSkill
- aeon-monitor-runnersSkill
- aeon-narrative-trackerSkill
- aeon-on-chain-monitorSkill
- aeon-paper-pickSkill
- aeon-reg-monitorSkill
- aeon-rss-digestSkill
- aeon-skill-evalsSkill
- aeon-skill-repairSkill
- aeon-skill-security-scanSkill
- aeon-token-moversSkill
- aeon-token-pickSkill
- aeon-unlock-monitorSkill
- aeon-vuln-scannerSkill
- agenticbetsSkill
- agent-wormholeSkill
- alchemySkill
- bankr-shopifySkill
- bankrSkill
- token-scam-analysisSkill
- twitter-agentSkill
- baseSkill
- blueagent-x402Skill
- botchanSkill
- botcoin-minerSkill
- capacitrSkill
- cattownSkill
- clankerSkill
- codegridSkill
- darksol-random-oracleSkill
- endaomentSkill
- ens-primary-nameSkill
- erc-8004Skill
- gem-minerSkill
- get-api-docsSkill
- gitlawbSkill
- helixaSkill
- hydrexSkill
- litcoin-minerSkill
- megapotSkill
- moltycashSkill
- nexusSkill
- neynarSkill
- nookplotSkill
- onchainkitSkill
- opensea-apiSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 65
Use spikes as your radar. Drill into token for context.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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, narrativeKey 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.nullif 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=falseRequirements
- USDC on Base mainnet
- Python:
pip install x402 - TypeScript:
npm install x402-axios - Base gas for payment (~$0.01)
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

