Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aAAaqwq/AGI-Super-Team --skill arbitrage-opportunity-findergit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aaaaqwq/agi-super-team/arbitrage-opportunity-finder)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/arbitrage-opportunity-finder"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/arbitrage-opportunity-finder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/arbitrage-opportunity-finder"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/arbitrage-opportunity-finder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 39 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00112 | $0.01725 |
| Opus 5 | $0.00056 | $0.00863 |
| Sonnet 5 | $0.00022 | $0.00345 |
| Haiku 4.5 | $0.00011 | $0.00172 |
Grade A, and why
finding-arbitrage-opportunities scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finding Arbitrage Opportunities
Overview
This skill detects and analyzes arbitrage opportunities across cryptocurrency exchanges and DeFi protocols. It aggregates prices from multiple sources, calculates net profit after fees and costs, and identifies both direct and triangular arbitrage paths.
Prerequisites
Before using this skill, ensure you have:
- Python 3.9+ with
httpx,rich, andnetworkxpackages - Internet access for API calls (no API keys required for basic use)
- Optional: Exchange API keys for real-time order book access
- Understanding of arbitrage concepts and trading fees
Instructions
Step 1: Configure Data Sources
Configure your price sources in {baseDir}/config/settings.yaml:
# Primary data sources
data_sources:
coingecko:
enabled: true
base_url: "https://api.coingecko.com/api/v3"
rate_limit: 10 # calls per minute (free tier)
exchanges:
- binance
- coinbase
- kraken
- kucoin
- okx
Or use environment variables for API keys:
export BINANCE_API_KEY="your-key"
export COINBASE_API_KEY="your-key"
Step 2: Quick Spread Scan
Scan for arbitrage opportunities on a specific pair:
python {baseDir}/scripts/arb_finder.py scan ETH USDC
This shows:
- Current prices on each exchange
- Spread percentage
- Estimated profit after fees
- Recommended action
Step 3: Multi-Exchange Comparison
Compare prices across specific exchanges:
python {baseDir}/scripts/arb_finder.py scan ETH USDC \
--exchanges binance,coinbase,kraken,kucoin,okx
Output includes:
| Exchange | Bid | Ask | Spread | Net Profit |
|---|---|---|---|---|
| Binance | 2541.20 | 2541.50 | 0.01% | - |
| Coinbase | 2543.80 | 2544.10 | 0.01% | +$2.30 |
Step 4: DEX Price Comparison
Scan decentralized exchanges for arbitrage:
python {baseDir}/scripts/arb_finder.py scan ETH USDC --dex-only
Compares:
- Uniswap V3
- SushiSwap
- Curve
- Balancer
Includes gas cost estimates for on-chain execution.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- ARD.md 15 KB
- config/settings.yaml 7.9 KB
- PRD.md 7.1 KB
- references/errors.md 6.1 KB
- references/examples.md 13 KB
- references/implementation.md 11 KB
- scripts/arb_finder.py 12 KB runs code
- scripts/formatters.py 13 KB runs code
- scripts/opportunity_scanner.py 11 KB runs code
- scripts/price_fetcher.py 12 KB runs code
- scripts/profit_calculator.py 12 KB runs code
- scripts/triangular_finder.py 11 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 243 lines · 112 tokens per session scan A 6aa1530f6996
finding-arbitrage-opportunities is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (92 stars, last pushed yesterday), licensed MIT. It adds 112 tokens to every session and 1,725 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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