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Jito Bundles skill

Jito bundle submission for MEV protection on Solana — bundle building, tip strategies, block engine endpoints, and landing rate optimization

$npx skills add agiprolabs/claude-trading-skills --skill jito-bundles
GitHub stars
521
Pack installs
34k
Alyn Score
59/99
Updated
2 months ago
License
MIT

Install Jito Bundles

Pick your agent. Every command is ready to paste.

$npx skills add agiprolabs/claude-trading-skills --skill jito-bundles

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads jito-bundles when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the jito-bundles skill”. In Codex, type $jito-bundles.

The skill itself

SKILL.md

GitHub

Jito Bundle Submission for Solana

Jito bundles allow you to submit up to 5 Solana transactions that execute atomically — either all land in the same slot or none do. This is the primary mechanism for MEV protection and competitive transaction execution on Solana. Approximately 85%+ of Solana validators run the Jito-modified client, making bundles the standard for reliable, front-run-resistant execution.

EXECUTION SKILL — SAFETY WARNING: Submitting bundles spends real SOL on tips. Always test with --demo mode first. Never submit bundles with real funds without explicit confirmation. Default to simulation/dry-run in all scripts and examples.

When to Use Bundles

Scenario Use Bundle? Why
Swap on illiquid token Yes Prevents sandwich attacks
Multi-step arbitrage Yes Atomic execution prevents partial fills
Liquidation Yes Competitive — tip determines priority
Simple SOL transfer No Priority fees are cheaper and sufficient
Time-insensitive swap Maybe Bundles cost tips; priority fees may suffice
NFT mint / competitive action Yes Guarantees ordering within the slot

Core Concepts

Bundle Anatomy

A Jito bundle is a JSON-RPC request containing 1-5 base58-encoded signed transactions. The transactions execute sequentially and atomically within a single slot.

Bundle = [Tx1, Tx2, ..., TxN]  (N <= 5)

- All transactions must be signed
- Transactions execute in order: Tx1 → Tx2 → ... → TxN
- If ANY transaction fails, the ENTIRE bundle is dropped
- The tip instruction goes in the LAST transaction (last instruction)
- Bundle has ~2 slots (~800ms) to land before expiry

Tip Mechanism

Tips are SOL transfers to one of Jito's 8 tip accounts. The tip incentivizes validators to include your bundle.

# Tip is a standard SOL transfer instruction
tip_instruction = transfer(
    from_pubkey=your_wallet,
    to_pubkey=tip_account,      # One of 8 Jito tip accounts
    lamports=tip_amount          # Tip in lamports (1 SOL = 1e9 lamports)
)
# Add as the LAST instruction of the LAST transaction in the bundle

Tip accounts are fetched dynamically via getTipAccounts. Rotate through them to distribute load.

Block Engine Endpoints

Jito operates geographically distributed block engines. Choose the one closest to your infrastructure:

Region Endpoint
New York https://mainnet.block-engine.jito.wtf
Amsterdam https://amsterdam.block-engine.jito.wtf
Frankfurt https://frankfurt.block-engine.jito.wtf
Tokyo https://tokyo.block-engine.jito.wtf

All endpoints accept JSON-RPC over HTTPS on port 443. The /api/v1/bundles path handles bundle operations.

API Methods

sendBundle

Submit a bundle of up to 5 transactions.

import httpx

BLOCK_ENGINE = "https://mainnet.block-engine.jito.wtf"

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "sendBundle",
    "params": [
        [tx1_base58, tx2_base58],  # List of base58-encoded signed txs
    ]
}

resp = httpx.post(f"{BLOCK_ENGINE}/api/v1/bundles", json=payload)
data = resp.json()
bundle_id = data["result"]  # UUID string

getBundleStatuses

Check the landing status of submitted bundles (up to 5 bundle IDs per request).

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "getBundleStatuses",
    "params": [[bundle_id]]
}
resp = httpx.post(f"{BLOCK_ENGINE}/api/v1/bundles", json=payload)
statuses = resp.json()["result"]["value"]
# Each status: {bundle_id, status, slot, transactions: [{signature, ...}]}
# status: "Invalid", "Pending", "Failed", "Landed"

getTipAccounts

Fetch the current list of Jito tip accounts.

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "getTipAccounts",
    "params": []
}
resp = httpx.post(f"{BLOCK_ENGINE}/api/v1/bundles", json=payload)
tip_accounts = resp.json()["result"]  # List of 8 base58 pubkeys

getInflightBundleStatuses

Check status of bundles that haven't landed yet (in-flight).

payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "getInflightBundleStatuses",
    "params": [[bundle_id]]
}
resp = httpx.post(f"{BLOCK_ENGINE}/api/v1/bundles", json=payload)
# status: "Pending", "Failed", "Landed"

Bundle Construction Pattern

A typical bundle for a protected swap:

from solders.transaction import VersionedTransaction
from solders.message import MessageV0
from solders.instruction import Instruction
from solders.system_program import transfer, TransferParams
from solders.pubkey import Pubkey
import random

def build_protected_swap_bundle(
    swap_ix: Instruction,
    payer: Pubkey,
    tip_lamports: int,
    tip_accounts: list[str],
    recent_blockhash: str,
) -> list[VersionedTransaction]:
    """Build a 1-tx bundle: swap + tip in the same transaction.

    For simple swaps, a single-transaction bundle is sufficient.
    The tip instruction is appended as the last instruction.
    """
    # Pick a random tip account
    tip_account = Pubkey.from_string(random.choice(tip_accounts))

    # Tip instruction
    tip_ix = transfer(TransferParams(
        from_pubkey=payer,
        to_pubkey=tip_account,
        lamports=tip_lamports,
    ))

    # Build transaction with swap + tip
    msg = MessageV0.try_compile(
        payer=payer,
        instructions=[swap_ix, tip_ix],
        address_lookup_table_accounts=[],
        recent_blockhash=recent_blockhash,
    )
    tx = VersionedTransaction(msg, [keypair])
    return [tx]

Tip Sizing Guide

Scenario Tip Range (lamports) Tip Range (SOL)
Normal swap (low urgency) 1,000 - 10,000 0.000001 - 0.00001
Normal swap (standard) 10,000 - 50,000 0.00001 - 0.00005
Competitive action (arb, liquidation) 50,000 - 500,000 0.00005 - 0.0005
Highly competitive (NFT mint, MEV) 500,000 - 5,000,000 0.0005 - 0.005
Emergency (must land this slot) 5,000,000+ 0.005+

Dynamic tip calculation based on recent tip levels:

def calculate_dynamic_tip(
    base_tip: int = 10_000,
    urgency_multiplier: float = 1.0,
    recent_tip_percentile_50: int = 15_000,
) -> int:
    """Calculate tip based on urgency and recent network tips.

    Args:
        base_tip: Minimum tip in lamports.
        urgency_multiplier: 1.0 = normal, 2.0 = urgent, 5.0 = critical.
        recent_tip_percentile_50: Median tip from recent bundles.

    Returns:
        Tip amount in lamports.
    """
    dynamic_tip = max(base_tip, int(recent_tip_percentile_50 * urgency_multiplier))
    # Cap at 0.01 SOL to prevent accidents
    return min(dynamic_tip, 10_000_000)

Common Errors and Fixes

Error Cause Fix
Bundle dropped (slot expired) Bundle didn't land within 2 slots Retry with fresh blockhash; consider higher tip
Transaction simulation failed A tx in the bundle would fail on-chain Simulate each tx individually to find the failing one
Bundle already processed Duplicate bundle ID Expected on retry; check status instead
Rate limited Too many requests to block engine Back off; rotate between block engine endpoints
Invalid transaction Malformed or unsigned transaction Verify all txs are signed and base58-encoded
Blockhash not found Stale blockhash Use getLatestBlockhash with finalized commitment

Landing Rate Optimization

Strategies to maximize bundle landing probability:

  1. Multi-region submission: Send the same bundle to multiple block engines simultaneously. The first to reach the current leader wins.

  2. Fresh blockhash: Use getLatestBlockhash with confirmed commitment immediately before building. Stale blockhashes are the #1 cause of dropped bundles.

  3. Retry with backoff: If a bundle doesn't land within 2-3 seconds, rebuild with a fresh blockhash and resubmit. Do NOT resubmit with the same blockhash.

  4. Adequate tipping: Under-tipped bundles are deprioritized. Monitor the network's tip distribution and tip at or above the 50th percentile for your urgency level.

  5. Minimal bundle size: Fewer transactions = less simulation time = higher landing rate. Use single-transaction bundles when possible.

async def submit_with_retry(
    bundle_txs: list[str],
    endpoints: list[str],
    max_retries: int = 3,
) -> str | None:
    """Submit bundle to multiple endpoints with retry logic.

    Returns bundle_id if submitted, None if all retries exhausted.
    """
    for attempt in range(max_retries):
        # Submit to all endpoints in parallel
        async with httpx.AsyncClient() as client:
            tasks = [
                client.post(
                    f"{ep}/api/v1/bundles",
                    json={
                        "jsonrpc": "2.0", "id": 1,
                        "method": "sendBundle",
                        "params": [bundle_txs],
                    },
                    timeout=5.0,
                )
                for ep in endpoints
            ]
            # Process first successful response
            for resp in asyncio.as_completed(tasks):
                result = (await resp).json()
                if "result" in result:
                    return result["result"]

        # Wait before retry with fresh blockhash
        await asyncio.sleep(0.5 * (attempt + 1))
    return None

Safety Checklist (Execution)

Before submitting any bundle with real funds:

  • Simulated all transactions individually via simulateTransaction
  • Verified tip amount is reasonable (not accidentally SOL instead of lamports)
  • Confirmed blockhash is fresh (< 60 seconds old)
  • Verified all transactions are properly signed
  • Checked wallet balance covers all transaction costs + tip
  • Tested with devnet or --demo mode first
  • Set maximum tip cap to prevent accidental overpayment

Files

References

  • references/bundle_api.md — Complete JSON-RPC API reference with request/response schemas and error codes
  • references/tip_strategies.md — Tip calculation strategies, dynamic tipping, cost optimization
  • references/best_practices.md — Bundle construction patterns, landing rate optimization, common pitfalls

Scripts

  • scripts/build_bundle.py — Bundle construction with tip instruction; --demo mode builds but does not submit
  • scripts/check_bundle_status.py — Bundle status checking and tip account fetching; --demo mode uses mock responses

Tips for Jito Bundles

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • This skill ships scripts. Read them before the first run, and run it in a project without secrets first.
  • • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
  • • It is part of a pack with 40 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Jito Bundles

What does the Jito Bundles skill do?

Jito bundle submission for MEV protection on Solana — bundle building, tip strategies, block engine endpoints, and landing rate optimization

How do I install Jito Bundles?

Run "npx skills add agiprolabs/claude-trading-skills --skill jito-bundles" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Jito Bundles work in Cursor and Codex?

Yes. Jito Bundles uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Jito Bundles free?

Jito Bundles is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Jito Bundles?

Jito Bundles is published by agiprolabs in the agiprolabs/claude-trading-skills repository, together with 39 other skills.

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