Complete Surfpool development environment for Solana - drop-in replacement for solana-test-validator with mainnet forking, cheatcodes, Infrastructure as Code, and Surfpool Studio. The fastest way to develop and test Solana programs.
npx skills add https://github.com/sendaifun/skills --skill surfpool
The definitive guide for Surfpool - where developers start their Solana journey. A drop-in replacement for solana-test-validator that enables local program simulation using Mainnet accounts fetched just-in-time.
Surfpool is a comprehensive development environment that combines local-first testing with real Mainnet data access:
| Feature | Description |
|---------|-------------|
| Instant Boot | No 2TB snapshots, runs on Raspberry Pi |
| Lazy Forking | Copy-on-read strategy pulls mainnet data as needed |
| Full Compatibility | Works with solana-cli, Anchor, wallets, explorers |
| Zero Config | Auto-detects Anchor projects and deploys programs |
curl -sL https://run.surfpool.run/ | bash
brew install txtx/taps/surfpool
git clone https://github.com/txtx/surfpool.git
cd surfpool
cargo surfpool-install
docker pull surfpool/surfpool
docker run -p 8899:8899 -p 18488:18488 surfpool/surfpool
# Start with default configuration
surfpool start
# Start with custom RPC source
surfpool start -u https://api.mainnet-beta.solana.com
# Start without terminal UI
surfpool start --no-tui
# Start with debug logging
surfpool start --debug
| Service | URL | Description |
|---------|-----|-------------|
| RPC Endpoint | http://127.0.0.1:8899 | Standard Solana RPC |
| WebSocket | ws://127.0.0.1:8900 | Real-time subscriptions |
| Surfpool Studio | http://127.0.0.1:18488 | Web dashboard |
Start the local Surfnet network.
surfpool start [OPTIONS]
Options:
| Option | Default | Description |
|--------|---------|-------------|
| -m, --manifest-file-path | ./Surfpool.toml | Path to manifest file |
| -p, --port | 8899 | RPC port |
| -o, --host | 127.0.0.1 | Host address |
| -s, --slot-time | 400 | Slot time in ms |
| -u, --rpc-url | https://api.mainnet-beta.solana.com | Source RPC URL |
| --no-tui | - | Disable terminal UI |
| --debug | - | Enable debug logs |
| --no-deploy | - | Disable auto deployments |
| -r, --runbook | deployment | Runbooks to execute |
| -a, --airdrop | - | Pubkeys to airdrop |
| -q, --airdrop-amount | 10000000000000 | Airdrop amount (lamports) |
| -k, --airdrop-keypair-path | - | Keypair path for airdrop |
| --no-explorer | - | Disable explorer |
# Start with airdrop to specific address
surfpool start -a YOUR_PUBKEY -q 100000000000
# Start with custom slot time (faster blocks)
surfpool start -s 100
# Start with specific runbook
surfpool start -r deployment -r setup
Create a Surfpool.toml in your project root:
[network]
slot_time = 400
epoch_duration = 432000
rpc_url = "https://api.mainnet-beta.solana.com"
[behavior]
# Fork from mainnet genesis
genesis = false
# Fork from specific point
point_fork = true
[accounts]
# Pre-clone specific accounts
clone = [
"TokenkegQfeZyiNwAJbNbGKPFXCWuBvf9Ss623VQ5DA", # Token Program
"ATokenGPvbdGVxr1b2hvZbsiqW5xWH25efTNsLJA8knL", # ATA Program
]
[programs]
# Auto-deploy local programs
deploy = ["./target/deploy/my_program.so"]
[airdrop]
# Default airdrop recipients
addresses = ["YOUR_PUBKEY"]
amount = 10000000000000 # 10,000 SOL
Surfpool provides special RPC methods for advanced state manipulation during testing.
Set arbitrary account data:
await connection.send("surfnet_setAccount", [
{
pubkey: "AccountPubkey...",
lamports: 1000000000,
data: "base64EncodedData",
owner: "OwnerPubkey...",
executable: false,
},
]);
Create or modify token accounts:
await connection.send("surfnet_setTokenAccount", [
{
owner: "OwnerPubkey...",
mint: "MintPubkey...",
tokenProgram: "TokenkegQfeZyiNwAJbNbGKPFXCWuBvf9Ss623VQ5DA",
update: {
amount: "1000000000",
delegate: null,
state: "initialized",
},
},
]);
Clone a program from mainnet:
await connection.send("surfnet_cloneProgramAccount", [
{
source: "SourceProgramPubkey...",
destination: "DestinationPubkey...",
},
]);
Reset account to mainnet state:
await connection.send("surfnet_resetAccount", [
{
pubkey: "AccountPubkey...",
includeOwnedAccounts: true,
},
]);
Advance network time:
await connection.send("surfnet_timeTravel", [
{
epoch: 100,
slot: 50000,
timestamp: 1700000000,
},
]);
Control block production:
// Pause
await connection.send("surfnet_pauseClock", []);
// Resume
await connection.send("surfnet_resumeClock", []);
Advance clock incrementally:
await connection.send("surfnet_advanceClock", [
{ slots: 100 },
]);
Profile transaction execution:
const result = await connection.send("surfnet_profileTransaction", [
{
transaction: "base64EncodedTx",
tag: "my-test-tag",
},
]);
console.log("Compute units:", result.computeUnits);
console.log("Account changes:", result.accountChanges);
Get profiling results by tag:
const results = await connection.send("surfnet_getProfileResults", [
{ tag: "my-test-tag" },
]);
Reset entire network to initial state:
await connection.send("surfnet_resetNetwork", []);
Get current network time:
const clock = await connection.send("surfnet_getClock", []);
console.log("Slot:", clock.slot);
console.log("Epoch:", clock.epoch);
console.log("Timestamp:", clock.timestamp);
Access the web dashboard at http://127.0.0.1:18488 for:
Surfpool integrates txtx DSL for reproducible deployments.
# deployment.tx
// Define signers
signer "deployer" "svm::secret_key" {
secret_key = env.DEPLOYER_KEY
}
// Deploy program
action "deploy_program" "svm::deploy_program" {
program_path = "./target/deploy/my_program.so"
signer = signer.deployer
}
// Initialize program
action "initialize" "svm::send_transaction" {
transaction {
instruction {
program_id = action.deploy_program.program_id
data = encode_instruction("initialize", {})
}
}
signers = [signer.deployer]
}
# Run specific runbook
surfpool start -r deployment
# Run in unsupervised mode
surfpool start -r deployment --unsupervised
Define account state sequences for testing:
await connection.send("surfnet_registerScenario", [
{
name: "high-volume-trading",
slots: [
{
slot: 100,
accounts: {
"PoolPubkey...": { lamports: 1000000000000 },
},
},
{
slot: 200,
accounts: {
"PoolPubkey...": { lamports: 500000000000 },
},
},
],
},
]);
Export transaction fixtures for reproducible tests:
const fixture = await connection.send("surfnet_exportSnapshot", [
{
transaction: "txSignature...",
format: "json",
},
]);
// Save fixture for CI/CD
fs.writeFileSync("fixtures/my-test.json", JSON.stringify(fixture));
Surfpool auto-detects Anchor projects and handles deployment:
# In an Anchor project directory
surfpool start
# Programs in target/deploy/ are automatically deployed
import * as anchor from "@coral-xyz/anchor";
describe("My Program", () => {
// Use local Surfnet
const provider = anchor.AnchorProvider.local("http://127.0.0.1:8899");
anchor.setProvider(provider);
it("works with mainnet state", async () => {
// Your tests automatically have access to mainnet accounts
});
});
// Set up test state before each test
beforeEach(async () => {
await connection.send("surfnet_resetNetwork", []);
await connection.send("surfnet_setTokenAccount", [...]);
});
// Tag transactions for profiling
const result = await connection.send("surfnet_profileTransaction", [
{ transaction: tx, tag: "swap-operation" },
]);
expect(result.computeUnits).toBeLessThan(200000);
// Test with specific mainnet conditions
await connection.send("surfnet_registerScenario", [
{ name: "low-liquidity", slots: [...] },
]);
// Create reproducible test fixtures
const fixture = await connection.send("surfnet_exportSnapshot", [...]);
surfpool/
├── SKILL.md # This file
├── resources/
│ ├── cheatcodes.md # Complete cheatcodes reference
│ ├── cli-reference.md # CLI commands reference
│ └── github-repos.md # Repository links
├── examples/
│ ├── basic/
│ │ └── getting-started.ts # Basic setup example
│ ├── cheatcodes/
│ │ └── state-manipulation.ts # Cheatcode examples
│ └── iac/
│ └── deployment.tx # Infrastructure as Code example
├── templates/
│ ├── Surfpool.toml # Configuration template
│ └── test-setup.ts # Test setup template
└── docs/
└── troubleshooting.md # Common issues
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take sendaifun/surfpool from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference brew, docker.
Without those the skill loads but fails at the first command.