Results for “uniswap”

This skill should be used when the user asks to "swap tokens", "trade ETH for USDC", "exchange tokens on Uniswap", "buy tokens", "sell tokens", "convert ETH to stablecoins", "find memecoins", "discover tokens", "research tokens", "tokens to buy", "find tokens to swap", "what should I buy", or mentions swapping, trading, researching, discovering, buying, or exchanging tokens on any Uniswap-supported chain. Supports both known token swaps and token discovery workflows (discovery uses keyword search and web search — there is no live "trending" feed). Generates deep links to execute swaps in the Uniswap interface.

Integrate Uniswap liquidity provisioning (LP) into applications via the LP REST API. Use when the user says "LP API", "liquidity provisioning API", "provide liquidity programmatically", "create LP position via API", "add liquidity via API", "increase liquidity", "decrease liquidity", "remove liquidity", "claim LP fees", "collect LP fees", "manage LP positions in code", or mentions building a backend, bot, or frontend that creates or manages Uniswap v2/v3/v4 liquidity positions through an API. Also use when debugging LP API calls (e.g. /lp/create, /lp/check_approval, /lp/increase, /lp/decrease, /lp/claim_fees), unexpected response fields, the approval or EIP-712 permit flow, or transaction-building errors for liquidity positions. For generating deep links to the Uniswap web app instead of calling the API, use the liquidity-planner skill; for using the Uniswap v4 SDK directly rather than the REST API, use the v4-sdk-integration skill.

Perform nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows using the umap-learn library.

Nonlinear dimensionality reduction with UMAP — fast manifold learning for 2D/3D visualization, clustering preprocessing (e.g., HDBSCAN), and supervised or parametric UMAP. Use when projecting high-dimensional data to low dimensions for visualization, embedding generation, or as a preprocessing step before clustering. Part of the AlterLab Academic Skills suite.

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

Reduce high-dimensional data with UMAP for visualization, clustering preprocessing, and supervised or semi-supervised learning, including parameter tuning guidance.

Integrate with EVM blockchains using viem and wagmi for wallet connection, contract reads/writes, event subscriptions, multicall, and multi-chain support.

Run MISP, curate threat feeds, and auto-generate detections for Wazuh, Sigma, and Suricata.

Unified search API across Google, Amazon, Yelp, OpenTable, Walmart, and more. Use when searching for products, local businesses, restaurants, shopping, images, news, or any web search. One API key, many engines.

Provides GSAP utility functions for math, value mapping, randomization, snapping, and unit parsing in animations.

Simulate and analyze open quantum systems using QuTiP, including master equations, Lindblad dynamics, decoherence, and quantum optics.

Chainlink CCIP — Cross-Chain Interoperability Protocol

Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time evolution. NOT for circuit-based quantum computing or hardware execution — for IBM Quantum circuits prefer alterlab-qiskit, for Google Quantum AI or NISQ circuits prefer alterlab-cirq, and for gradient-trained quantum ML prefer alterlab-pennylane. Part of the AlterLab Academic Skills suite.

Simulates ARP spoofing attacks in authorized lab or pentest environments using arpspoof, Ettercap, and Scapy to demonstrate man-in-the-middle risks, test network detection capabilities, and validate ARP inspection countermeasures.

Statistical fine-mapping of GWAS loci using SuSiE, SuSiE-inf, and Approximate Bayes Factors to identify credible sets and posterior inclusion probabilities (PIPs) for causal variant discovery. SuSiE-inf adds an infinitesimal polygenic component for improved calibration at well-powered loci.

Simulate open and closed quantum systems with QuTiP, covering master equations, Lindblad dynamics, decoherence, and quantum optics.

Craft, send, sniff, and dissect network packets using Scapy for protocol analysis, network reconnaissance, and traffic anomaly detection in authorized security testing.

Set up and verify a connection to an NI USRP radio (USRP E320, N300, N310, N320, N321, X300, X310, or X410) using Wireless Testbench. Use when connecting a USRP for the first time, configuring radio hardware, troubleshooting connection failures, or verifying a radio setup. Covers host inspection (OS, NIC type/speed/MTU), device discovery (findsdru, probesdru), UHD version checking, programmatic radio configuration, and basebandTransceiver verification. Also use when the user mentions USRP setup, radio not found, connection errors, dropped samples, or network configuration for SDR hardware.

Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.

Official GSAP skill for gsap.utils — clamp, mapRange, normalize, interpolate, random, snap, toArray, wrap, pipe. Use when the user asks about gsap.utils, clamp, mapRange, random, snap, toArray, wrap, or helper utilities in GSAP.

Compare multiple UI variants locally in a real app, choose one, and clean up unused temporary code.

Drafts a Written Information Security Program compliant with Massachusetts 201 CMR 17.00 and supplementary frameworks (GDPR, CCPA, HIPAA, GLBA, PCI-DSS). Produces a board-ready regulatory document covering coordinator designation, risk assessment, safeguards, training, incident response with breach notification, and vendor oversight. Use when an organization handles personal information of MA residents and needs a standalone WISP for regulatory examination or executive approval.

Launch and trade tokens on hood.markets (Robinhood Chain) via the agent API, including deploy, buy, sell, and fee claiming.

Simulate and analyze quantum mechanical systems, including open quantum systems, using QuTiP's solvers for master equations, Lindblad dynamics, and quantum trajectories.

Write effective unit tests with XUnit, covering standard and data-driven testing approaches.

Write effective unit tests with modern MSTest 3.x/4.x, covering assertion APIs, data-driven tests, and test lifecycle best practices.

Deploy MISP, configure threat feeds, use the PyMISP API for programmatic access, and build automated collection pipelines that aggregate IOCs from multiple community and commercial sources.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

Official GSAP skill for gsap.utils — clamp, mapRange, normalize, interpolate, random, snap, toArray, wrap, pipe. Use when the user asks about gsap.utils, clamp, mapRange, random, snap, toArray, wrap, or helper utilities in GSAP.