Results for “alpaca”

Use Alpaca CryptoDataStream websocket for real-time crypto bars in live trading (OHLC only, volume excluded)

MCP (Model Context Protocol) server configuration for Claude Code integration with trading platform. Trigger when setting up MCP servers, fixing alpaca-mcp-server issues, or adding new integrations.

Alpaca broker limitations: crypto shorts blocked (broker doesn't support), stock shorts allowed. Trigger when: (1) shorting gate blocks wrong assets, (2) SELL signals blocked, (3) order type confusion.

CRITICAL: Alpaca API is MANDATORY for all OHLCV data. yfinance is NOT a valid fallback - EVER. Trigger when: (1) any code attempts yfinance for price/volume data, (2) crypto volume filter fails, (3) zero-volume bars detected, (4) API key configuration issues, (5) fallback behavior proposed.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Symbol Database Selection Pattern

Apache Kafka event streaming platform. Covers producers, consumers, topics, partitions, Kafka Streams, and Connect. Use for high-throughput event-driven architectures and real-time data pipelines. USE WHEN: user mentions "kafka", "event streaming", "kafka streams", "consumer groups", "topic partitions", asks about "high throughput messaging", "event sourcing", "log aggregation", "real-time pipelines" DO NOT USE FOR: simple queues - use `rabbitmq` or `activemq`; cloud-native lightweight - use `nats`; AWS-native - use `sqs`; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`

This skill should be used when the user wants to "dca into" a token, "buy X every day", set up a "recurring buy", "dollar cost average" into an asset, "schedule a buy", or "auto-buy on a dip". Buys a fixed amount into a token on a schedule, optionally only when a condition holds (for example only when ETH is below a price threshold). The host agent's scheduler wakes the skill on a cadence; each wake is one self-contained run.

llama.cpp local GGUF inference + HF Hub model discovery.

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants for clean API contracts in Python applications using Pydantic v2.

SQLAlchemy Python SQL toolkit and ORM with powerful query builder, relationship mapping, and database migrations via Alembic

AI Personal Assistant network skill for multi-agent PA coordination. Use when: contacting another PA, coordinating with peer agents, scheduling meetings between owners, broadcasting messages to PA groups, or looking up contacts from the local PA directory. Reads contact data from data/pa-directory.json in the workspace.

Write and run analytical SQL queries against Redpanda SQL (Oxla), a distributed PostgreSQL-wire-compatible columnar database, including data loading, external sources, and type handling.

Fetch random dog images and breed information from the Dog API (dog.ceo). Use when the user wants dog pictures or information about specific dog breeds. No API key required.

Use when masking columns or coordinate ranges in multiple-sequence alignments before downstream HMMER or alignment-processing steps.

Provides Kelvin Garr's fixed AICA brand identity and Next.js 14 implementation guide for building his personal sites and AICA-branded projects.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Manages and analyzes incidents, post-incident reviews, and collaboration workflows in Allma via its REST API, covering incident discovery, timeline tracking, stakeholder communication, and retrospective analysis.

Evaluates likelihood of primary aldosteronism by measuring plasma aldosterone suppression after oral captopril; normal suppression ≥30% makes PA unlikely, while lack of suppression with persistently suppressed plasma renin activity suggests PA. Use when assessing captopril challenge test (CCT) results for PA diagnosis in patients with positive aldosterone-to-renin ratio.

Manage Planka Kanban projects, boards, lists, cards, and notifications through a command-line interface.

WOLVERINE v2.0 — HYPE alpha hunter. Entry-only scanner, DSL-exit-only architecture. v1.1 lost -22.7% because the scanner's thesis exit chopped 25/27 trades before DSL could manage them. v2.0 removes thesis exit entirely. Scanner decides entries (score 8+, 4H/1H aligned, SM consensus). DSL manages all exits (wide Phase 1 for HYPE volatility, trailing tiers starting at +15% ROE). Leverage lowered to 7x. Max 4 entries/day. 3-hour cooldown between entries. DSL exit managed by plugin runtime via runtime.yaml.

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.

Automates question submission to Amazon's Alexa/Rufus AI shopping assistant and collects structured response data, with optional keyword search context for category-specific answers.

Determines whether to recommend unilateral laparoscopic adrenalectomy or medical therapy with a mineralocorticoid receptor antagonist for patients with confirmed unilateral PA (aldosterone-producing adenoma or unilateral adrenal hyperplasia). Triggered when discussing treatment options after confirming unilateral PA in a hypertensive patient with hypokalemia or resistant hypertension.

Run LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Applies Kelvin Garr's fixed AICA brand identity—black glass, gold circuits, Space Grotesk—and Next.js 14 implementation guide for his personal sites and AICA-branded projects.

Guiding workflows by decomposing complex tasks (Epics) into Atomic Steps under 15 minutes each, with progress tracking and drift prevention. Use when complex decomposition is needed.

Provides guidance for setting up an Elasticsearch MCP server, including prerequisites and links to official documentation.

Installs the Snowflake Connector for Python and builds a wheel package using PEP-517.

Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.