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Found 259 Skills
Translate Cypher and Neo4j-style queries into HelixDB Rust DSL stored queries. Use when the input contains Cypher, Neo4j, MATCH, OPTIONAL MATCH, WHERE, RETURN, ORDER BY, LIMIT, DISTINCT, MERGE, CASE, UNWIND, FOREACH, DETACH DELETE, IS NULL, or variable-length path patterns and the goal is to produce an equivalent Helix Rust query.
Generates DDD Value Objects for PHP 8.4. Creates immutable, self-validating objects with equality comparison. Includes unit tests.
Analyze equity securities, factor models, and equity portfolio construction. Use when the user asks about stocks, equity valuation ratios, index construction methods, or style analysis. Also trigger when users mention 'P/E ratio', 'growth vs value', 'market cap weighting', 'sector allocation', 'GICS classification', 'earnings per share', 'Fama-French factors', 'CAPM', 'dividend yield', 'PEG ratio', 'EV/EBITDA', or ask which factors explain equity returns.
Converts cuTile GPU kernels (@ct.kernel) to Triton (@triton.jit). Handles standard in-repo conversion, debugging (cudaErrorIllegalAddress, shape mismatch, numerical mismatch), and mapping cuTile idioms (ct.load/ct.store, ct.Constant, ct.launch) to Triton equivalents. Covers dual-kernel layout flags (e.g. transpose=True/False + autotune grid via META) per translations/advanced-patterns.md. Use when converting, porting, or translating cuTile kernels to Triton, or debugging existing Triton translations.
Guardião da arquitetura de software no SynkOS. Use esta skill quando o usuário pedir para propor ou revisar a arquitetura de um sistema, avaliar tradeoffs entre tecnologias ou abordagens, criar um ADR (Architecture Decision Record), desenhar um modelo de dados ou contrato de API, ou fazer perguntas como "qual stack usar para X?", "como estruturar esse serviço?", "quais são os tradeoffs de Y vs Z?", "documente as decisões técnicas", "revise essa arquitetura". Ative também para discovery brownfield (entender o que já existe antes de propor mudanças), para cross-cutting concerns como segurança e performance, e para revisar designs propostos pelas equipes de implementação.
How to create, manage, and transfer tokens on Hedera using the Hiero JavaScript SDK (@hiero-ledger/sdk). Use this skill whenever the user wants to work with fungible tokens, NFTs, token creation, minting, burning, transfers, token association, custom fees (fixed, fractional, royalty), airdrops, KYC/freeze/wipe/pause operations, or any HTS (Hedera Token Service) operation in JavaScript or TypeScript. Also trigger when users mention @hashgraph/sdk token operations, ERC-20/ERC-721 equivalents on Hedera, or tokenization on the Hedera network.
Router skill for LLMQuant hedge-fund and PM strategy workflows. Use when the user needs equity long/short, long-biased, event-driven, macro, quant, or multi-strategy playbooks.
Owns the smoke test contract for an ML experiment: a small, diagnostic-by-construction pytest that fits the experiment's learner on a portion of the real `data/` source and predicts on a *disjoint* portion that deliberately carries **no pre-history buffer**. The assertion is structural — the number of predictions must equal the number of rows in the predict grid. A pipeline that loads-then-features-then-splits will silently drop the cold-start rows of the predict slice and the test will fail with a row-count mismatch; a pipeline that marks X early and references upstream history nodes from feature steps will pass trivially. The smoke test is the executable proof of the X-marker placement rule from `build-ml-pipeline`. TRIGGER when: `test-ml-pipeline` has dispatched here to write the smoke test for an approved experiment; `pytest tests/smoke/` is failing on row count; the user asks "why is the smoke test failing?"; a pipeline edit in `build-ml-pipeline` needs an executable proof; an experiment script changes the pipeline shape and the matching smoke test needs revisiting. SKIP when: the design note does not exist or is not yet approved (route to `iterate-ml-experiment`); the user is asking about a regression test or schema invariant (route to `regression-test-ml-pipeline` / `distribution-test-ml-pipeline` once those exist); the question is the *interpretation* of CV metrics, not predict-time correctness (route to `evaluate-ml-pipeline`). HOW TO USE: read the matching experiment's `journal/NN_*.md` and `experiments/NN_*.py` first to understand the pipeline's source binding (what env-dict keys does `build_learner` expect?). Then construct two env-dicts from the **real `data/` source** — a train env and a predict env — such that the predict env carries *only the rows we want predictions for* and *no pre-history buffer*. The hard assertion is that the prediction count matches the predict-env row count exactly. The soft assertion is that the smoke set's MAE is within `3 × CV_mean` (or the task-appropriate analogue). **Do not write the design note or run CV — that's other skills' job.**
Converts cuTile GPU kernels (@ct.kernel) to Triton (@triton.jit). Handles standard in-repo conversion, debugging (cudaErrorIllegalAddress, shape mismatch, numerical mismatch), and mapping cuTile idioms (ct.load/ct.store, ct.Constant, ct.launch) to Triton equivalents. Covers dual-kernel layout flags (e.g. transpose=True/False + autotune grid via META) per translations/advanced-patterns.md. Use when converting, porting, or translating cuTile kernels to Triton, or debugging existing Triton translations.
Laboratory automation toolkit for controlling liquid handlers, plate readers, pumps, heater shakers, incubators, centrifuges, and analytical equipment. Use this skill when automating laboratory workflows, programming liquid handling robots (Hamilton STAR, Opentrons OT-2, Tecan EVO), integrating lab equipment, managing deck layouts and resources (plates, tips, containers), reading plates, or creating reproducible laboratory protocols. Applicable for both simulated protocols and physical hardware control.
Create irresistible offers and pitches using Alex Hormozi's methodology from $100M Offers. Guides through value equation, guarantee frameworks, pricing psychology, and creating offers "too good not to take" for any product or service.
Use the nasdaq_quote tool to fetch a US equity quote (free; delayed) with lightweight caching and latency metadata.