agentsclimarketplace

Llmquant crypto

Skill LLMQuant/skills/skills/llmquant-crypto

Reusable Skills for LLMQuant Agent, Claude Code, Claude.ai, Cursor, Hermes Agent, OpenClaw and Codex, grounded in LLMQuant Data

Install
npx -y skills add LLMQuant/skills --skill llmquant-crypto

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Router skill for LLMQuant crypto workflows. Use when the user needs crypto market regime analysis, token research, perpetual funding, basis, leverage, liquidity, or cross-asset crypto context.

SKILL.md

2.2 KB, as published. Nobody here has run it

LLMQuant Crypto

This category routes crypto research and trading-context workflows. It covers market regime, token-level diligence, and perpetual funding or basis monitoring.

Routing Rules

  1. Identify the asset, chain, venue, horizon, benchmark, and requested decision.
  2. Select the closest workflow below.
  3. Open only that workflow and any referenced local resources.
  4. Use LLMQuant Data for crypto prices, liquidity, funding, open interest, on-chain context, macro, ETF, and risk inputs.
  5. Report timestamps, venue coverage, observation windows, stale notices, and unavailable future inputs.

Workflow Index

User intentWorkflow
Diagnose the crypto market regime across BTC, ETH, majors, liquidity, leverage, and macro.workflows/crypto-market-regime.md
Build a token or protocol research memo with tokenomics, usage, valuation, and risk evidence.workflows/crypto-token-research.md
Monitor perpetual funding, basis, open interest, and leverage crowding.workflows/crypto-perp-funding-monitor.md

LLMQuant Data Contract

Prefer LLMQuant Data when available. The workflows may need these data capabilities:

  • Retrieve crypto spot prices, OHLCV history, realized volatility, drawdowns, correlations, and liquidity.
  • Retrieve perpetual funding, basis, open interest, liquidations, exchange flows, and venue-level timestamps.
  • Retrieve token supply, unlock schedules, protocol usage, revenue, TVL, holder concentration, governance, and security-risk context.
  • Retrieve macro, rates, liquidity, ETF, and equity-market inputs that affect crypto risk appetite.

Fallback:

  • If on-chain, funding, or venue-level data is unavailable, name the missing input and continue only with available price, macro, or user-provided evidence.
  • Do not infer live funding, liquidity, TVL, or holder behavior from memory.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.