llmquant-crypto
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.
npx skills add LLMQuant/skills --skill llmquant-crypto --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 intent | Workflow | |---|---| | Diagnose the crypto market regime across BTC, ETH, majors, liquidity, leverage, and macro. | [`workflows/crypto-market-regime.md`](workflows/crypto-market-regime.md) | | Build a token or protocol research memo with tokenomics, usage, valuation, and risk evidence. | [`workflows/crypto-token-research.md`](workflows/crypto-token-research.md) | | Monitor perpetual funding, basis, open interest, and leverage crowding. | [`workflows/crypto-perp-funding-monitor.md`](workflows/crypto-perp-funding-monitor.md) | ## LLMQuant Data Contract Prefer
- Routing Rules
- Workflow Index
- LLMQuant Data Contract
What does the llmquant-crypto skill do?
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.
How do I install it?
Run `npx skills add LLMQuant/skills --skill llmquant-crypto --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LLMQuant/skills, a repository with 183 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.