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Examples — Reading the Market, Not Just the Numbers

Each metric in cryptospect-cli answers one question. The real signal comes from combining them — following a thread from macro context down to specific conditions. The examples below walk through three common lines of inquiry and show you exactly how to chain the commands.


Example 1: "Is this rally real, or is it a BTC trap?"

You've noticed the total market cap is up 4% today. Before chasing it, you want to know: is this a genuine broad move, or is it BTC carrying an otherwise soft market?

Step 1 — Establish the macro regime

cryptospect-cli market-regime --detail full

This is always your first call. It tells you the structural state in a single label — Alt-Season, Institutional Build, Flight to Safety, etc. — and anchors everything else you're about to read.

Suppose the output shows:

"regime": "Institutional Build",
"dominance_trend": "rising",
"market_breadth_score": 0.44

That's a yellow flag: BTC dominance is rising, and breadth is mixed (44% of coins are green). BTC may be outperforming while alts lag. Let's check.

Step 2 — Verify participation

cryptospect-cli market-breadth

market-breadth gives you the weighted composite of how many coins are green across 1h, 24h, 7d, and 30d windows, plus an explicit divergence_detected flag.

If you see:

"market_breadth_score": 0.41,
"divergence_detected": true,
"btc_change_24h_pct": 4.2

That's a Ghost Rally: BTC is up 4.2% but fewer than half the market is participating. The rally is mechanically narrow.

Step 3 — Check if the aggression is real

cryptospect-cli flow-tension

flow-tension tells you how the move is happening: is it backed by aggressive spot buying (CVD), or are people just piling into leveraged longs?

If CVD is aggressive_buy but funding is overheated (> 0.30% per 8h), you've found the trap: spot demand exists but leveraged longs are crowded and paying dearly to stay open. The move is fragile.

LLM prompt to tie it together:

"I ran three cryptospect-cli commands. Here's the JSON output from market-regime, market-breadth, and flow-tension. The regime is Institutional Build, breadth is 0.41 with divergence detected, and flow-tension shows aggressive buy CVD but overheated funding. Is this rally safe to chase, or is this a Ghost Rally setup?"


Example 2: "Is there enough fuel left for the run to continue?"

The market has been in a solid uptrend for three weeks. You want to know if there's still dry powder available, or if the rally has already consumed its fuel supply.

Step 1 — Check dry powder

cryptospect-cli stablecoin-power --detail extended

stablecoin-power is your fuel gauge: the ratio of stablecoin market cap to volatile-asset market cap. A high ratio means sidelined capital hasn't deployed yet. A low ratio means the tank is nearly empty.

Look at two fields together:

  • stable_power_ratio — the ratio itself (High >0.15, Normal 0.07–0.15, Low <0.07)
  • supply_trend_7d — is stablecoin supply growing, stable, or shrinking?

If stable_power_ratio is 0.06 and supply_trend_7d is contracting, that's not just "fuel depleted" — it's capital flight. Money is leaving crypto entirely, not just rotating into volatile assets.

Step 2 — Check how the conviction is being expressed

cryptospect-cli liquidity-pulse

Low stablecoin power becomes more or less urgent depending on how actively the market is trading. A volume_to_mcap_ratio above 0.15 alongside low fuel means the market is burning hot on near-empty — a blow-off risk. A low ratio with low fuel means the market is coasting quietly; less immediate danger.

Step 3 — See where remaining capital is rotating

cryptospect-cli momentum-divergence

Even when aggregate fuel is low, knowing which tier is receiving flows matters. momentum-divergence segments the top 200 coins into Large (top 10), Mid (11–50), and Small (51–200) and reports whether capital is moving down the risk curve or concentrating into mega-caps.

A risk_on label with tail_extension: true means capital is rotating aggressively into smaller assets — historically this coincides with late-cycle speculative peaks. Pair that with stablecoin-power showing Low + contracting supply, and you have a classic blow-off setup.

LLM prompt to tie it together:

"Here's JSON output from stablecoin-power, liquidity-pulse, and momentum-divergence. Stablecoin power is 0.06 with contracting supply, liquidity pulse is 0.18 (high), and momentum-divergence shows risk_on with tail_extension true. What does this combination tell me about where we are in the cycle, and what's the appropriate posture?"


Example 3: "The market just sold off hard. Is this a flush or the beginning of something worse?"

You woke up to a 12% daily drop. You want to know: is this a leveraged unwind that will stabilize, or is there a macro story underneath it?

Step 1 — Understand the structural state first

cryptospect-cli market-regime

The regime label is your first read. Capitulation requires high trading conviction alongside collapsing breadth — it's different from Structural Decay, which is a slow bleed. Flight to Safety means capital is concentrating into BTC rather than leaving crypto. These require different responses.

Step 2 — Diagnose the mechanics

cryptospect-cli flow-tension --detail extended

Selloffs have different causes. flow-tension separates them:

  • Leveraged unwind: OI unwinding (>-5%) + CVD aggressive_sell → forced liquidations clearing the deck. Often self-limiting once OI is flushed.
  • Spot distribution: CVD aggressive_sell + OI stable → holders selling into bids. More persistent, no forced-liquidation floor.
  • Funding normalization: Funding negative (shorts paying longs) → bearish sentiment dominant. If CVD is turning neutral or positive alongside this, exhaustion may be near.

Step 3 — Check whether the macro backdrop amplifies the risk

cryptospect-cli stablecoin-power

If supply_trend_7d is contracting during a selloff, capital is being redeemed back to fiat — not rotating into stablecoins for re-entry. That's a fundamentally different situation from a normal correction where stablecoin supply grows as people take risk off.

Also check:

cryptospect-cli china-m2

A China M2 slowing classification during a crypto selloff adds macro weight. China's M2 (~$47T, roughly 2× the US) has historically shown strong correlation to BTC price cycles. Tightening monetary conditions there amplify crypto drawdowns.

LLM prompt to tie it together:

"Crypto just dropped 12% today. Here's the JSON output from market-regime, flow-tension, stablecoin-power, and china-m2. Regime is Flight to Safety, flow-tension shows OI unwinding with aggressive sell CVD, stablecoin supply is contracting, and China M2 is slowing. Is this a leverage flush I should buy, or something more structural?"


Quick Reference: Which Metrics Talk to Each Other

If you're asking... Start here Then check
Is this rally real? market-regime market-breadthflow-tension
Is there fuel for continuation? stablecoin-power liquidity-pulsemomentum-divergence
Is this selloff a flush or flight? flow-tension stablecoin-powerchina-m2
Where is capital rotating? momentum-divergence market-breadthflow-tension
What's the overall sentiment backdrop? fear-greed-index market-regime

market-regime aggregates breadth and dominance internally and is always a good first call. Every other metric adds a layer of why.


Running All Relevant Signals at Once

For a full macro snapshot, feed all outputs to an LLM in one shot:

cryptospect-cli market-regime --detail full > mr.json
cryptospect-cli stablecoin-power --detail full >> mr.json
cryptospect-cli flow-tension --detail full >> mr.json
cryptospect-cli market-breadth --detail full >> mr.json

Then prompt:

"Here is JSON output from four cryptospect-cli metrics: market-regime, stablecoin-power, flow-tension, and market-breadth. Synthesize these into a single market assessment. What regime are we in, how much fuel remains, and is the current price action conviction-backed or fragile? End with a one-sentence recommended posture."

Use --detail full when feeding to an LLM — it includes the threshold values and metric descriptions the model needs to interpret the numbers correctly. Use --detail basic for automated loops where token economy matters.