CryptoScreener is the live filterable market table inside 24HourCrypto. It turns a broad market into an exact result set you can inspect, save, and reuse. The table is the evidence layer beneath Screen Analysis™ and Market Reports: every summary should trace back to coins that passed explicit conditions.

A useful session has four stages: ask, define, inspect, save. Ask a market question. Define a fair universe and measurable conditions. Inspect whether the survivors actually express the idea. Save the result only when the filter can be explained in plain English.

A screen is not “coins I like.” It is a reproducible rule for which coins belong in the list right now.

Begin with a sentence that includes a universe, a condition, and a purpose. “What is moving?” is too broad. “Which top-500 coins are positive across 1h, 24h, and 7d, with at least $10M in daily volume?” can be translated into filters and checked later.

Good question patterns include:

• Leadership: Which large assets lead over 7d?
• Breadth: How much of a category is green today?
• Attention: Which established coins have unusual volume relative to size?
• Risk: Which top-500 names are weak across all tracked windows?
• Recovery: Which deeply discounted assets are improving, with real participation?

Avoid adding conditions merely because they are available. Every filter changes the population and therefore changes the meaning of the answer.

First decide what is eligible. Rank and market cap create size universes. Categories create thematic universes. Exchanges answer availability questions. A named-coin list creates a fixed peer group. This first step prevents accidental comparisons between assets with radically different liquidity and risk profiles.

Then add the condition you want to study: percent-change ranges, signal, trend, momentum, risk, ATH distance, supply, volume, or Vol/Mcap. Applying the signal second makes the denominator clear. “12 allGreen coins” means little until you know whether the starting universe contained 20 coins or 2,000.

If a filter produces no results, relax one condition at a time. That teaches you which assumption removed the market instead of turning the screen into an opaque pile of compromises.

Filtering decides membership; sorting decides reading order. Sort descending by 24h change to inspect daily leaders, ascending to inspect laggards, by market cap to see who dominates the set, or by volume to see where trading activity is concentrated. A sort never changes which coins match.

Visible columns should support the claim. A momentum screen usually needs signal, trend, 1h/24h/7d changes, volume, market cap, and Vol/Mcap. A dilution screen needs market cap, FDV, circulating supply, total supply, and max supply. Hiding unrelated columns reduces scanning cost without changing the saved universe.

After sorting, inspect the middle and bottom—not only the first row. If one outlier creates the entire story, describe it as an outlier rather than claiming the list moved together.

Start with Top 500, add allGreen, require meaningful 24h volume, and sort by 24h change descending. This asks for multi-window strength among established names. Check Vol/Mcap so one thin asset does not dominate.

Select one category, keep all directional outcomes, and sort by 24h change. Read the count and breadth before filtering to winners. This distinguishes “the theme moved” from “two members moved.”

Start with Top 200 or a large-cap bucket, add allRed, and sort 24h change ascending. The result identifies broad weakness in relatively established names. It does not predict a rebound or recommend selling; it creates a focused risk-monitoring set.

Save each recipe under a name that states both universe and condition, such as “Top-500 All-Green With Volume.”

Screen Analysis™ (SA™) reads the entire current result set. Use it as a quality check on the question. Breadth shows whether strength or weakness is shared. Benchmark comparison shows whether the median coin is outperforming Bitcoin. Concentration shows whether a few large names dominate. Liquidity describes attention relative to size. Category mix reveals hidden thematic overlap.

If the plain-English read surprises you, return to the table. The filter may be too broad, too narrow, or dominated by an unintended subgroup. For example, a “market leaders” screen can really be a single-category bet if most results share one tag.

SA does not replace the rows. It tells you where to inspect them. Open named leaders, laggards, or high-attention coins to connect the aggregate read to evidence.

Saving captures the filter definition, sort, and visible evidence—not a frozen snapshot of today’s winners. When market data changes, membership and Screen Analysis can change. Name the rule, not the current outcome. “Mid-Cap Breakouts” remains meaningful next week; “Coins Going Up Today” is harder to distinguish from dozens of other screens.

Add a description that records intent and important boundaries: “$100M–$1B market cap, +5% or more over 24h, sorted by daily return.” A reader should understand what belongs without reverse-engineering every chip.

Revisit saved screens to ask what changed: count, breadth, leaders, liquidity, benchmark performance, or category mix. A changing answer is the value of a live screen, not evidence that the screen failed.

User-facing pages read the local database from the latest completed sync. They do not pause on each click to query a vendor. Empty fields mean data is unavailable locally; old values can reflect sync timing. Never convert “unknown” into a confident zero.

1. Can you state the question in one sentence?
2. Is the starting universe fair for the comparison?
3. Does each filter serve the question?
4. Does the sort expose leaders, laggards, size, or activity appropriately?
5. Are the necessary evidence columns visible?
6. Did you inspect breadth and the middle of the list?
7. Does the name describe a durable rule?

If all seven answers are clear, the screen is ready to share or place inside a Guide or Market Report.