# CloudMaxi0x Trade Filter Validator > CloudMaxi0x Trade Filter Validator is a paid API for AI agents from cloudmaxi0x.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-09-14). Tests a trade filter against a permutation null hypothesis to determine whether its selection lift is statistically distinguishable from chance, with optional gross-return and claimed-lift gap reporting. ## Facts - Endpoint: GET https://cloudmaxi0x.com/v1/validate/filter - Price: $0.25/call - Payment: x402 - Status: unknown - Last checked: 2026-09-14 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/cloudmaxi0x-trade-filter-validator-e9e9752f - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ND2ixKR9L6Cs2VUPXzMnL Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability cloudmaxi0x-trade-filter-validator-e9e9752f ``` Example prompt: Run a permutation audit on my crypto trade filter — I have 200 candidate trades with 5 features each (all computed before entry), returns in R, and entry timestamps. Use 100 permutations and check whether my claimed lift of 0.35 R holds up against the null. ## When to prefer this Choose this endpoint when you need to statistically validate whether a trade filter's selection lift exceeds what random permutation of the same features would produce — specifically when you want a permutation null hypothesis test rather than a simple Sharpe or t-test. Prefer this over generic statistics APIs when the input is trade-level feature rows with R-denominated returns and you want an honest audit that accounts for baseline performance, overlap detection, and claimed-vs-actual lift gaps in a crypto trading context. ## Known failure modes - Fewer than 120 trades supplied — request rejected with validation error - Features matrix row count does not match returns array length — schema mismatch error - Features contain values not computable before trade entry (lookahead) — cannot be fully detected, audit proceeds with caveat - Entry/exit timestamp arrays length mismatch — error returned - Permutations below minimum of 20 — rejected - p-value floor limited by 1/(permutations+1) — very low p-values unresolvable with few permutations - Returns include post-fee costs but gross_returns_r omitted — audit proceeds but fee-snooping check skipped ## How this service works Deterministic, verifiable crypto market data and honest backtest audits. Use GET /v1/data/ohlcv for exact OHLCV over a half-open range with a SHA-256 Merkle manifest - only closed candles are returned, exchange decimal strings are preserved byte for byte, so the same query always yields the same root. Use GET /v1/data/proof to verify one candle against a root you already hold. Use POST /v1/validate/trades to find out whether a list of trade returns can be distinguished from luck, and POST /v1/validate/filter to test a trade filter against a permutation null. GET /, /v1/schema and /v1/data/sources are free. ## Output Returns a p-value indicating whether the filter's lift is distinguishable from chance, the measured lift in R over the unfiltered baseline, the permutation null distribution, and optionally the gap between claimed out-of-sample lift and audited lift; also reports any detected overlapping trade windows that would invalidate walk-forward testing. ## Request schema (JSON Schema) ```json { "type": "object", "properties": { "exit_ms": { "anyOf": [ { "type": "array", "items": { "type": "integer" } }, { "type": "null" } ], "title": "Exit Ms", "default": null, "description": "Optional exit timestamps (epoch ms)." }, "entry_ms": { "anyOf": [ { "type": "array", "items": { "type": "integer" } }, { "type": "null" } ], "title": "Entry Ms", "default": null, "description": "Optional entry timestamps (epoch ms). Supplying these lets us detect overlapping trades, which silently invalidate walk-forward testing." }, "features": { "type": "array", "items": { "type": "array", "items": { "type": "number" } }, "title": "Features", "minItems": 120, "description": "One row per candidate trade, in chronological order. Every value must have been computable strictly BEFORE that trade's entry - this is the assumption the whole audit rests on, and the one we can only partly check." }, "returns_r": { "type": "array", "items": { "type": "number" }, "title": "Returns R", "minItems": 120, "description": "Outcome of each candidate trade in R, same order as `features`. Include the trades your filter rejected: without them there is no baseline to measure lift against, and lift is the entire question." }, "permutations": { "type": "integer", "title": "Permutations", "default": 50, "minimum": 20, "description": "Permutations used to build the chance distribution. The p-value cannot resolve below 1/(permutations+1)." }, "feature_names": { "type": "array", "items": { "type": "string" }, "title": "Feature Names", "minItems": 1 }, "claimed_lift_r": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "title": "Claimed Lift R", "default": null, "description": "Optional: the out-of-sample edge your own backtest reported for the filtered subset, in R above the unfiltered baseline. We report the gap between your number and our strict replay." }, "gross_returns_r": { "anyOf": [ { "type": "array", "items": { "type": "number" } }, { "type": "null" } ], "title": "Gross Returns R", "default": null, "description": "Optional but strongly recommended: the same trades BEFORE fees and slippage. Any feature that is part of how `returns_r` is computed - a fee c … (truncated) ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/cloudmaxi0x-trade-filter-validator-e9e9752f/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from cloudmaxi0x.com](https://www.zero.xyz/host/cloudmaxi0x.com/llms.txt)