← The evidence ledger
Evidence row 569301
Observed , by probe.mcp/1.
- Kind
- mcp.tools
- About
- endpoint 489a615e-77aa-4326-8975-8da98b91a390
- Recorded
- Previous row
- None: the first of its kind about this subject
- Body SHA-256
- f49a9b63b4d49037367abd3e746872624687ccf86efffdaeb775f08d74413697
- Leaf
- 0x5276e0a544c44a2e8f8a572bed32baf5afe46621e1a0511d398ea1560f954daf
What was observed
{
"count": 7,
"tools": [
{
"description": "Quick single-pair diagnostic. IC with risk prediction for both model classes. Include variances for sign detectability. Requires X-Wallet header with your EVM wallet address (0x...). First 5 queries are free trial.",
"inputSchema": {
"properties": {
"coupling_value": {
"description": "IC or coupling value",
"type": "number"
},
"i": {
"description": "First variable name",
"type": "string"
},
"j": {
"description": "Second variable name",
"type": "string"
},
"sample_size": {
"minimum": 10,
"type": "integer"
},
"variance_i": {
"type": "number"
},
"variance_j": {
"type": "number"
}
},
"required": [
"i",
"j",
"coupling_value",
"sample_size"
],
"type": "object"
},
"name": "factorguide_diagnose"
},
{
"description": "Plain-language explanation of a previous navigate response, including wave mechanics grounding for observational cost guidance. Requires a prediction_hash from a prior factorguide_navigate call. Consumes 1 query allocation. Available for starter and professional tiers. Requires X-Wallet header with your EVM wallet address (0x...). First 5 queries are free trial.",
"inputSchema": {
"properties": {
"prediction_hash": {
"description": "prediction_hash from a previous navigate response",
"type": "string"
}
},
"required": [
"prediction_hash"
],
"type": "object"
},
"name": "factorguide_explain"
},
{
"description": "Map the factorization terrain of your model. Send coupling structure (precision matrix preferred for n>2; covariance matrix recommended if sign or CC information is needed) and receive a block-diagonal strategy with calibrated risk prediction. Answers: 'How should I factorize, and what will it cost me?' Optional: set report_sign_detectability=true to get sign(ρ) for high-leverage pairs at no additional cost when variance ratio > 20. Requires X-Wallet header with your EVM wallet address (0x...). First 5 queries are free trial.",
"inputSchema": {
"$defs": {
"CorrelationMatrixInput": {
"properties": {
"correlation_matrix": {
"items": {
"items": {
"type": "number"
},
"type": "array"
},
"title": "Correlation Matrix",
"type": "array"
}
},
"required": [
"correlation_matrix"
],
"title": "CorrelationMatrixInput",
"type": "object"
},
"CostModel": {
"enum": [
"cubic",
"quadratic",
"linear",
"information_cost"
],
"title": "CostModel",
"type": "string"
},
"CovarianceMatrixInput": {
"properties": {
"covariance_matrix": {
"items": {
"items": {
"type": "number"
},
"type": "array"
},
"title": "Covariance Matrix",
"type": "array"
}
},
"required": [
"covariance_matrix"
],
"title": "CovarianceMatrixInput",
"type": "object"
},
"DistributionDiagnostics": {
"properties": {
"excess_kurtosis": {
"anyOf": [
{
"items": {
"type": "number"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Excess Kurtosis"
},
"skewness": {
"anyOf": [
{
"items": {
"type": "number"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Skewness"
},
"spearman_rank_correlation": {
"anyOf": [
{
"items": {
"items": {
"type": "number"
},
"type": "array"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Spearman Rank Correlation"
}
},
"title": "DistributionDiagnostics",
"type": "object"
},
"EdgeListInput": {
"properties": {
"edge_list": {
"items": {},
"title": "Edge List",
"type": "array"
},
"n": {
"minimum": 2,
"title": "N",
"type": "integer"
}
},
"required": [
"edge_list",
"n"
],
"title": "EdgeListInput",
"type": "object"
},
"ModelClass": {
"enum": [
"filtering",
"hierarchical",
"deep_hierarchy",
"graphical_model",
"gp",
"vae",
"unknown",
"constitutive",
"inductive"
],
"title": "ModelClass",
"type": "string"
},
"PrecisionMatrixInput": {
"properties": {
"precision_matrix": {
"items": {
"items": {
"type": "number"
},
"type": "array"
},
"title": "Precision Matrix",
"type": "array"
}
},
"required": [
"precision_matrix"
],
"title": "PrecisionMatrixInput",
"type": "object"
},
"TaskType": {
"enum": [
"inference",
"control"
],
"title": "TaskType",
"type": "string"
}
},
"properties": {
"accuracy_target": {
"default": 2,
"exclusiveMinimum": 1,
"maximum": 7,
"title": "Accuracy Target",
"type": "number"
},
"compute_budget": {
"anyOf": [
{
"type": "number"
},
{
"const": "minimize",
"type": "string"
}
],
"default": "minimize",
"title": "Compute Budget"
},
"cost_model": {
"$ref": "#/$defs/CostModel",
"default": "cubic"
},
"coupling": {
"anyOf": [
{
"$ref": "#/$defs/PrecisionMatrixInput"
},
{
"$ref": "#/$defs/CorrelationMatrixInput"
},
{
"$ref": "#/$defs/CovarianceMatrixInput"
},
{
"$ref": "#/$defs/EdgeListInput"
}
],
"title": "Coupling"
},
"distribution_diagnostics": {
"anyOf": [
{
"$ref": "#/$defs/DistributionDiagnostics"
},
{
"type": "null"
}
],
"default": null
},
"encoding_label": {
"anyOf": [
{
"maxLength": 128,
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Encoding Label"
},
"model_class": {
"$ref": "#/$defs/ModelClass",
"default": "unknown"
},
"report_marginal_ic": {
"default": false,
"title": "Report Marginal Ic",
"type": "boolean"
},
"report_sign_detectability": {
"default": false,
"title": "Report Sign Detectability",
"type": "boolean"
},
"sample_size": {
"minimum": 10,
"title": "Sample Size",
"type": "integer"
},
"synergy_check": {
"default": false,
"title": "Synergy Check",
"type": "boolean"
},
"task_type": {
"$ref": "#/$defs/TaskType",
"default": "inference"
},
"variable_names": {
"anyOf": [
{
"items": {
"type": "string"
},
"type": "array"
},
{
"type": "null"
}
],
"default": null,
"title": "Variable Names"
}
},
"required": [
"coupling",
"sample_size"
],
"title": "NavigateRequest",
"type": "object"
},
"name": "factorguide_navigate"
},
{
"description": "Detect coupling regime changes in time series via windowed IC. Specification pending — v1.1 target.",
"inputSchema": {
"properties": {},
"type": "object"
},
"name": "factorguide_regime_detect"
},
{
"description": "Complete the prediction loop — report inference diagnostics so future predictions improve. After running the approach FactorGuide recommended, return your ESS ratio, PSIS-khat, or log-likelihood gap. Zero additional computation required. Does not consume a query allocation.",
"inputSchema": {
"$defs": {
"ApproachTaken": {
"enum": [
"factorized",
"structured",
"hybrid"
],
"title": "ApproachTaken",
"type": "string"
}
},
"properties": {
"actual_mse_ratio": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Actual Mse Ratio"
},
"approach_taken": {
"$ref": "#/$defs/ApproachTaken"
},
"ess_ratio": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Ess Ratio"
},
"log_lik_gap": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Log Lik Gap"
},
"n_replications": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"default": null,
"title": "N Replications"
},
"prediction_hash": {
"title": "Prediction Hash",
"type": "string"
},
"psis_khat": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Psis Khat"
},
"runtime_seconds": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"default": null,
"title": "Runtime Seconds"
}
},
"required": [
"prediction_hash",
"approach_taken"
],
"title": "OutcomeReport",
"type": "object"
},
"name": "factorguide_report_outcome"
},
{
"description": "Submit payment proof after sending stablecoins to a FactorGuide wallet address. For x402: provide tx_hash and chain. For MPP: use in-band Authorization header instead — no separate submission needed.",
"inputSchema": {
"properties": {
"chain": {
"description": "Chain identifier, e.g. 'eip155:8453' or 'tempo:4217'",
"type": "string"
},
"tx_hash": {
"description": "On-chain transaction hash",
"type": "string"
}
},
"required": [
"tx_hash",
"chain"
],
"type": "object"
},
"name": "factorguide_submit_payment"
},
{
"description": "Detect hidden synergistic structure via Walsh-Hadamard spectral analysis. Accepts pre-computed Walsh coefficients — agent performs the transform locally and sends only the spectral summary. Specification pending — v1.1 target.",
"inputSchema": {
"properties": {
"ic_matrix_ref": {
"type": "string"
},
"n_samples": {
"type": [
"integer",
"null"
]
},
"n_variables": {
"type": "integer"
},
"transform_method": {
"enum": [
"exact",
"sampled"
],
"type": "string"
},
"walsh_coefficients": {
"properties": {
"order_0": {
"type": "number"
},
"order_1": {
"items": {
"type": "number"
},
"type": "array"
},
"order_2": {
"items": {
"properties": {
"coefficient": {
"type": "number"
},
"pair": {
"items": {
"type": "integer"
},
"type": "array"
}
},
"type": "object"
},
"type": "array"
},
"order_3": {
"items": {
"properties": {
"coefficient": {
"type": "number"
},
"triple": {
"items": {
"type": "integer"
},
"type": "array"
}
},
"type": "object"
},
"type": "array"
}
},
"type": "object"
}
},
"type": "object"
},
"name": "factorguide_synergy_detect"
}
]
}What the leaf hashes
{"body":"f49a9b63b4d49037367abd3e746872624687ccf86efffdaeb775f08d74413697","id":569301,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793139287235920,"prev":null,"subject":"489a615e-77aa-4326-8975-8da98b91a390","subject_kind":"endpoint"}Proof
Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (273461 rows).
- 0x5276e3e94b5dece710f6692d0e266083631115126c44e878f06f89d74f075f17
- 0x4bd2dde5f8a7bbde11be845716ef1377d396b59b1294a1df02d8916430ce3b6f
- 0xb69fbee0d56b9e18057215f099cb1adc3de3e15094cf1ad7b51f2dc6b7ad9f2c
- 0x25bd3ab8042d7090264013ffa64615a1856ed39bcbca0fd9239ebda2ca05deda
- 0xfbedbc0a588bc287e75afda4ce8824bd52d9435ee4b8af006b75d7864f95f88f
- 0xe4db616b8f0a4eb381187f40c91629ac52d3a37ddc78ac089772c3c129bf76f0
- 0x216a1bf52c3b555fcf70aa70f22aaf2674bb9722f5f2e33c0190a7f42b0814c2
- 0xbc140d23cb12b662e2a12b0acea112f950a36510da5b381a809898de14ae1619
- 0xd457f6b6343800d817a6233096c88bcf3229b8251d90adcaaa53b4f534676e03
- 0x2c7eacabc74fc573690fc9a970f9c763fd5121c991acbecc3d1007fac5a9d364
- 0xf08d73dbf9855d720c0a2a3ccd264381a0c543dccc463bf9362cb3ec368ba1ac
- 0xd57b5a86cf210d9ed4e220de5668cf59c88f82934bf7c8ef9e6b3e894577973c
- 0x996f3d89f9508378f3c194c9828b500725dd599c52fd040349190982338d96f2
- 0x9ea0c6a53f80a30b6f13671109f98a000cf98e581875129f4be4b57131d06364
- 0xb78ea6a255dd06e2f402a1a733bca392fa6243920bcba95e8b80bdfc6ce5f553
- 0x3ed50f053eca72dfd3a9d45a11935240bfe691e57835c367ddebe2cbc49efe9d
- 0x0e01aa9525097570a6edaf32bfc959de57bf5c24317cf10c0716affea85ca60d
- 0xa20d48798a34aba12eb9c7297722982d910f06c148f5e27ac59307422964a585
- 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
- Day root
- 0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
- Chained
- 0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
- Published
- On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4