{
  "components": {
    "schemas": {
      "BatchEffectRequest": {
        "properties": {
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ],
            "description": "Graph shared by every query."
          },
          "observations": {
            "anyOf": [
              {
                "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
                "examples": [
                  [
                    [
                      0.4,
                      -1.2,
                      0.9
                    ],
                    [
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                      0.3,
                      -0.1
                    ]
                  ]
                ],
                "items": {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "description": "Sample shared by every query.",
            "title": "Observations"
          },
          "queries": {
            "items": {
              "$ref": "#/components/schemas/EffectRequest"
            },
            "title": "Queries",
            "type": "array"
          }
        },
        "required": [
          "queries"
        ],
        "title": "BatchEffectRequest",
        "type": "object"
      },
      "BatchEffectResponse": {
        "properties": {
          "results": {
            "items": {
              "$ref": "#/components/schemas/EffectResult"
            },
            "title": "Results",
            "type": "array"
          }
        },
        "required": [
          "results"
        ],
        "title": "BatchEffectResponse",
        "type": "object"
      },
      "BatchInterventionRequest": {
        "properties": {
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ]
          },
          "interventions": {
            "items": {
              "additionalProperties": {
                "type": "number"
              },
              "type": "object"
            },
            "title": "Interventions",
            "type": "array"
          },
          "observations": {
            "anyOf": [
              {
                "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
                "examples": [
                  [
                    [
                      0.4,
                      -1.2,
                      0.9
                    ],
                    [
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                      0.3,
                      -0.1
                    ]
                  ]
                ],
                "items": {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "title": "Observations"
          },
          "samples": {
            "anyOf": [
              {
                "maximum": 4096.0,
                "minimum": 1.0,
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "title": "Samples"
          }
        },
        "required": [
          "interventions"
        ],
        "title": "BatchInterventionRequest",
        "type": "object"
      },
      "BatchInterventionResponse": {
        "properties": {
          "results": {
            "items": {
              "$ref": "#/components/schemas/InterventionResult"
            },
            "title": "Results",
            "type": "array"
          }
        },
        "required": [
          "results"
        ],
        "title": "BatchInterventionResponse",
        "type": "object"
      },
      "CounterfactualRequest": {
        "properties": {
          "factual": {
            "additionalProperties": {
              "anyOf": [
                {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                {
                  "type": "number"
                }
              ]
            },
            "description": "A complete assignment for the individuals of interest; every variable in the graph must appear.",
            "title": "Factual",
            "type": "object"
          },
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ]
          },
          "interventions": {
            "additionalProperties": {
              "type": "number"
            },
            "title": "Interventions",
            "type": "object"
          },
          "observations": {
            "anyOf": [
              {
                "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
                "examples": [
                  [
                    [
                      0.4,
                      -1.2,
                      0.9
                    ],
                    [
                      -0.7,
                      0.3,
                      -0.1
                    ]
                  ]
                ],
                "items": {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "title": "Observations"
          },
          "targets": {
            "anyOf": [
              {
                "items": {
                  "type": "string"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "title": "Targets"
          }
        },
        "required": [
          "factual",
          "interventions"
        ],
        "title": "CounterfactualRequest",
        "type": "object"
      },
      "CounterfactualResult": {
        "properties": {
          "assumptions": {
            "items": {
              "type": "string"
            },
            "title": "Assumptions",
            "type": "array"
          },
          "counterfactual": {
            "additionalProperties": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "title": "Counterfactual",
            "type": "object"
          },
          "delta": {
            "additionalProperties": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "description": "Counterfactual minus factual.",
            "title": "Delta",
            "type": "object"
          },
          "factual": {
            "additionalProperties": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "title": "Factual",
            "type": "object"
          },
          "identification": {
            "additionalProperties": {
              "type": "string"
            },
            "title": "Identification",
            "type": "object"
          },
          "provenance": {
            "additionalProperties": true,
            "title": "Provenance",
            "type": "object"
          },
          "uncertainty": {
            "additionalProperties": {
              "type": "number"
            },
            "title": "Uncertainty",
            "type": "object"
          }
        },
        "required": [
          "factual",
          "counterfactual",
          "delta",
          "uncertainty",
          "identification",
          "assumptions",
          "provenance"
        ],
        "title": "CounterfactualResult",
        "type": "object"
      },
      "DiscoverRequest": {
        "properties": {
          "observations": {
            "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
            "examples": [
              [
                [
                  0.4,
                  -1.2,
                  0.9
                ],
                [
                  -0.7,
                  0.3,
                  -0.1
                ]
              ]
            ],
            "items": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "title": "Observations",
            "type": "array"
          },
          "threshold": {
            "default": 0.5,
            "description": "Edge probability cut-off.",
            "maximum": 1.0,
            "minimum": 0.0,
            "title": "Threshold",
            "type": "number"
          },
          "variables": {
            "anyOf": [
              {
                "items": {
                  "type": "string"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "description": "Variable names, in column order.",
            "title": "Variables"
          }
        },
        "required": [
          "observations"
        ],
        "title": "DiscoverRequest",
        "type": "object"
      },
      "DiscoverResult": {
        "properties": {
          "assumptions": {
            "items": {
              "type": "string"
            },
            "title": "Assumptions",
            "type": "array"
          },
          "edge_probabilities": {
            "items": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "title": "Edge Probabilities",
            "type": "array"
          },
          "edges": {
            "items": {
              "additionalProperties": true,
              "type": "object"
            },
            "title": "Edges",
            "type": "array"
          },
          "graph": {
            "additionalProperties": true,
            "description": "The discovered DAG, serialised.",
            "title": "Graph",
            "type": "object"
          },
          "provenance": {
            "additionalProperties": true,
            "title": "Provenance",
            "type": "object"
          },
          "uncertainty": {
            "title": "Uncertainty",
            "type": "number"
          }
        },
        "required": [
          "graph",
          "edges",
          "edge_probabilities",
          "uncertainty",
          "assumptions",
          "provenance"
        ],
        "title": "DiscoverResult",
        "type": "object"
      },
      "EdgePayload": {
        "properties": {
          "edge_type": {
            "default": "causal",
            "description": "causal or latent.",
            "title": "Edge Type",
            "type": "string"
          },
          "source": {
            "title": "Source",
            "type": "string"
          },
          "strength": {
            "default": 1.0,
            "title": "Strength",
            "type": "number"
          },
          "target": {
            "title": "Target",
            "type": "string"
          }
        },
        "required": [
          "source",
          "target"
        ],
        "title": "EdgePayload",
        "type": "object"
      },
      "EffectRequest": {
        "properties": {
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ]
          },
          "observations": {
            "anyOf": [
              {
                "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
                "examples": [
                  [
                    [
                      0.4,
                      -1.2,
                      0.9
                    ],
                    [
                      -0.7,
                      0.3,
                      -0.1
                    ]
                  ]
                ],
                "items": {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "title": "Observations"
          },
          "outcome": {
            "examples": [
              "y"
            ],
            "title": "Outcome",
            "type": "string"
          },
          "treatment": {
            "examples": [
              "x"
            ],
            "title": "Treatment",
            "type": "string"
          },
          "x0": {
            "description": "Baseline treatment value.",
            "examples": [
              -1.0
            ],
            "title": "X0",
            "type": "number"
          },
          "x1": {
            "description": "Comparison treatment value.",
            "examples": [
              1.0
            ],
            "title": "X1",
            "type": "number"
          }
        },
        "required": [
          "treatment",
          "outcome",
          "x0",
          "x1"
        ],
        "title": "EffectRequest",
        "type": "object"
      },
      "EffectResult": {
        "properties": {
          "adjustment_set": {
            "items": {
              "type": "string"
            },
            "title": "Adjustment Set",
            "type": "array"
          },
          "assumptions": {
            "items": {
              "type": "string"
            },
            "title": "Assumptions",
            "type": "array"
          },
          "causal_paths": {
            "items": {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "title": "Causal Paths",
            "type": "array"
          },
          "confidence": {
            "description": "Zero when the effect is not identified from the graph.",
            "maximum": 1.0,
            "minimum": 0.0,
            "title": "Confidence",
            "type": "number"
          },
          "effect": {
            "description": "E[Y | do(T=x1)] - E[Y | do(T=x0)].",
            "title": "Effect",
            "type": "number"
          },
          "identification": {
            "description": "no_causal_path, no_backdoor_path, backdoor_adjustment or not_identified.",
            "title": "Identification",
            "type": "string"
          },
          "provenance": {
            "additionalProperties": true,
            "title": "Provenance",
            "type": "object"
          },
          "uncertainty": {
            "description": "Calibrated standard deviation of the estimate.",
            "title": "Uncertainty",
            "type": "number"
          }
        },
        "required": [
          "effect",
          "uncertainty",
          "confidence",
          "identification",
          "adjustment_set",
          "causal_paths",
          "assumptions",
          "provenance"
        ],
        "title": "EffectResult",
        "type": "object"
      },
      "ErrorResponse": {
        "properties": {
          "detail": {
            "title": "Detail",
            "type": "string"
          }
        },
        "required": [
          "detail"
        ],
        "title": "ErrorResponse",
        "type": "object"
      },
      "ExplainRequest": {
        "properties": {
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ]
          },
          "outcome": {
            "title": "Outcome",
            "type": "string"
          },
          "treatment": {
            "title": "Treatment",
            "type": "string"
          }
        },
        "required": [
          "treatment",
          "outcome"
        ],
        "title": "ExplainRequest",
        "type": "object"
      },
      "ExplainResult": {
        "properties": {
          "adjustment_set": {
            "items": {
              "type": "string"
            },
            "title": "Adjustment Set",
            "type": "array"
          },
          "assumptions": {
            "items": {
              "type": "string"
            },
            "title": "Assumptions",
            "type": "array"
          },
          "causal_paths": {
            "items": {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "title": "Causal Paths",
            "type": "array"
          },
          "confounders": {
            "items": {
              "type": "string"
            },
            "title": "Confounders",
            "type": "array"
          },
          "identified": {
            "title": "Identified",
            "type": "boolean"
          },
          "mediators": {
            "items": {
              "type": "string"
            },
            "title": "Mediators",
            "type": "array"
          },
          "open_backdoor_paths": {
            "items": {
              "items": {
                "type": "string"
              },
              "type": "array"
            },
            "title": "Open Backdoor Paths",
            "type": "array"
          },
          "provenance": {
            "additionalProperties": true,
            "title": "Provenance",
            "type": "object"
          },
          "reason": {
            "title": "Reason",
            "type": "string"
          },
          "strategy": {
            "title": "Strategy",
            "type": "string"
          },
          "unobserved_confounders": {
            "items": {
              "type": "string"
            },
            "title": "Unobserved Confounders",
            "type": "array"
          }
        },
        "required": [
          "identified",
          "strategy",
          "reason",
          "adjustment_set",
          "causal_paths",
          "open_backdoor_paths",
          "mediators",
          "confounders",
          "unobserved_confounders",
          "assumptions",
          "provenance"
        ],
        "title": "ExplainResult",
        "type": "object"
      },
      "GraphPayload": {
        "properties": {
          "edges": {
            "items": {
              "$ref": "#/components/schemas/EdgePayload"
            },
            "title": "Edges",
            "type": "array"
          },
          "variables": {
            "items": {
              "$ref": "#/components/schemas/VariablePayload"
            },
            "title": "Variables",
            "type": "array"
          }
        },
        "required": [
          "variables",
          "edges"
        ],
        "title": "GraphPayload",
        "type": "object"
      },
      "HealthResponse": {
        "properties": {
          "deterministic": {
            "title": "Deterministic",
            "type": "boolean"
          },
          "max_variables": {
            "description": "Largest graph the model accepts.",
            "title": "Max Variables",
            "type": "integer"
          },
          "model_version": {
            "title": "Model Version",
            "type": "string"
          },
          "parameters": {
            "description": "Total trainable parameters.",
            "title": "Parameters",
            "type": "integer"
          },
          "requires_llm": {
            "description": "Always false: inference is structural simulation.",
            "title": "Requires Llm",
            "type": "boolean"
          },
          "requires_observations": {
            "description": "Always true for interventional and counterfactual queries.",
            "title": "Requires Observations",
            "type": "boolean"
          },
          "status": {
            "title": "Status",
            "type": "string"
          }
        },
        "required": [
          "status",
          "model_version",
          "parameters",
          "max_variables",
          "deterministic",
          "requires_llm",
          "requires_observations"
        ],
        "title": "HealthResponse",
        "type": "object"
      },
      "InterventionRequest": {
        "properties": {
          "graph": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/GraphPayload"
              },
              {
                "type": "null"
              }
            ]
          },
          "interventions": {
            "additionalProperties": {
              "type": "number"
            },
            "description": "Variable name to the value it is held at.",
            "examples": [
              {
                "x": 1.0
              }
            ],
            "title": "Interventions",
            "type": "object"
          },
          "observations": {
            "anyOf": [
              {
                "description": "Observational sample: one row per observation, columns in the order of the graph's variables.",
                "examples": [
                  [
                    [
                      0.4,
                      -1.2,
                      0.9
                    ],
                    [
                      -0.7,
                      0.3,
                      -0.1
                    ]
                  ]
                ],
                "items": {
                  "items": {
                    "type": "number"
                  },
                  "type": "array"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "title": "Observations"
          },
          "samples": {
            "anyOf": [
              {
                "maximum": 4096.0,
                "minimum": 1.0,
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "description": "Number of simulated individuals.",
            "title": "Samples"
          },
          "targets": {
            "anyOf": [
              {
                "items": {
                  "type": "string"
                },
                "type": "array"
              },
              {
                "type": "null"
              }
            ],
            "description": "Restrict the response to these variables.",
            "title": "Targets"
          }
        },
        "required": [
          "interventions"
        ],
        "title": "InterventionRequest",
        "type": "object"
      },
      "InterventionResult": {
        "properties": {
          "assumptions": {
            "items": {
              "type": "string"
            },
            "title": "Assumptions",
            "type": "array"
          },
          "provenance": {
            "additionalProperties": true,
            "title": "Provenance",
            "type": "object"
          },
          "samples": {
            "additionalProperties": {
              "items": {
                "type": "number"
              },
              "type": "array"
            },
            "title": "Samples",
            "type": "object"
          },
          "std": {
            "additionalProperties": {
              "type": "number"
            },
            "title": "Std",
            "type": "object"
          },
          "values": {
            "additionalProperties": {
              "type": "number"
            },
            "description": "Mean of each variable under do().",
            "title": "Values",
            "type": "object"
          }
        },
        "required": [
          "values",
          "std",
          "samples",
          "assumptions",
          "provenance"
        ],
        "title": "InterventionResult",
        "type": "object"
      },
      "VariablePayload": {
        "properties": {
          "cardinality": {
            "anyOf": [
              {
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "description": "Number of categories for a discrete variable.",
            "title": "Cardinality"
          },
          "name": {
            "title": "Name",
            "type": "string"
          },
          "observed": {
            "default": true,
            "description": "An unobserved variable induces confounding that no adjustment set can block.",
            "title": "Observed",
            "type": "boolean"
          },
          "selection": {
            "default": false,
            "description": "A variable the observational regime conditions on.",
            "title": "Selection",
            "type": "boolean"
          },
          "variable_type": {
            "default": "continuous",
            "description": "One of continuous, binary or categorical.",
            "title": "Variable Type",
            "type": "string"
          }
        },
        "required": [
          "name"
        ],
        "title": "VariablePayload",
        "type": "object"
      }
    }
  },
  "info": {
    "description": "Interventional and counterfactual inference over structural causal models.\n\nNo language model is involved. Answers come from explicit structural\nsimulation: mechanisms are evaluated in topological order, an intervention pins\nits variable and its equation is skipped, and counterfactuals run abduction,\naction and prediction over recovered exogenous terms.\n\n**Observational data is required** for `/effect`, `/intervene` and\n`/counterfactual`. A DAG says which structural equations exist, not what they\nare, and two systems sharing a graph can have opposite effects, so the service\ninfers each system's mechanisms from its own sample. Requests without a sample\nare rejected with `422` rather than answered with an invented mechanism.\n\n`/discover` needs only data, and `/explain` needs only a graph.",
    "title": "Causal Model",
    "version": "1.0.0"
  },
  "openapi": "3.1.0",
  "paths": {
    "/batch/effect": {
      "post": {
        "operationId": "batch_effect_batch_effect_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/BatchEffectRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/BatchEffectResponse"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Many effect queries against one system",
        "tags": [
          "inference"
        ]
      }
    },
    "/batch/intervene": {
      "post": {
        "operationId": "batch_intervene_batch_intervene_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/BatchInterventionRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/BatchInterventionResponse"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Several do-queries against one system",
        "tags": [
          "inference"
        ]
      }
    },
    "/counterfactual": {
      "post": {
        "operationId": "counterfactual_counterfactual_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/CounterfactualRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/CounterfactualResult"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Unit-level counterfactuals by abduction, action and prediction",
        "tags": [
          "inference"
        ]
      }
    },
    "/discover": {
      "post": {
        "operationId": "discover_discover_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/DiscoverRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/DiscoverResult"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Infer a DAG from observational data alone",
        "tags": [
          "structure"
        ]
      }
    },
    "/effect": {
      "post": {
        "operationId": "effect_effect_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/EffectRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/EffectResult"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Average treatment effect with calibrated uncertainty",
        "tags": [
          "inference"
        ]
      }
    },
    "/explain": {
      "post": {
        "operationId": "explain_explain_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/ExplainRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ExplainResult"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "How an effect would be identified, and through which paths",
        "tags": [
          "structure"
        ]
      }
    },
    "/health": {
      "get": {
        "operationId": "health_health_get",
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HealthResponse"
                }
              }
            },
            "description": "Successful Response"
          }
        },
        "summary": "Service liveness and model metadata",
        "tags": [
          "service"
        ]
      }
    },
    "/intervene": {
      "post": {
        "operationId": "intervene_intervene_post",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/InterventionRequest"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/InterventionResult"
                }
              }
            },
            "description": "Successful Response"
          },
          "422": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            },
            "description": "Malformed or incomplete query."
          }
        },
        "summary": "Sample the interventional distribution P(V | do(...))",
        "tags": [
          "inference"
        ]
      }
    }
  },
  "tags": [
    {
      "description": "Liveness and model metadata.",
      "name": "service"
    },
    {
      "description": "Interventional, counterfactual and effect queries.",
      "name": "inference"
    },
    {
      "description": "Graph discovery and identification analysis.",
      "name": "structure"
    }
  ]
}