Server definition

Hash: sha256:cc0f16e250c22b728aa79d8d935bbe9d4106aa8654f6e243a2bcba39aca64f7e
What it is: What a remote MCP server returned when asked what it offers: 14 tools

The blob, as servednamed by its sha256

{
  "instructions": null,
  "tools": [
    {
      "description": "Postmarket presence rates across the snapshotted AI/ML device cohort (optionally by panel): share with any recall in 24 months, with a rising MAUDE trend, with any drift signal, with a warning-letter match — every rate with its denominator inline, never pooled across devices.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "panel": {
            "description": "Advisory panel, e.g. Radiology; omit for all",
            "maxLength": 80,
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "cohort_postmarket_stats",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Look up the structured premarket evidence FDA accepted for a specific AI/ML-enabled device by 510(k) number (e.g. K252148). Returns parsed summary fields — validation study design, sample sizes, endpoints, reported performance, predicate chain, PCCP — each with a verbatim source quote and page. Null means the summary did not state it.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "k_number": {
            "description": "510(k) or De Novo number, e.g. K252148 or DEN180001",
            "pattern": "^(K|DEN)\\d{6}$",
            "type": "string"
          }
        },
        "required": [
          "k_number"
        ],
        "type": "object"
      },
      "name": "device_evidence_lookup",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Post-clearance intelligence for one AI/ML device by 510(k) number: its product code's recalls, MAUDE adverse-event level and trend, warning-letter and 483 matches for the applicant, plus per-device drift signals (adverse-event inflection, re-clearances of the same device line, software-recall patterns, predicate-cohort recall activity). Descriptive observables with sources — never a safety judgment.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "k_number": {
            "description": "510(k) or De Novo number, e.g. K252148 or DEN180001",
            "pattern": "^(K|DEN)\\d{6}$",
            "type": "string"
          }
        },
        "required": [
          "k_number"
        ],
        "type": "object"
      },
      "name": "device_postmarket_lookup",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Review a medical-device category's public FDA signals by three-letter product code (e.g. FRN = infusion pump). Returns recalls, MAUDE adverse-event trend, warning-letter matches, a normalized category signal, its driver contributions, and interpretation limits. It does not predict enforcement against a firm.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "product_code": {
            "description": "FDA product code, e.g. FRN",
            "pattern": "^[A-Za-z0-9]{3}$",
            "type": "string"
          }
        },
        "required": [
          "product_code"
        ],
        "type": "object"
      },
      "name": "device_risk_lookup",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Reporting-rate stats across the parsed AI/ML corpus (optionally by panel). Each rate is a presence figure with its denominator — 'reported in X of Y audited devices' — never a pooled performance value. Excludes not-yet-parsed devices from every denominator and discloses the parse queue separately. Predicate age (median years between a clearance and its cited predicates) is included when decision-date coverage clears a 60% floor, and withheld otherwise.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "panel": {
            "description": "Advisory panel, e.g. Radiology; omit for all",
            "maxLength": 80,
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "evidence_cohort_stats",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Find AI/ML device clearances by filter — product code, panel, applicant, and whether the submission reported clinical data, any sensitivity metric, or a PCCP. Answers 'what evidence did FDA accept for devices like mine'. Returns bounded discovery summaries; call device_evidence_lookup with a result's K-number for the full source-quoted FDA record. Presence flags are descriptive: 'reports a sensitivity metric' is not 'reports a comparable sensitivity' — analysis units differ across devices.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "applicant": {
            "description": "Substring match on applicant/company name",
            "maxLength": 120,
            "type": "string"
          },
          "cursor": {
            "description": "Opaque continuation cursor returned by a prior page.",
            "maxLength": 512,
            "type": "string"
          },
          "has_clinical_data": {
            "type": "boolean"
          },
          "has_pccp": {
            "description": "Included a Predetermined Change Control Plan",
            "type": "boolean"
          },
          "limit": {
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "panel": {
            "description": "Advisory panel, e.g. Radiology",
            "maxLength": 80,
            "type": "string"
          },
          "product_code": {
            "description": "FDA product code, e.g. QAS",
            "pattern": "^[A-Za-z0-9]{3}$",
            "type": "string"
          },
          "reports_any_sensitivity_metric": {
            "description": "Reported any sensitivity metric (canonical — includes per-finding sensitivities, not just the top-level slot). Not a claim of cross-device comparability.",
            "type": "boolean"
          }
        },
        "type": "object"
      },
      "name": "evidence_search",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {
                "additionalProperties": false,
                "properties": {
                  "count": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "next_cursor": {
                    "type": "string"
                  },
                  "results": {
                    "items": {},
                    "type": "array"
                  },
                  "scanned": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "truncated": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "count",
                  "results"
                ],
                "type": "object"
              },
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Build a recent, source-bounded FDA public-record timeline for a device firm: matched recalls, warning letters, and Form 483 citations where exact FEI numbers are available. Product codes are discovered from Constat's AI/ML-device corpus or may be supplied explicitly. Returns attribution and coverage limits with the records; it is not a finding of noncompliance or a prediction of FDA action.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "fei_numbers": {
            "description": "Optional exact FDA FEI numbers; improves Form 483 attribution.",
            "items": {
              "pattern": "^\\d{6,12}$",
              "type": "string"
            },
            "maxItems": 20,
            "type": "array"
          },
          "firm_name": {
            "description": "FDA applicant or company name, e.g. 'Medtronic'",
            "maxLength": 160,
            "minLength": 2,
            "type": "string"
          },
          "limit": {
            "description": "Maximum records per source and events in the timeline (default 20).",
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "product_codes": {
            "description": "Optional FDA product-code scope. When omitted, Constat discovers codes from applicant matches in its device corpus.",
            "items": {
              "pattern": "^[A-Za-z0-9]{3}$",
              "type": "string"
            },
            "maxItems": 8,
            "type": "array"
          },
          "since": {
            "description": "Earliest event date, YYYY-MM-DD. Defaults to five years ago.",
            "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
            "type": "string"
          }
        },
        "required": [
          "firm_name"
        ],
        "type": "object"
      },
      "name": "firm_compliance_history",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Find AI/ML devices by postmarket criteria — product code, panel, applicant, whether any drift signal exists, minimum recalls in 24 months, or a rising MAUDE trend. Returns per-device postmarket summaries with drift-signal counts.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "applicant": {
            "description": "Substring match on applicant/company name",
            "maxLength": 120,
            "type": "string"
          },
          "cursor": {
            "description": "Opaque continuation cursor returned by a prior page.",
            "maxLength": 512,
            "type": "string"
          },
          "has_drift_signal": {
            "type": "boolean"
          },
          "limit": {
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "maude_trend_up": {
            "description": "Code-level MAUDE trend above its own 3-year baseline",
            "type": "boolean"
          },
          "min_recalls_24mo": {
            "description": "Product-code recalls in trailing 24 months",
            "maximum": 9007199254740991,
            "minimum": 0,
            "type": "integer"
          },
          "panel": {
            "description": "Advisory panel, e.g. Radiology",
            "maxLength": 80,
            "type": "string"
          },
          "product_code": {
            "description": "FDA product code, e.g. QIH",
            "pattern": "^[A-Za-z0-9]{3}$",
            "type": "string"
          },
          "signal_specificity": {
            "description": "Restrict the drift-signal filter to one tier: 'device' = attributable to this device (own line re-cleared, own applicant's recall, predicate neighbors) — the high-signal tier; 'product_code' = observed in its category",
            "enum": [
              "device",
              "product_code"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "postmarket_search",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {
                "additionalProperties": false,
                "properties": {
                  "count": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "next_cursor": {
                    "type": "string"
                  },
                  "results": {
                    "items": {},
                    "type": "array"
                  },
                  "scanned": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "truncated": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "count",
                  "results"
                ],
                "type": "object"
              },
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Trace the predicate ancestry of a 510(k) device, with each cited predicate's age (how many years old the predicate was when the child cleared). Reveals how AI/ML devices chain to older predicates.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "depth": {
            "description": "Max ancestry depth (default 4)",
            "maximum": 6,
            "minimum": 1,
            "type": "integer"
          },
          "k_number": {
            "description": "510(k) or De Novo number, e.g. K252148 or DEN180001",
            "pattern": "^(K|DEN)\\d{6}$",
            "type": "string"
          }
        },
        "required": [
          "k_number"
        ],
        "type": "object"
      },
      "name": "predicate_chain",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {
                "additionalProperties": false,
                "properties": {
                  "chain": {
                    "items": {},
                    "type": "array"
                  },
                  "root": {
                    "type": "string"
                  },
                  "truncated": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "root",
                  "chain",
                  "truncated"
                ],
                "type": "object"
              },
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Trace the clearance-to-payment pathway for an AI/ML device by FDA clearance number (K/DEN, e.g. DEN170073) OR bare CPT code (e.g. 75580). Returns every payment mechanism (NTAP add-on, Category I/III CPT + CMS rate, HCPCS, MAC LCD) with amounts, effective dates, and source links, plus any commercial/MAC payer coverage policies that reference the clearance or its codes. Answers 'who got paid, how much, through which mechanism, on what basis.' CPT codes are bare factual identifiers only — no procedure descriptors; follow the CMS source link for the official descriptor.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "cpt_code": {
            "description": "Bare CPT code, e.g. 75580 or 0932T",
            "pattern": "^\\d{4,5}[A-Z]?$",
            "type": "string"
          },
          "k_number": {
            "description": "FDA clearance number, e.g. DEN170073 or K252148",
            "pattern": "^(K|DEN)\\d{6}$",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "reimbursement_lookup",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Find AI/ML device payment pathways by mechanism — e.g. 'devices that got NTAP', 'devices paid under a Category I CPT code', 'pathways with a known CMS dollar rate'. Filters: mechanism, CPT category, NTAP status, applicant. Returns pathways with amounts, effective dates, and sources. Use reimbursement_stats for the mechanism distribution (never a single pooled reimbursement rate).",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "applicant": {
            "description": "Substring match on device maker / applicant name",
            "maxLength": 120,
            "type": "string"
          },
          "cpt_category": {
            "description": "CPT category",
            "enum": [
              "I",
              "III",
              "unknown"
            ],
            "type": "string"
          },
          "cursor": {
            "description": "Opaque continuation cursor returned by a prior page.",
            "maxLength": 512,
            "type": "string"
          },
          "has_cms_rate": {
            "description": "Only pathways with a known CMS dollar rate",
            "type": "boolean"
          },
          "limit": {
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          },
          "mechanism": {
            "description": "Payment mechanism",
            "enum": [
              "ntap",
              "cat_iii_apc",
              "cat_i",
              "hcpcs",
              "lcd",
              "none"
            ],
            "type": "string"
          },
          "ntap_status": {
            "enum": [
              "active",
              "expired",
              "granted",
              "none"
            ],
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "reimbursement_search",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {
                "additionalProperties": false,
                "properties": {
                  "count": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "next_cursor": {
                    "type": "string"
                  },
                  "results": {
                    "items": {},
                    "type": "array"
                  },
                  "scanned": {
                    "maximum": 9007199254740991,
                    "minimum": 0,
                    "type": "integer"
                  },
                  "truncated": {
                    "type": "boolean"
                  }
                },
                "required": [
                  "count",
                  "results"
                ],
                "type": "object"
              },
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Distribution of payment mechanisms across the AI/ML reimbursement corpus — pathway and distinct-device counts per mechanism (NTAP, Cat I, Cat III/APC, …) with the min/median/max dollar amounts for each. Deliberately never a single pooled 'reimbursement rate': NTAP add-on amounts and CMS rates are different measurements and are reported separately with their own spreads.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {},
        "type": "object"
      },
      "name": "reimbursement_stats",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Look up NHTSA safety history for a vehicle by make, model, and model year. Returns recall campaigns and complaint statistics (crashes, fires, injuries, top components).",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "make": {
            "description": "e.g. honda",
            "maxLength": 64,
            "minLength": 2,
            "type": "string"
          },
          "model": {
            "description": "e.g. civic",
            "maxLength": 64,
            "minLength": 1,
            "type": "string"
          },
          "year": {
            "description": "model year, e.g. 2020",
            "pattern": "^\\d{4}$",
            "type": "string"
          }
        },
        "required": [
          "make",
          "model",
          "year"
        ],
        "type": "object"
      },
      "name": "vehicle_risk_lookup",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    },
    {
      "description": "Return machine-generated FDA public-record changes detected for monitored product codes since a caller-supplied date, plus each code's latest category snapshot and postmarket coverage. Defaults to Constat Radar's five-code watchlist and the last seven days. Analyst verdict text and internal review status are excluded; use next_since as the next polling cursor.",
      "inputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "properties": {
          "limit": {
            "description": "Maximum changes to return (default 10).",
            "maximum": 100,
            "minimum": 1,
            "type": "integer"
          },
          "product_codes": {
            "description": "FDA product codes to poll. Omit for the default Radar watchlist.",
            "items": {
              "pattern": "^[A-Za-z0-9]{3}$",
              "type": "string"
            },
            "maxItems": 20,
            "type": "array"
          },
          "since": {
            "description": "Return changes on or after this ISO date or UTC timestamp. Defaults to the last seven days; pass the prior response's next_since for exact polling.",
            "pattern": "^\\d{4}-\\d{2}-\\d{2}(?:T\\d{2}:\\d{2}:\\d{2}(?:\\.\\d{1,3})?Z)?$",
            "type": "string"
          }
        },
        "type": "object"
      },
      "name": "watchlist_diff",
      "outputSchema": {
        "$schema": "http://json-schema.org/draft-07/schema#",
        "additionalProperties": false,
        "properties": {
          "data": {
            "anyOf": [
              {},
              {
                "type": "null"
              }
            ]
          },
          "message": {
            "type": "string"
          },
          "status": {
            "enum": [
              "ok",
              "not_found",
              "invalid_request",
              "unavailable"
            ],
            "type": "string"
          },
          "untrusted_data_notice": {
            "type": "string"
          }
        },
        "required": [
          "status",
          "data",
          "untrusted_data_notice"
        ],
        "type": "object"
      }
    }
  ]
}

Verify it yourself

curl -s https://api.teppi.xyz/v1/evidence/sha256:cc0f16e250c22b728aa79d8d935bbe9d4106aa8654f6e243a2bcba39aca64f7e | sha256sum