nvidia-production-f205.up.railway.app

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "Short name of the process"
    },
    "steps": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": {
            "type": "string",
            "description": "Short unique id, e.g. \"s1\""
          },
          "label": {
            "type": "string",
            "description": "Human-readable step name"
          },
          "type": {
            "type": "string",
            "enum": [
              "task",
              "decision",
              "approval"
            ]
          },
          "approvalPurpose": {
            "type": "string",
            "enum": [
              "work",
              "plan"
            ],
            "description": "For approval steps, ask whether the person approves completed work (work) or only a remediation/redesign plan (plan). Plan approval never certifies that failed work checks passed."
          },
          "detail": {
            "type": "string",
            "description": "Optional one-line explanation"
          },
          "role": {
            "type": "string",
            "description": "Owner role from describe_workspace"
          },
          "humanOnly": {
            "type": "boolean"
          },
          "fields": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "Input keys this task collects. Every declared input must be assigned to a task; ask the human who records it and when."
          },
          "action": {
            "type": "string",
            "description": "Optional: name of a host action (from describe_workspace) that performs this step when replaying"
          },
          "next": {
            "type": "array",
            "description": "Outgoing edges. Omit on the last step. Multiple edges = a branch; give each a condition.",
            "items": {
              "type": "object",
              "properties": {
                "to": {
                  "type": "string",
                  "description": "id of the next step"
                },
                "condition": {
                  "type": "string",
                  "description": "When this edge is taken, e.g. \"urgent == true\""
                },
                "criteria": {
                  "type": "object",
                  "description": "Machine-checkable routing rules from the human: numbers use e.g. {\"testPassRate\":{\"gte\":100}}; dropdowns use exact choices e.g. {\"shippingMethod\":{\"eq\":\"Courier\"}} and {\"shippingMethod\":{\"eq\":\"Pickup\"}} on the respective edges. Always set criteria when the human states thresholds or choice-based routes. resolve_decision checks submitted task values and refuses a contradictory route. A prose condition alone does not enforce the dropdown choice."
                }
              },
              "required": [
                "to"
              ]
            }
          }
        },
        "required": [
          "id",
          "label",
          "type"
        ]
      }
    },
    "applies_when": {
      "type": "object",
      "description": "REQUIRED when creating from a live entry: the structured conditions under which this playbook applies, copied from the entry — find_relevant_processes' entering_now shows which keys this app matches on. Add finer keys when the human names them (e.g. team, artifact, system), and ALWAYS a \"keywords\" array of 3-6 distinctive words from the work itself (e.g. keywords [\"hotfix\", \"latency\", \"rollback\"] or [\"handoff\", \"contrast\", \"accessibility\"]) — a generic kind alone (routine log) scores only ~30% and will not surface as a suggestion; keywords matched in the live text are what raise it. Without applies_when the playbook can never be auto-suggested to the next worker."
    },
    "priority_when": {
      "type": "object",
      "description": "Conditions that raise the match priority, e.g. {\"urgent\": true}"
    },
    "source_worklog_id": {
      "type": "string",
      "description": "Id of the work entry that triggered creating this playbook"
    },
    "fields": {
      "type": "array",
      "description": "The playbook's data contract: variables that must be captured when following it (from the required_context interview answer). Rendered as a form for the next worker.",
      "items": {
        "type": "object",
        "properties": {
          "key": {
            "type": "string",
            "description": "Unique camelCase input key"
          },
          "label": {
            "type": "string",
            "description": "Label shown to the worker"
          },
          "type": {
            "type": "string",
            "enum": [
              "number",
              "string",
              "boolean",
              "select"
            ]
          },
          "options": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "Required for select: the human-approved dropdown choices. No default is selected."
          },
          "unit": {
            "type": "string"
          },
          "required": {
            "type": "boolean"
          },
          "confirm": {
            "type": "boolean",
            "description": "Boolean acknowledgment that must be checked true, not a pass/fail measurement."
          }
        },
        "required": [
          "key",
          "type"
        ]
      }
    }
  },
  "required": [
    "title",
    "steps"
  ]
}