octopus-workflow/core/schemas/reviewer-output.schema.json

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://eightarms.net/octopus-workflow/schemas/reviewer-output.schema.json",
  "title": "Reviewer Output",
  "description": "Schema for a single reviewer's output for one review dimension. Also the Tier 1 review-findings schema ([org-internal #1988]): migrated skills (review-code) write each dimension's finding as a JSON file at runs/{slug}/reviews/{stage}/round{N}/findings-{DIMENSION_CODE}.json validated by this schema; the index.json row for that file carries type=review-findings, schema=this $id. When a dimension has multiple reviewers (dim_split > 1, e.g. D3 TOPO:2 / D4 TOPO:2), each writes its OWN slot file findings-{DIMENSION_CODE}-r{k}.json with reviewer_slot/reviewer_count set. See templates/runs-layout.md and rules/two-tier-artifacts.md.",
  "type": "object",
  "required": ["dimension", "dimension_label", "verdict", "quantitative_summary", "findings", "reviewed_files"],
  "properties": {
    "dimension": {
      "type": "string",
      "description": "Dimension code (e.g. COR, SEC, PERF, TRC)"
    },
    "dimension_label": {
      "type": "string",
      "description": "Human-readable label"
    },
    "reviewer_slot": {
      "type": "integer",
      "minimum": 1,
      "description": "1-based slot of this reviewer WITHIN its dimension, when dim_split assigns >1 reviewer to the dimension (e.g. review-dag D3 TOPO:2, D4 TOPO:2 鈥?dim_split per `workflow-routing.yaml` dag.size_derivation.review_depth). Multi-reviewer dimensions write one file per slot: findings-{DIMENSION_CODE}-r{k}.json. Omitted for single-reviewer dimensions (file stays findings-{DIMENSION_CODE}.json). Preserves per-reviewer attribution for the retrospective overlap analysis ([org-internal #2996] step 1a)."
    },
    "reviewer_count": {
      "type": "integer",
      "minimum": 2,
      "description": "Total reviewers assigned to this dimension in this round (set together with reviewer_slot)."
    },
    "verdict": {
      "type": "string",
      "enum": ["PASS", "WARN", "FAIL", "UNRESOLVED"],
      "description": "PASS: pass_rate = 1.0 (no failed checks). WARN: pass_rate >= 0.7 and no BLOCKER findings. FAIL: any BLOCKER finding OR pass_rate < 0.7."
    },
    "quantitative_summary": {
      "type": "object",
      "required": ["total_checks", "passed", "failed", "pass_rate"],
      "properties": {
        "total_checks": { "type": "integer", "minimum": 1 },
        "passed": { "type": "integer", "minimum": 0 },
        "failed": { "type": "integer", "minimum": 0 },
        "pass_rate": { "type": "number", "minimum": 0, "maximum": 1 },
        "na_count": { "type": "integer", "minimum": 0, "description": "Count of not-applicable items" },
        "blocker_count": {
          "type": "integer",
          "minimum": 0,
          "description": "Count of BLOCKER findings (consumed by synthesis_task.md aggregation)"
        },
        "major_count": {
          "type": "integer",
          "minimum": 0,
          "description": "Count of MAJOR findings (consumed by synthesis_task.md aggregation)"
        },
        "minor_count": {
          "type": "integer",
          "minimum": 0,
          "description": "Count of MINOR findings (consumed by synthesis_task.md aggregation)"
        },
        "info_count": {
          "type": "integer",
          "minimum": 0,
          "description": "Count of INFO findings (consumed by synthesis_task.md aggregation)"
        }
      }
    },
    "findings": {
      "type": "array",
      "uniqueItems": true,
      "items": {
        "type": "object",
        "required": ["id", "severity", "checklist_ref", "location", "summary", "detail", "evidence", "suggestion"],
        "properties": {
          "id": {
            "type": "string",
            "pattern": "^[A-Z0-9]+-F\\d{3,}$",
            "description": "Unique finding ID within the dimension file, form {OWN_DIMENSION_CODE}-F{NNN}, e.g. COR-F001. In a grouped dispatch the id uses the finding's OWN dimension code (e.g. TST-F001 inside the COR+TST+DBT group), never the joined group code. NOTE: uniqueness of the id VALUE is NOT enforced by findings[] uniqueItems (JSON Schema uniqueItems compares whole objects by deep equality); the synthesizer MUST post-check that id values are unique across all findings-{DIM}*.json files of the round (wired as step 1b of _shared/synthesis_task.md). Multi-slot dimensions (reviewer_slot set): prefix the slot in the id, e.g. TOPOR1-F001 / TOPOR2-F001, so ids stay unique across a dimension's slot files while still matching this pattern."
          },
          "severity": {
            "type": "string",
            "enum": ["BLOCKER", "MAJOR", "MINOR", "INFO"]
          },
          "checklist_ref": {
            "type": "string",
            "pattern": "^[A-Z0-9]{2,6} \\d+(\\.\\d+)+(\\s*\\([^\\)]*\\))?(\\s*/\\s*[A-Z0-9]{2,6} \\d+(\\.\\d+)+(\\s*\\([^\\)]*\\))?)*$",
            "description": "Checklist item reference, e.g. COR 1.1, INV 1.3, SEC 3.7.1, STD 8.4 鈥?dimension/section code followed by item number(s)."
          },
          "location": {
            "type": "string",
            "description": "File:line or file:section where the issue occurs"
          },
          "summary": {
            "type": "string",
            "description": "One-line description"
          },
          "detail": {
            "type": "string",
            "description": "Full explanation of the finding"
          },
          "evidence": {
            "type": "string",
            "description": "Quote or excerpt from the document that supports this finding"
          },
          "suggestion": {
            "type": "string",
            "description": "Actionable recommendation to resolve the finding"
          }
        }
      }
    },
    "reviewed_files": {
      "type": "array",
      "items": { "type": "string" },
      "description": "List of files actually reviewed"
    }
  }
}