feat(ECR-012–016): 合规、题库、时辰刷新、头像、MBTI OEJTS 与埋点

落地输入合规、探索题库、报告日/时辰刷新、账号头像、OEJTS 量表，并补齐 H5 埋点与 Admin 漏斗；同步 ESS 工件、切至自建 Git、清理 GitHub Actions。 Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-13 01:27:58 +08:00
parent 13860bf1ef
commit 89756f65b4
227 changed files with 7405 additions and 1407 deletions
@@ -0,0 +1,122 @@
+package scale
+
+import (
+	"encoding/json"
+	"strconv"
+)
+
+// JungianQuestionMeta is parsed from scale_questions.body for OEJTS-style items.
+type JungianQuestionMeta struct {
+	Dimension string `json:"dimension"`
+	Format    string `json:"format"`
+	Left      string `json:"left"`
+	Right     string `json:"right"`
+	Prompt    string `json:"prompt"`
+}
+
+// ScoreJungian tallies 1–5 Likert answers per EI/SN/TF/JP (OEJTS rules).
+// Left poles: E, S, F, J · Right poles: I, N, T, P · threshold = perDim*3.
+func ScoreJungian(answers map[string]string, qMeta map[string]JungianQuestionMeta, perDim int) (typeCode string, raw map[string]int, pct map[string]int) {
+	raw = map[string]int{"EI": 0, "SN": 0, "TF": 0, "JP": 0}
+	if perDim <= 0 {
+		perDim = 8
+	}
+	for qid, ans := range answers {
+		meta, ok := qMeta[qid]
+		if !ok || meta.Dimension == "" {
+			continue
+		}
+		v, err := strconv.Atoi(ans)
+		if err != nil || v < 1 || v > 5 {
+			v = 3
+		}
+		raw[meta.Dimension] += v
+	}
+	thr := perDim * 3
+	pick := func(score int, left, right string) string {
+		if score > thr {
+			return right
+		}
+		return left
+	}
+	typeCode = pick(raw["EI"], "E", "I") +
+		pick(raw["SN"], "S", "N") +
+		pick(raw["TF"], "F", "T") +
+		pick(raw["JP"], "J", "P")
+
+	pct = map[string]int{}
+	minS, maxS := perDim, perDim*5
+	span := float64(maxS - minS)
+	rightPct := func(score int) int {
+		p := int(float64(score-minS)/span*100 + 0.5)
+		if p < 0 {
+			return 0
+		}
+		if p > 100 {
+			return 100
+		}
+		return p
+	}
+	eiR := rightPct(raw["EI"])
+	snR := rightPct(raw["SN"])
+	tfR := rightPct(raw["TF"])
+	jpR := rightPct(raw["JP"])
+	pct["E"], pct["I"] = 100-eiR, eiR
+	pct["S"], pct["N"] = 100-snR, snR
+	pct["F"], pct["T"] = 100-tfR, tfR
+	pct["J"], pct["P"] = 100-jpR, jpR
+	return typeCode, raw, pct
+}
+
+// ParseJungianMeta extracts dimension metadata from question body JSON.
+func ParseJungianMeta(body json.RawMessage) JungianQuestionMeta {
+	var m JungianQuestionMeta
+	_ = json.Unmarshal(body, &m)
+	return m
+}
+
+// BuildJungianResult builds rich result with 4-letter code + preference bars.
+func BuildJungianResult(typeCode string, pct map[string]int) map[string]interface{} {
+	label := MBTILabel(typeCode)
+	base := mbtiPack(typeCode, label)
+	base.Label = typeCode + " · " + label
+	base.ShareLine = "我的类型探索：" + typeCode + " · " + label
+	base.Dimensions = []map[string]interface{}{
+		{"title": "E/I 能量", "score": maxPct(pct, "E", "I"), "note": prefNote("E", "I", pct, "外向互动", "内向思考")},
+		{"title": "S/N 信息", "score": maxPct(pct, "S", "N"), "note": prefNote("S", "N", pct, "具体事实", "模式可能")},
+		{"title": "T/F 决策", "score": maxPct(pct, "T", "F"), "note": prefNote("T", "F", pct, "逻辑一致", "价值与人际")},
+		{"title": "J/P 节奏", "score": maxPct(pct, "J", "P"), "note": prefNote("J", "P", pct, "计划结构", "灵活开放")},
+	}
+	out := map[string]interface{}{
+		"title":       "MBTI 探索结果",
+		"style_key":   typeCode,
+		"type_code":   typeCode,
+		"label":       base.Label,
+		"summary":     base.Summary,
+		"overview":    base.Overview,
+		"share_line":  base.ShareLine,
+		"dimensions":  base.Dimensions,
+		"preferences": pct,
+		"strengths":   base.Strengths,
+		"watchouts":   base.Watchouts,
+		"tips":        base.Tips,
+		"scripts":     base.Scripts,
+		"growth_plan": base.GrowthPlan,
+		"faq":         base.FAQ,
+	}
+	return out
+}
+
+func maxPct(pct map[string]int, a, b string) int {
+	if pct[a] >= pct[b] {
+		return pct[a]
+	}
+	return pct[b]
+}
+
+func prefNote(a, b string, pct map[string]int, aDesc, bDesc string) string {
+	if pct[a] >= pct[b] {
+		return a + " " + strconv.Itoa(pct[a]) + "% · " + aDesc
+	}
+	return b + " " + strconv.Itoa(pct[b]) + "% · " + bDesc
+}