fix(transfer): expire stale jobs and deduplicate diagnostics

skills/feedback-issue/SKILL.md

@@ -1,6 +1,6 @@
 ---
 name: feedback-issue
-version: 7
+version: 8
 description: >-
   Use this skill ONLY when the user EXPLICITLY requests filing an
   upstream issue for MoviePilot core, frontend, or an installed plugin,
@@ -92,6 +92,9 @@ Log relevance rules:
   then applies a recent time window, removes Agent/tool dispatch noise,
   and keeps only timestamped log blocks whose first line contains a
   normalized keyword.
+- Consecutive log records with the same template are compacted to the
+  first record, a repetition count, and the last record. Verify the
+  retained boundary records before treating the excerpt as evidence.
 - If no specific keyword survives normalization, the script records the
   doctor report and log-selection metadata but does not include recent
   log lines. This avoids attaching unrelated noise.

skills/feedback-issue/scripts/collect_feedback_diagnostics.py

@@ -33,6 +33,10 @@ _LOG_TIMESTAMP_FORMAT = "%Y-%m-%d %H:%M:%S"
 _LOG_MODULE_RE = re.compile(
     r"^【[^】]+】\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2},\d+\s+-\s+([^\s][^\-]*?)\s+-\s+"
 )
+_LOG_DYNAMIC_VALUE_RE = re.compile(
+    r"(?<![A-Za-z])(?:[0-9a-f]{8,}|\d+(?:\.\d+)?)(?![A-Za-z])",
+    re.IGNORECASE,
+)
 
 _META_NOISE_MODULES = frozenset({
     "collect_feedback_diagnostics.py",
@@ -238,6 +242,43 @@ def is_meta_noise(line: str) -> bool:
     return match.group(1).strip() in _META_NOISE_MODULES
 
 
+def _repetition_fingerprint(line: str) -> str:
+    """生成用于识别连续重复日志模板的指纹。"""
+    if parse_line_timestamp(line) is None:
+        return line
+    normalized = _LOG_TIMESTAMP_RE.sub("<time>", line)
+    normalized = _LOG_DYNAMIC_VALUE_RE.sub("<value>", normalized)
+    return re.sub(r"\s+", " ", normalized).strip().lower()
+
+
+def _compact_repeated_lines(lines: list[str]) -> list[str]:
+    """压缩连续重复日志模板，同时保留首条、末条和重复次数。"""
+    compacted: list[str] = []
+    group: list[str] = []
+    fingerprint: Optional[str] = None
+
+    def flush_group() -> None:
+        if len(group) < 4:
+            compacted.extend(group)
+            return
+        compacted.append(group[0])
+        compacted.append(
+            f"... 同类日志连续重复 {len(group)} 次，已省略 {len(group) - 2} 行 ..."
+        )
+        compacted.append(group[-1])
+
+    for line in lines:
+        current_fingerprint = _repetition_fingerprint(line)
+        if group and current_fingerprint != fingerprint:
+            flush_group()
+            group = []
+        group.append(line)
+        fingerprint = current_fingerprint
+    if group:
+        flush_group()
+    return compacted
+
+
 def filter_lines(
     text: str,
     keywords: list[str],
@@ -285,7 +326,8 @@ def filter_lines(
         elif keep_block:
             matched.append(line)
     if matched:
-        return matched[-max_lines:], sorted(matched_keywords)
+        compacted = _compact_repeated_lines(matched)
+        return compacted[-max_lines:], sorted(matched_keywords)
     return [], []
 
 

skills/feedback-issue/scripts/feedback_issue_common.py

@@ -371,6 +371,14 @@ def build_prefill_url(
     return f"{issue_new_url(repo)}?{encoded}"
 
 
+def _safe_count(value: Any) -> int:
+    """把不可信的诊断计数字段转换为非负整数。"""
+    try:
+        return max(int(value or 0), 0)
+    except (TypeError, ValueError):
+        return 0
+
+
 def format_doctor_summary(doctor: Optional[dict[str, Any]]) -> str:
     """把 doctor JSON 报告压缩成适合 Issue 和预览展示的摘要。"""
     if not isinstance(doctor, dict):
@@ -390,28 +398,75 @@ def format_doctor_summary(doctor: Optional[dict[str, Any]]) -> str:
         runtime = environment.get("runtime")
         if runtime:
             lines.append(f"运行环境：{runtime}")
+    findings = report.get("findings") or []
     summary = report.get("summary") or {}
     if isinstance(summary, dict):
+        advisory_count = summary.get("advisory")
+        if advisory_count is None and isinstance(findings, list):
+            advisory_count = sum(
+                1
+                for item in findings
+                if isinstance(item, dict)
+                and item.get("affects_report_status") is False
+                and not item.get("fixed")
+            )
         lines.append(
             "汇总："
             f"total={summary.get('total', 0)} "
             f"error={summary.get('error', 0)} "
             f"warn={summary.get('warn', 0)} "
+            f"advisory={advisory_count or 0} "
             f"fixed={summary.get('fixed', 0)}"
         )
 
-    findings = report.get("findings") or []
     if isinstance(findings, list):
-        important = [
-            item for item in findings
-            if isinstance(item, dict) and item.get("severity") in {"error", "warn"}
-        ][:8]
+        grouped: dict[tuple[str, str, str, bool], dict[str, Any]] = {}
+        for item in findings:
+            if not isinstance(item, dict) or item.get("severity") not in {"error", "warn"}:
+                continue
+            title = str(item.get("title") or item.get("id") or "未知诊断项")
+            recommendation = str(item.get("recommendation") or "").strip()
+            advisory = item.get("affects_report_status") is False
+            key = (str(item.get("severity")), title, recommendation, advisory)
+            group = grouped.setdefault(
+                key,
+                {
+                    "count": 0,
+                    "matches": 0,
+                    "unique_matches": 0,
+                    "sources": [],
+                },
+            )
+            group["count"] += 1
+            context = item.get("context") or {}
+            if not isinstance(context, dict):
+                continue
+            group["matches"] += _safe_count(context.get("matches"))
+            group["unique_matches"] += _safe_count(
+                context.get("unique_matches") or context.get("matches") or 0
+            )
+            source_files = context.get("log_files") or [context.get("log_file")]
+            for source_file in source_files:
+                if not source_file:
+                    continue
+                source_name = Path(str(source_file)).name
+                if source_name not in group["sources"]:
+                    group["sources"].append(source_name)
+
+        important = list(grouped.items())[:8]
         if important:
             lines.append("关键发现：")
-            for item in important:
-                title = str(item.get("title") or item.get("id") or "未知诊断项")
-                recommendation = str(item.get("recommendation") or "").strip()
-                line = f"- [{item.get('severity')}] {title}"
+            for (severity, title, recommendation, advisory), group in important:
+                marker = f"{severity}/advisory" if advisory else severity
+                line = f"- [{marker}] {title}"
+                if group["count"] > 1:
+                    line = f"{line}（合并 {group['count']} 项）"
+                if group["sources"]:
+                    line = f"{line}；来源：{', '.join(group['sources'])}"
+                if group["matches"]:
+                    line = f"{line}；命中：{group['matches']} 条"
+                    if group["unique_matches"] < group["matches"]:
+                        line = f"{line}，去重后 {group['unique_matches']} 条"
                 if recommendation:
                     line = f"{line}；建议：{recommendation}"
                 lines.append(line)