Add DMN-style decision tables

README.md

@@ -13,6 +13,7 @@
 
 ## Table of Contents
 
+- [What's new (2026-06-20) — DMN-Style Decision Tables](#whats-new-2026-06-20--dmn-style-decision-tables)
 - [What's new (2026-06-20) — Saga / Compensating Rollback](#whats-new-2026-06-20--saga--compensating-rollback)
 - [What's new (2026-06-20) — JSONPath Querying](#whats-new-2026-06-20--jsonpath-querying)
 - [What's new (2026-06-20) — Multi-Channel Webhook Notifications](#whats-new-2026-06-20--multi-channel-webhook-notifications)
@@ -105,6 +106,12 @@
 
 ---
 
+## What's new (2026-06-20) — DMN-Style Decision Tables
+
+Externalize branching into reviewable rule tables. Full reference: [`docs/source/Eng/doc/new_features/v53_features_doc.rst`](docs/source/Eng/doc/new_features/v53_features_doc.rst).
+
+- **`evaluate_table` / `DecisionTable`** (`AC_decision_table`, `ac_decision_table`): replaces nested `AC_if_var` chains with rows of `conditions -> outputs` and a hit policy (`UNIQUE`/`FIRST`/`PRIORITY`/`COLLECT`). Cell conditions are wildcard / literal / `{op, value}` using the executor's standard comparators (reused, not duplicated). Pure-stdlib, fully testable; the DMN way to keep business rules data-driven.
+
 ## What's new (2026-06-20) — Saga / Compensating Rollback
 
 Undo completed steps when a later one fails. Full reference: [`docs/source/Eng/doc/new_features/v52_features_doc.rst`](docs/source/Eng/doc/new_features/v52_features_doc.rst).

README/README_zh-CN.md

@@ -12,6 +12,7 @@
 
 ## 目录
 
+- [本次更新 (2026-06-20) — DMN 式决策表](#本次更新-2026-06-20--dmn-式决策表)
 - [本次更新 (2026-06-20) — Saga / 补偿回滚](#本次更新-2026-06-20--saga--补偿回滚)
 - [本次更新 (2026-06-20) — JSONPath 查询](#本次更新-2026-06-20--jsonpath-查询)
 - [本次更新 (2026-06-20) — 多通道 Webhook 通知](#本次更新-2026-06-20--多通道-webhook-通知)
@@ -104,6 +105,12 @@
 
 ---
 
+## 本次更新 (2026-06-20) — DMN 式决策表
+
+将分支外部化为可审查的规则表。完整参考:[`docs/source/Zh/doc/new_features/v53_features_doc.rst`](../docs/source/Zh/doc/new_features/v53_features_doc.rst)。
+
+- **`evaluate_table` / `DecisionTable`**(`AC_decision_table`、`ac_decision_table`):以一列列的 `conditions -> outputs` 加命中政策(`UNIQUE`/`FIRST`/`PRIORITY`/`COLLECT`)取代嵌套 `AC_if_var` 链。单元格条件为通配符 / 字面值 / `{op, value}`,使用执行器标准比较子(重用,不重复)。纯标准库、可完整测试;DMN 让业务规则数据驱动的方式。
+
 ## 本次更新 (2026-06-20) — Saga / 补偿回滚
 
 后续步骤失败时回滚已完成步骤。完整参考:[`docs/source/Zh/doc/new_features/v52_features_doc.rst`](../docs/source/Zh/doc/new_features/v52_features_doc.rst)。

README/README_zh-TW.md

@@ -12,6 +12,7 @@
 
 ## 目錄
 
+- [本次更新 (2026-06-20) — DMN 式決策表](#本次更新-2026-06-20--dmn-式決策表)
 - [本次更新 (2026-06-20) — Saga / 補償回溯](#本次更新-2026-06-20--saga--補償回溯)
 - [本次更新 (2026-06-20) — JSONPath 查詢](#本次更新-2026-06-20--jsonpath-查詢)
 - [本次更新 (2026-06-20) — 多通道 Webhook 通知](#本次更新-2026-06-20--多通道-webhook-通知)
@@ -104,6 +105,12 @@
 
 ---
 
+## 本次更新 (2026-06-20) — DMN 式決策表
+
+將分支外部化為可審查的規則表。完整參考:[`docs/source/Zh/doc/new_features/v53_features_doc.rst`](../docs/source/Zh/doc/new_features/v53_features_doc.rst)。
+
+- **`evaluate_table` / `DecisionTable`**(`AC_decision_table`、`ac_decision_table`):以一列列的 `conditions -> outputs` 加命中政策(`UNIQUE`/`FIRST`/`PRIORITY`/`COLLECT`)取代巢狀 `AC_if_var` 鏈。儲存格條件為萬用字元 / 字面值 / `{op, value}`,使用執行器標準比較子(重用,不重複)。純標準函式庫、可完整測試;DMN 讓商業規則資料驅動的方式。
+
 ## 本次更新 (2026-06-20) — Saga / 補償回溯
 
 後續步驟失敗時復原已完成步驟。完整參考:[`docs/source/Zh/doc/new_features/v52_features_doc.rst`](../docs/source/Zh/doc/new_features/v52_features_doc.rst)。

docs/source/Eng/doc/new_features/v53_features_doc.rst

@@ -0,0 +1,55 @@
+DMN-Style Decision Tables
+=========================
+
+Nested ``AC_if_var`` chains get unreadable fast. A decision table externalizes
+branching into rows of ``conditions -> outputs`` evaluated by a **hit policy** —
+the DMN way to keep business rules data-driven and reviewable.
+
+Each cell condition is a wildcard (``None`` / ``"-"`` / ``"*"``), a literal
+(equality), or ``{"op": "ge", "value": 18}`` using the project's standard
+comparators (``eq/ne/lt/le/gt/ge/contains/startswith/endswith`` — reused from the
+executor, not duplicated). Pure standard library; imports no ``PySide6``.
+
+Hit policies
+------------
+
+================ ===================================================
+Policy           Behavior
+================ ===================================================
+``UNIQUE``       Exactly one rule may match (raises if more do).
+``FIRST``        The first matching rule wins.
+``PRIORITY``     Same as FIRST — first match in rule order.
+``COLLECT``      All matching rules' outputs (a list).
+================ ===================================================
+
+Headless API
+------------
+
+.. code-block:: python
+
+    from je_auto_control import evaluate_table
+
+    spec = {
+        "inputs": ["age", "country"],
+        "hit_policy": "FIRST",
+        "rules": [
+            {"conditions": {"age": {"op": "lt", "value": 18}},
+             "outputs": {"tier": "minor"}},
+            {"conditions": {"age": {"op": "ge", "value": 18}, "country": "US"},
+             "outputs": {"tier": "us-adult"}},
+            {"conditions": {"age": {"op": "ge", "value": 18}},
+             "outputs": {"tier": "adult"}},
+        ],
+    }
+    evaluate_table(spec, {"age": 30, "country": "DE"})   # -> {"tier": "adult"}
+
+``evaluate_table`` returns the matched outputs dict (or ``{}`` if none) for
+single-hit policies, and a list for ``COLLECT``. The ``DecisionTable`` class
+(``from_dict`` / ``evaluate``) is available for reuse.
+
+Executor command
+----------------
+
+``AC_decision_table`` takes ``spec`` and ``context`` (each a dict or JSON
+string) and returns ``{result}``. The same operation is exposed as the MCP tool
+``ac_decision_table`` and as a Script Builder command under **Flow**.

docs/source/Eng/eng_index.rst

@@ -75,6 +75,7 @@ Comprehensive guides for all AutoControl features.
    doc/new_features/v50_features_doc
    doc/new_features/v51_features_doc
    doc/new_features/v52_features_doc
+   doc/new_features/v53_features_doc
    doc/ocr_backends/ocr_backends_doc
    doc/observability/observability_doc
    doc/operations_layer/operations_layer_doc

docs/source/Zh/doc/new_features/v53_features_doc.rst

@@ -0,0 +1,53 @@
+DMN 式決策表
+============
+
+巢狀的 ``AC_if_var`` 鏈很快就難以閱讀。決策表將分支外部化為一列列的 ``conditions ->
+outputs``,並以**命中政策(hit policy)**評估 —— 這是 DMN 讓商業規則維持資料驅動且易於審
+查的方式。
+
+每個儲存格條件為萬用字元(``None`` / ``"-"`` / ``"*"``)、字面值(相等)或 ``{"op": "ge",
+"value": 18}``,使用本專案標準比較子(``eq/ne/lt/le/gt/ge/contains/startswith/endswith``
+—— 重用自執行器,不重複)。純標準函式庫;不匯入 ``PySide6``。
+
+命中政策
+--------
+
+================ ===================================================
+政策             行為
+================ ===================================================
+``UNIQUE``       僅可有一條規則命中(多於一條則拋例外)。
+``FIRST``        第一條命中的規則勝出。
+``PRIORITY``     同 FIRST —— 依規則順序取第一個命中。
+``COLLECT``      所有命中規則的 outputs(清單)。
+================ ===================================================
+
+無頭 API
+--------
+
+.. code-block:: python
+
+    from je_auto_control import evaluate_table
+
+    spec = {
+        "inputs": ["age", "country"],
+        "hit_policy": "FIRST",
+        "rules": [
+            {"conditions": {"age": {"op": "lt", "value": 18}},
+             "outputs": {"tier": "minor"}},
+            {"conditions": {"age": {"op": "ge", "value": 18}, "country": "US"},
+             "outputs": {"tier": "us-adult"}},
+            {"conditions": {"age": {"op": "ge", "value": 18}},
+             "outputs": {"tier": "adult"}},
+        ],
+    }
+    evaluate_table(spec, {"age": 30, "country": "DE"})   # -> {"tier": "adult"}
+
+``evaluate_table`` 對單一命中政策回傳命中的 outputs dict(若無則 ``{}``),``COLLECT`` 則
+回傳清單。``DecisionTable`` 類別(``from_dict`` / ``evaluate``)亦可重用。
+
+執行器指令
+----------
+
+``AC_decision_table`` 接受 ``spec`` 與 ``context``(各為 dict 或 JSON 字串),回傳
+``{result}``。相同操作亦提供為 MCP 工具 ``ac_decision_table``,以及 Script Builder 中
+**Flow** 分類下的指令。

docs/source/Zh/zh_index.rst

@@ -75,6 +75,7 @@ AutoControl 所有功能的完整使用指南。
    doc/new_features/v50_features_doc
    doc/new_features/v51_features_doc
    doc/new_features/v52_features_doc
+   doc/new_features/v53_features_doc
    doc/ocr_backends/ocr_backends_doc
    doc/observability/observability_doc
    doc/operations_layer/operations_layer_doc

je_auto_control/__init__.py

@@ -282,6 +282,10 @@
 )
 # Saga orchestrator: multi-step flow with compensating rollback
 from je_auto_control.utils.saga import Saga, SagaResult, run_saga
+# DMN-style decision tables (rules + hit policy)
+from je_auto_control.utils.decision_table import (
+    DecisionTable, Rule, evaluate_table,
+)
 # Background popup/interrupt watchdog (unattended automation)
 from je_auto_control.utils.watchdog import (
     PopupWatchdog, WatchdogRule, default_popup_watchdog,
@@ -746,6 +750,7 @@ def start_autocontrol_gui(*args, **kwargs):
     "WebhookChannel", "WebhookResult", "notify_webhook", "set_default_poster",
     "json_extract", "json_query", "json_query_one",
     "Saga", "SagaResult", "run_saga",
+    "DecisionTable", "Rule", "evaluate_table",
     # MCP server
     "AuditLogger", "HttpMCPServer", "MCPContent", "MCPPrompt",
     "MCPPromptArgument", "MCPResource", "MCPServer", "MCPTool",

je_auto_control/gui/script_builder/command_schema.py

@@ -1154,6 +1154,17 @@ def _add_misc_specs(specs: List[CommandSpec]) -> None:
         ),
         description="Run steps; on failure undo completed steps LIFO.",
     ))
+    specs.append(CommandSpec(
+        "AC_decision_table", "Flow", "Decision Table (DMN)",
+        fields=(
+            FieldSpec("spec", FieldType.STRING,
+                      placeholder='{"inputs": ["age"], "hit_policy": "FIRST", '
+                                  '"rules": [...]}'),
+            FieldSpec("context", FieldType.STRING,
+                      placeholder='{"age": 30}'),
+        ),
+        description="Evaluate inputs against a rule table (hit policy).",
+    ))
     specs.append(CommandSpec(
         "AC_generate_sop", "Report", "Generate SOP Document",
         fields=(

je_auto_control/utils/decision_table/__init__.py

@@ -0,0 +1,6 @@
+"""DMN-style decision tables: rules + hit policy for externalized branching."""
+from je_auto_control.utils.decision_table.decision_table import (
+    DecisionTable, Rule, evaluate_table,
+)
+
+__all__ = ["DecisionTable", "Rule", "evaluate_table"]

je_auto_control/utils/decision_table/decision_table.py

@@ -0,0 +1,97 @@
+"""Evaluate inputs against a table of rules (a DMN-style decision table).
+
+Nested ``AC_if_var`` chains get unreadable fast; a decision table externalizes
+branching into rows of ``conditions -> outputs`` with a *hit policy*. Each cell
+condition is a wildcard (``None`` / ``"-"`` / ``"*"``), a literal (equality), or
+``{"op": "ge", "value": 18}`` using the project's standard comparators
+(``eq/ne/lt/le/gt/ge/contains/startswith/endswith`` — reused from the executor,
+not duplicated).
+
+Hit policies: ``UNIQUE`` (exactly one rule may match, else error), ``FIRST`` /
+``PRIORITY`` (first matching rule wins), ``COLLECT`` (all matches). Pure standard
+library; imports no ``PySide6``.
+"""
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Mapping
+
+HIT_UNIQUE = "UNIQUE"
+HIT_FIRST = "FIRST"
+HIT_PRIORITY = "PRIORITY"
+HIT_COLLECT = "COLLECT"
+_WILDCARDS = (None, "", "-", "*")
+
+
+@dataclass
+class Rule:
+    """One table row: per-input conditions and the outputs to return."""
+
+    conditions: Dict[str, Any] = field(default_factory=dict)
+    outputs: Dict[str, Any] = field(default_factory=dict)
+
+
+def _comparators() -> Dict[str, Any]:
+    from je_auto_control.utils.executor.flow_control import _COMPARATORS
+    return _COMPARATORS
+
+
+def _cell_matches(value: Any, condition: Any) -> bool:
+    if condition in _WILDCARDS:
+        return True
+    if isinstance(condition, dict) and "op" in condition:
+        comparator = _comparators().get(condition["op"])
+        if comparator is None:
+            raise ValueError(f"unknown decision op: {condition['op']!r}")
+        try:
+            return comparator(value, condition.get("value"))
+        except TypeError:
+            return False
+    return value == condition
+
+
+def _rule_matches(rule: Rule, context: Mapping[str, Any]) -> bool:
+    return all(_cell_matches(context.get(name), cond)
+               for name, cond in rule.conditions.items())
+
+
+class DecisionTable:
+    """A list of rules evaluated against an input context by a hit policy."""
+
+    def __init__(self, inputs: List[str], rules: List[Rule],
+                 hit_policy: str = HIT_UNIQUE) -> None:
+        """``inputs`` documents the input names; ``hit_policy`` selects matches."""
+        self.inputs = list(inputs)
+        self.rules = list(rules)
+        self.hit_policy = hit_policy.upper()
+
+    @classmethod
+    def from_dict(cls, spec: Mapping[str, Any]) -> "DecisionTable":
+        """Build a table from a JSON-style ``{inputs, hit_policy, rules}`` spec."""
+        rules = [Rule(dict(r.get("conditions", {})), dict(r.get("outputs", {})))
+                 for r in spec.get("rules", [])]
+        return cls(spec.get("inputs", []), rules,
+                   spec.get("hit_policy", HIT_UNIQUE))
+
+    def evaluate(self, context: Mapping[str, Any]) -> List[Dict[str, Any]]:
+        """Return the outputs of matching rules per the hit policy."""
+        matches = [dict(rule.outputs) for rule in self.rules
+                   if _rule_matches(rule, context)]
+        if self.hit_policy == HIT_UNIQUE and len(matches) > 1:
+            raise ValueError(
+                f"UNIQUE hit policy matched {len(matches)} rules")
+        if self.hit_policy in (HIT_FIRST, HIT_PRIORITY, HIT_UNIQUE):
+            return matches[:1]
+        return matches
+
+
+def evaluate_table(spec: Mapping[str, Any],
+                   context: Mapping[str, Any]) -> Any:
+    """Evaluate a table spec against a context.
+
+    Returns a list for ``COLLECT``; otherwise the single matched outputs dict
+    (or ``{}`` when nothing matches).
+    """
+    table = DecisionTable.from_dict(spec)
+    matches = table.evaluate(context)
+    if table.hit_policy == HIT_COLLECT:
+        return matches
+    return matches[0] if matches else {}

je_auto_control/utils/executor/action_executor.py

@@ -3328,6 +3328,17 @@ def _run_saga(steps: Any) -> Dict[str, Any]:
             "failed_step": result.failed_step, "error": result.error}
 
 
+def _decision_table(spec: Any, context: Any) -> Dict[str, Any]:
+    """Adapter: evaluate a DMN-style decision table against a context."""
+    import json
+    from je_auto_control.utils.decision_table import evaluate_table
+    if isinstance(spec, str):
+        spec = json.loads(spec)
+    if isinstance(context, str):
+        context = json.loads(context)
+    return {"result": evaluate_table(spec, context)}
+
+
 class Executor:
     """
     Executor
@@ -3611,6 +3622,7 @@ def __init__(self):
             "AC_json_query": _json_query,
             "AC_json_extract": _json_extract,
             "AC_run_saga": _run_saga,
+            "AC_decision_table": _decision_table,
             "AC_a11y_record_start": _a11y_record_start,
             "AC_a11y_record_stop": _a11y_record_stop,
             "AC_a11y_record_events": _a11y_record_events,

je_auto_control/utils/mcp_server/tools/_factories.py

@@ -3244,6 +3244,24 @@ def saga_tools() -> List[MCPTool]:
     ]
 
 
+def decision_table_tools() -> List[MCPTool]:
+    return [
+        MCPTool(
+            name="ac_decision_table",
+            description=("Evaluate a DMN-style decision table 'spec' "
+                         "({inputs, hit_policy: UNIQUE/FIRST/PRIORITY/COLLECT, "
+                         "rules:[{conditions, outputs}]}) against a 'context'. "
+                         "Conditions are wildcard/literal/{op,value}. Returns "
+                         "{result} (outputs dict, or list for COLLECT)."),
+            input_schema=schema(
+                {"spec": {"type": "object"}, "context": {"type": "object"}},
+                ["spec", "context"]),
+            handler=h.decision_table,
+            annotations=READ_ONLY,
+        ),
+    ]
+
+
 def unattended_tools() -> List[MCPTool]:
     return [
         MCPTool(
@@ -4307,7 +4325,7 @@ def media_assert_tools() -> List[MCPTool]:
     video_report_tools, fuzzy_tools, artifact_store_tools, image_dedup_tools,
     locale_tools, voice_tools, coordinate_space_tools, loop_guard_tools,
     process_mining_tools, asset_tools, events_tools, notify_channel_tools,
-    jsonpath_tools, saga_tools,
+    jsonpath_tools, saga_tools, decision_table_tools,
     screen_record_tools,
     process_and_shell_tools, remote_desktop_tools, gamepad_tools,
     usb_passthrough_tools, assertion_tools, data_source_tools,