feat(ai): 新增 P2-407 報表 no-write 分析

apps/api/src/api/v1/agents.py

@@ -91,6 +91,9 @@ from src.services.ai_agent_professional_task_expansion import (
 from src.services.ai_agent_receipt_readback_owner_review import (
     load_latest_ai_agent_receipt_readback_owner_review,
 )
+from src.services.ai_agent_report_no_write_analysis_runtime import (
+    load_latest_ai_agent_report_no_write_analysis_runtime,
+)
 from src.services.ai_agent_matched_playbook_learning_gap import (
     load_latest_ai_agent_matched_playbook_learning_gap,
 )
@@ -829,6 +832,37 @@ async def get_agent_receipt_readback_owner_review() -> dict[str, Any]:
         ) from exc
 
 
+@router.get(
+    "/agent-report-no-write-analysis-runtime",
+    response_model=dict[str, Any],
+    summary="取得 P2-407 AI Agent 報表 no-write 分析 runtime",
+    description=(
+        "讀取最新已提交的 P2-407 AI Agent 報表 no-write 分析快照；此端點只呈現 "
+        "OpenClaw、Hermes、NemoTron 讀取日報 / 週報 / 月報、P2-406B receipt owner review、"
+        "P2-004 供應鏈漂移與 P2-403J 報表真相後產生的分析草稿與風險分級。"
+        "它不啟動 live AI worker、不排程實發、不寫 Gateway queue、不送 Telegram、"
+        "不呼叫 Bot API、不寫 receipt production target、不寫 production、不讀 secret、"
+        "不呼叫付費 API、不改主機、不執行 kubectl 或不可逆操作。"
+    ),
+)
+async def get_agent_report_no_write_analysis_runtime() -> dict[str, Any]:
+    """回傳最新 P2-407 report no-write analysis runtime 只讀快照。"""
+    try:
+        payload = await asyncio.to_thread(load_latest_ai_agent_report_no_write_analysis_runtime)
+        return redact_public_lan_topology(payload)
+    except FileNotFoundError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=str(exc),
+        ) from exc
+    except (json.JSONDecodeError, ValueError) as exc:
+        logger.error("ai_agent_report_no_write_analysis_runtime_invalid", error=str(exc))
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="P2-407 AI Agent 報表 no-write 分析 runtime 快照無效",
+        ) from exc
+
+
 @router.get(
     "/agent-communication-learning-contract",
     response_model=dict[str, Any],

apps/api/src/services/ai_agent_report_no_write_analysis_runtime.py

@@ -0,0 +1,374 @@
+"""
+P2-407 AI Agent report no-write analysis runtime snapshot.
+
+Loads the latest committed analysis draft that lets OpenClaw, Hermes, and
+NemoTron read report evidence and propose risk-ranked recommendations. This
+module intentionally does not run a live AI worker, send Telegram, write a
+Gateway queue, write delivery receipts, read secrets, call paid APIs, mutate
+hosts, run kubectl, or write production state.
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from typing import Any
+
+from src.services.snapshot_paths import default_evaluations_dir
+
+_DEFAULT_EVALUATIONS_DIR = default_evaluations_dir(Path(__file__))
+_SNAPSHOT_PATTERN = "ai_agent_report_no_write_analysis_runtime_*.json"
+_SCHEMA_VERSION = "ai_agent_report_no_write_analysis_runtime_v1"
+_RUNTIME_AUTHORITY = "report_analysis_no_write_runtime_only_committed_snapshot"
+_EXPECTED_CURRENT_TASK = "P2-407"
+_EXPECTED_NEXT_TASK = "P2-408"
+_EXPECTED_CANONICAL_ROOM = "AwoooI SRE 戰情室"
+_EXPECTED_CANONICAL_ROOM_ENV = "SRE_GROUP_CHAT_ID"
+_EXPECTED_SOURCE_SCHEMAS = {
+    "ai_agent_report_status_board_v1",
+    "ai_agent_report_automation_review_v1",
+    "ai_agent_receipt_readback_owner_review_v1",
+    "dependency_supply_chain_drift_monitor_v1",
+    "ai_agent_report_truth_actionability_review_v1",
+}
+_TRUE_TRUTH_FLAGS = {
+    "daily_weekly_monthly_reports_loaded",
+    "agent_workload_loaded",
+    "charts_loaded",
+    "receipt_owner_review_loaded",
+    "dependency_drift_loaded",
+    "report_truth_loaded",
+    "analysis_draft_snapshot_ready",
+}
+_FALSE_TRUTH_FLAGS = {
+    "ai_analysis_runtime_enabled",
+    "report_delivery_enabled",
+    "telegram_send_enabled",
+    "gateway_queue_write_enabled",
+    "bot_api_call_enabled",
+    "receipt_production_write_enabled",
+    "production_write_enabled",
+    "secret_read_enabled",
+    "paid_api_call_enabled",
+    "host_write_enabled",
+    "kubectl_action_enabled",
+}
+_ZERO_TRUTH_COUNTS = {
+    "live_ai_analysis_run_count_24h",
+    "live_report_delivery_count_24h",
+    "telegram_send_count_24h",
+    "gateway_queue_write_count_24h",
+    "bot_api_call_count_24h",
+    "receipt_production_write_count_24h",
+    "production_write_count_24h",
+}
+_TRUE_BOUNDARY_FLAGS = {
+    "read_only_analysis_allowed",
+    "draft_snapshot_write_allowed",
+}
+_FALSE_BOUNDARY_FLAGS = {
+    "ai_analysis_runtime_enabled",
+    "report_delivery_enabled",
+    "telegram_send_enabled",
+    "gateway_queue_write_enabled",
+    "bot_api_call_enabled",
+    "receipt_production_write_enabled",
+    "production_write_enabled",
+    "secret_read_enabled",
+    "paid_api_call_enabled",
+    "host_write_enabled",
+    "kubectl_action_enabled",
+    "destructive_operation_enabled",
+    "openclaw_replacement_allowed",
+}
+_ZERO_ROLLUP_FIELDS = {
+    "live_report_delivery_count",
+    "live_ai_analysis_count",
+    "telegram_send_count",
+    "gateway_queue_write_count",
+    "bot_api_call_count",
+    "receipt_production_write_count",
+    "production_write_count",
+    "secret_read_count",
+    "paid_api_call_count",
+    "host_write_count",
+    "kubectl_action_count",
+}
+_FORBIDDEN_PUBLIC_TERMS = {
+    "批准！繼續",
+    "In app browser",
+    "My request for Codex",
+    "chain_of_thought",
+    "chain-of-thought",
+    "private reasoning text",
+    "authorization_header",
+    "authorization header value",
+    "telegram token value",
+    "raw prompt",
+    "raw_payload",
+}
+
+
+def load_latest_ai_agent_report_no_write_analysis_runtime(
+    evaluations_dir: Path | None = None,
+) -> dict[str, Any]:
+    """Load the newest committed P2-407 no-write report analysis snapshot."""
+    directory = evaluations_dir or _DEFAULT_EVALUATIONS_DIR
+    candidates = sorted(directory.glob(_SNAPSHOT_PATTERN))
+    if not candidates:
+        raise FileNotFoundError(
+            f"no AI Agent report no-write analysis runtime snapshots found in {directory}"
+        )
+
+    latest = candidates[-1]
+    with latest.open(encoding="utf-8") as handle:
+        payload = json.load(handle)
+
+    if not isinstance(payload, dict):
+        raise ValueError(f"{latest}: expected JSON object")
+
+    label = str(latest)
+    _require_schema(payload, label)
+    _require_sources(payload, label)
+    _require_analysis_truth(payload, label)
+    _require_report_inputs(payload, label)
+    _require_agent_passes(payload, label)
+    _require_recommendations_and_artifacts(payload, label)
+    _require_owner_gates(payload, label)
+    _require_boundaries(payload, label)
+    _require_rollups(payload, label)
+    _require_no_forbidden_public_terms(payload, label)
+    return payload
+
+
+def _require_schema(payload: dict[str, Any], label: str) -> None:
+    if payload.get("schema_version") != _SCHEMA_VERSION:
+        raise ValueError(f"{label}: expected schema_version={_SCHEMA_VERSION}")
+    status = payload.get("program_status") or {}
+    expected = {
+        "overall_completion_percent": 100,
+        "current_priority": "P2",
+        "current_task_id": _EXPECTED_CURRENT_TASK,
+        "next_task_id": _EXPECTED_NEXT_TASK,
+        "read_only_mode": True,
+        "runtime_authority": _RUNTIME_AUTHORITY,
+    }
+    mismatches = _mismatches(status, expected)
+    if mismatches:
+        raise ValueError(f"{label}: program_status mismatch: {mismatches}")
+    if not status.get("status_note"):
+        raise ValueError(f"{label}: program_status.status_note is required")
+
+
+def _require_sources(payload: dict[str, Any], label: str) -> None:
+    if not payload.get("source_refs"):
+        raise ValueError(f"{label}: source_refs must not be empty")
+    sources = payload.get("source_readbacks") or []
+    schemas = {item.get("source_schema_version") for item in sources}
+    missing = sorted(_EXPECTED_SOURCE_SCHEMAS - schemas)
+    if missing:
+        raise ValueError(f"{label}: missing source schemas: {missing}")
+    for item in sources:
+        readback_id = item.get("readback_id") or "<missing>"
+        for field in ("source_ref", "endpoint", "owner_agent", "status", "key_readback", "next_action"):
+            if not item.get(field):
+                raise ValueError(f"{label}: source readback {readback_id} missing {field}")
+
+
+def _require_analysis_truth(payload: dict[str, Any], label: str) -> None:
+    truth = payload.get("analysis_truth") or {}
+    missing_true = sorted(flag for flag in _TRUE_TRUTH_FLAGS if truth.get(flag) is not True)
+    if missing_true:
+        raise ValueError(f"{label}: analysis truth flags must remain true: {missing_true}")
+    unsafe_false = sorted(flag for flag in _FALSE_TRUTH_FLAGS if truth.get(flag) is not False)
+    if unsafe_false:
+        raise ValueError(f"{label}: analysis truth flags must remain false: {unsafe_false}")
+    non_zero = sorted(field for field in _ZERO_TRUTH_COUNTS if truth.get(field) != 0)
+    if non_zero:
+        raise ValueError(f"{label}: live analysis truth counts must remain zero: {non_zero}")
+    if not truth.get("truth_note"):
+        raise ValueError(f"{label}: analysis_truth.truth_note is required")
+
+
+def _require_report_inputs(payload: dict[str, Any], label: str) -> None:
+    inputs = payload.get("report_inputs") or []
+    input_ids = {item.get("report_id") for item in inputs}
+    if input_ids != {"daily", "weekly", "monthly"}:
+        raise ValueError(f"{label}: report_inputs must include daily, weekly, monthly")
+    for item in inputs:
+        report_id = item.get("report_id") or "<missing>"
+        if item.get("completion_percent") != 100:
+            raise ValueError(f"{label}: report input {report_id} completion_percent must remain 100")
+        if not isinstance(item.get("actionability_score"), int) or item.get("actionability_score") <= 0:
+            raise ValueError(f"{label}: report input {report_id} actionability_score must be positive")
+        if not item.get("analysis_focus") or not item.get("blocked_runtime_action"):
+            raise ValueError(f"{label}: report input {report_id} missing focus or blocked action")
+
+
+def _require_agent_passes(payload: dict[str, Any], label: str) -> None:
+    passes = payload.get("agent_analysis_passes") or []
+    agent_ids = {item.get("agent_id") for item in passes}
+    if agent_ids != {"openclaw", "hermes", "nemotron"}:
+        raise ValueError(f"{label}: agent_analysis_passes must include OpenClaw, Hermes, NemoTron")
+    for item in passes:
+        agent_id = item.get("agent_id") or "<missing>"
+        if item.get("live_runtime_write_allowed") is not False:
+            raise ValueError(f"{label}: agent pass {agent_id} live_runtime_write_allowed must remain false")
+        if not item.get("summary") or not item.get("handoff_to"):
+            raise ValueError(f"{label}: agent pass {agent_id} missing summary or handoff")
+
+
+def _require_recommendations_and_artifacts(payload: dict[str, Any], label: str) -> None:
+    recommendations = payload.get("draft_recommendations") or []
+    if len(recommendations) < 1:
+        raise ValueError(f"{label}: draft_recommendations must not be empty")
+    for item in recommendations:
+        recommendation_id = item.get("recommendation_id") or "<missing>"
+        if not isinstance(item.get("actionability_score"), int) or item.get("actionability_score") <= 0:
+            raise ValueError(f"{label}: recommendation {recommendation_id} actionability_score must be positive")
+        if not item.get("blocked_runtime_action"):
+            raise ValueError(f"{label}: recommendation {recommendation_id} missing blocked_runtime_action")
+        if item.get("risk_tier") in {"high", "critical"} and item.get("approval_required") is not True:
+            raise ValueError(f"{label}: high/critical recommendation {recommendation_id} must require approval")
+
+    artifacts = payload.get("draft_artifacts") or []
+    if len(artifacts) < 1:
+        raise ValueError(f"{label}: draft_artifacts must not be empty")
+    for item in artifacts:
+        artifact_id = item.get("artifact_id") or "<missing>"
+        for flag in ("writes_production", "sends_telegram", "contains_secret"):
+            if item.get(flag) is not False:
+                raise ValueError(f"{label}: draft artifact {artifact_id}.{flag} must remain false")
+        if not item.get("evidence_ref"):
+            raise ValueError(f"{label}: draft artifact {artifact_id} evidence_ref is required")
+
+
+def _require_owner_gates(payload: dict[str, Any], label: str) -> None:
+    gates = payload.get("owner_review_gates") or []
+    if len(gates) < 1:
+        raise ValueError(f"{label}: owner_review_gates must not be empty")
+    for gate in gates:
+        gate_id = gate.get("gate_id") or "<missing>"
+        if gate.get("risk_tier") in {"high", "critical"} and gate.get("status") not in {
+            "owner_review_required",
+            "blocked_by_runtime_gate",
+        }:
+            raise ValueError(f"{label}: high/critical owner gate {gate_id} must remain blocked or owner-review")
+        for field in ("required_fields", "acceptance_checks", "blocked_runtime_actions"):
+            if not gate.get(field):
+                raise ValueError(f"{label}: owner gate {gate_id} missing {field}")
+
+
+def _require_boundaries(payload: dict[str, Any], label: str) -> None:
+    boundaries = payload.get("activation_boundaries") or {}
+    missing_true = sorted(flag for flag in _TRUE_BOUNDARY_FLAGS if boundaries.get(flag) is not True)
+    if missing_true:
+        raise ValueError(f"{label}: activation boundaries must remain true: {missing_true}")
+    unsafe_false = sorted(flag for flag in _FALSE_BOUNDARY_FLAGS if boundaries.get(flag) is not False)
+    if unsafe_false:
+        raise ValueError(f"{label}: activation boundaries must remain false: {unsafe_false}")
+
+    telegram = payload.get("telegram_policy") or {}
+    expected_telegram = {
+        "canonical_room": _EXPECTED_CANONICAL_ROOM,
+        "canonical_room_env": _EXPECTED_CANONICAL_ROOM_ENV,
+        "gateway_queue_write_allowed": False,
+        "direct_bot_api_allowed": False,
+        "telegram_send_allowed": False,
+        "receipt_write_allowed": False,
+    }
+    mismatches = _mismatches(telegram, expected_telegram)
+    if mismatches:
+        raise ValueError(f"{label}: telegram_policy mismatch: {mismatches}")
+
+    redaction = payload.get("display_redaction_contract") or {}
+    for flag in (
+        "redaction_required",
+    ):
+        if redaction.get(flag) is not True:
+            raise ValueError(f"{label}: display redaction flag {flag} must remain true")
+    for flag in (
+        "raw_report_payload_display_allowed",
+        "private_reasoning_display_allowed",
+        "secret_value_display_allowed",
+        "work_window_transcript_display_allowed",
+    ):
+        if redaction.get(flag) is not False:
+            raise ValueError(f"{label}: display redaction flag {flag} must remain false")
+
+
+def _require_rollups(payload: dict[str, Any], label: str) -> None:
+    rollups = payload.get("rollups") or {}
+    sources = payload.get("source_readbacks") or []
+    inputs = payload.get("report_inputs") or []
+    passes = payload.get("agent_analysis_passes") or []
+    recommendations = payload.get("draft_recommendations") or []
+    artifacts = payload.get("draft_artifacts") or []
+    gates = payload.get("owner_review_gates") or []
+    blocked_actions = {
+        *(item.get("blocked_runtime_action") for item in recommendations),
+        *(
+            action
+            for gate in gates
+            for action in (gate.get("blocked_runtime_actions") or [])
+        ),
+    }
+    blocked_actions.discard(None)
+    expected = {
+        "source_readback_count": len(sources),
+        "report_input_count": len(inputs),
+        "agent_analysis_pass_count": len(passes),
+        "draft_recommendation_count": len(recommendations),
+        "draft_artifact_count": len(artifacts),
+        "owner_review_gate_count": len(gates),
+        "approval_required_recommendation_count": sum(
+            1 for item in recommendations if item.get("approval_required") is True
+        ),
+        "low_risk_recommendation_count": sum(1 for item in recommendations if item.get("risk_tier") == "low"),
+        "medium_risk_recommendation_count": sum(1 for item in recommendations if item.get("risk_tier") == "medium"),
+        "high_risk_recommendation_count": sum(1 for item in recommendations if item.get("risk_tier") == "high"),
+        "critical_risk_recommendation_count": sum(1 for item in recommendations if item.get("risk_tier") == "critical"),
+        "actionability_score_ready_count": sum(
+            1 for item in recommendations if isinstance(item.get("actionability_score"), int) and item["actionability_score"] > 0
+        ),
+        "blocked_runtime_action_count": len(blocked_actions),
+    }
+    mismatches = {
+        key: {"expected": value, "actual": rollups.get(key)}
+        for key, value in expected.items()
+        if rollups.get(key) != value
+    }
+    if mismatches:
+        raise ValueError(f"{label}: rollup counts must match payload sections: {mismatches}")
+
+    approval_required_ids = sorted(
+        item.get("recommendation_id")
+        for item in recommendations
+        if item.get("approval_required") is True
+    )
+    if sorted(rollups.get("approval_required_recommendation_ids") or []) != approval_required_ids:
+        raise ValueError(f"{label}: approval_required_recommendation_ids mismatch")
+
+    non_zero = sorted(field for field in _ZERO_ROLLUP_FIELDS if rollups.get(field) != 0)
+    if non_zero:
+        raise ValueError(f"{label}: live rollup counts must remain zero: {non_zero}")
+
+
+def _require_no_forbidden_public_terms(payload: dict[str, Any], label: str) -> None:
+    public_text = json.dumps(payload, ensure_ascii=False)
+    lower_public_text = public_text.lower()
+    leaked_terms = sorted(
+        term
+        for term in _FORBIDDEN_PUBLIC_TERMS
+        if (term.lower() if term.isascii() else term) in lower_public_text
+    )
+    if leaked_terms:
+        raise ValueError(f"{label}: forbidden public terms present: {leaked_terms}")
+
+
+def _mismatches(actual: dict[str, Any], expected: dict[str, Any]) -> dict[str, dict[str, Any]]:
+    return {
+        key: {"expected": expected_value, "actual": actual.get(key)}
+        for key, expected_value in expected.items()
+        if actual.get(key) != expected_value
+    }