feat(platform): add new services, tools, tests and crews modules

New router intelligence modules (26 files): alert_ingest/store, audit_store,
architecture_pressure, backlog_generator/store, cost_analyzer, data_governance,
dependency_scanner, drift_analyzer, incident_* (5 files), llm_enrichment,
platform_priority_digest, provider_budget, release_check_runner, risk_* (6 files),
signature_state_store, sofiia_auto_router, tool_governance

New services:
- sofiia-console: Dockerfile, adapters/, monitor/nodes/ops/voice modules, launchd, react static
- memory-service: integration_endpoints, integrations, voice_endpoints, static UI
- aurora-service: full app suite (analysis, job_store, orchestrator, reporting, schemas, subagents)
- sofiia-supervisor: new supervisor service
- aistalk-bridge-lite: Telegram bridge lite
- calendar-service: CalDAV calendar service with reminders
- mlx-stt-service / mlx-tts-service: Apple Silicon speech services
- binance-bot-monitor: market monitor service
- node-worker: STT/TTS memory providers

New tools (9): agent_email, browser_tool, contract_tool, observability_tool,
oncall_tool, pr_reviewer_tool, repo_tool, safe_code_executor, secure_vault

New crews: agromatrix_crew (10 modules: depth_classifier, doc_facts, doc_focus,
farm_state, light_reply, llm_factory, memory_manager, proactivity, reflection_engine,
session_context, style_adapter, telemetry)

Tests: 85+ test files for all new modules
Made-with: Cursor

services/aurora-service/app/reporting.py

@@ -0,0 +1,92 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Iterable
+
+from fpdf import FPDF  # type: ignore[import-untyped]
+
+from .schemas import AuroraJob
+
+
+def _line(pdf: FPDF, text: str) -> None:
+    full_width = pdf.w - pdf.l_margin - pdf.r_margin
+    pdf.set_x(pdf.l_margin)
+    pdf.set_font("Helvetica", size=10)
+    pdf.multi_cell(full_width, 5, txt=_soft_wrap_tokens(text))
+
+
+def _section(pdf: FPDF, title: str) -> None:
+    pdf.ln(2)
+    pdf.set_x(pdf.l_margin)
+    pdf.set_font("Helvetica", style="B", size=12)
+    full_width = pdf.w - pdf.l_margin - pdf.r_margin
+    pdf.cell(full_width, 7, txt=title, ln=1)
+
+
+def _soft_wrap_tokens(text: str, chunk: int = 40) -> str:
+    parts = []
+    for token in str(text).split(" "):
+        if len(token) <= chunk:
+            parts.append(token)
+            continue
+        segments = [token[i : i + chunk] for i in range(0, len(token), chunk)]
+        parts.append(" ".join(segments))
+    return " ".join(parts)
+
+
+def _iter_output_rows(job: AuroraJob) -> Iterable[str]:
+    if not job.result:
+        return []
+    for item in job.result.output_files:
+        yield f"[{item.type}] {item.name} | {item.hash}"
+
+
+def generate_forensic_report_pdf(job: AuroraJob, output_path: Path) -> Path:
+    if not job.result:
+        raise RuntimeError("Job has no result data")
+
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    pdf = FPDF(unit="mm", format="A4")
+    pdf.set_auto_page_break(auto=True, margin=14)
+    pdf.add_page()
+
+    pdf.set_font("Helvetica", style="B", size=16)
+    pdf.cell(0, 10, txt="Aurora Forensic Report", ln=1)
+    pdf.set_font("Helvetica", size=9)
+    pdf.cell(0, 5, txt="Autonomous Media Forensics Agent", ln=1)
+    pdf.ln(3)
+
+    _section(pdf, "Case Summary")
+    _line(pdf, f"Job ID: {job.job_id}")
+    _line(pdf, f"Mode: {job.mode}")
+    _line(pdf, f"Media Type: {job.media_type}")
+    _line(pdf, f"Status: {job.status}")
+    _line(pdf, f"Created At: {job.created_at}")
+    _line(pdf, f"Started At: {job.started_at or '-'}")
+    _line(pdf, f"Completed At: {job.completed_at or '-'}")
+    _line(pdf, f"Input File: {job.file_name}")
+    _line(pdf, f"Input Hash: {job.input_hash}")
+    _line(pdf, f"Digital Signature: {job.result.digital_signature or '-'}")
+
+    _section(pdf, "Processing Log")
+    if not job.result.processing_log:
+        _line(pdf, "No processing steps were recorded.")
+    for idx, step in enumerate(job.result.processing_log, start=1):
+        _line(
+            pdf,
+            f"{idx}. {step.step} | agent={step.agent} | model={step.model} | time_ms={step.time_ms}",
+        )
+
+    _section(pdf, "Output Artifacts")
+    rows = list(_iter_output_rows(job))
+    if not rows:
+        _line(pdf, "No output artifacts available.")
+    for row in rows:
+        _line(pdf, row)
+
+    _section(pdf, "Metadata")
+    for k, v in (job.result.metadata or {}).items():
+        _line(pdf, f"{k}: {v}")
+
+    pdf.output(str(output_path))
+    return output_path