BossAgents Real-time Demo Capability Assessment — On-site Verification (2026-07-31)

Method: Static scanning of source code + real HTTP calls to the running service (port 3006) for verification.

Conclusion: All three demo scenarios are fully functional; however, the original analysis contains outdated or incorrect information in multiple areas regarding numbers/tool lists/routing mechanisms. Corrections are provided below.

I. Three Verified and Functional Demo Scenarios (Evidence)

| Scenario | Endpoint | Test Result |

|---|---|---|

| 1. Query Impact Scope of P-1001 | POST /api/change/analyze | ✅ Only {"description":"Query the impact scope of P-1001","change_type":"part"} is passed (no target_id). The system automatically extracts the part number via text regex → queries SCSAI → resolves SCSAI ID 284C6CFC12B34FACA25A416B3D2CD897, and returns the impact chain in affectedParts / affectedModels / affectedProducts. |

| 2. Execute Data Quality Inspection | POST /api/ai-inspector/inspect | ✅ Returns summary: totalChecked:1517, issuesFound:28, autoFixable:4, manualFix:24 (model scope P2); /inspect-stream and /fix-stream are also mounted. |

| 3. View recent governance records | GET /api/audit-logs?days=7 | ✅ Returns logs array (e.g., 36312 records within the 7-day window), structured by category/level; /api/ai-inspector/last-result also returns the last inspection result. |

Additional verification: /api/health 200; /api/change/stats 200 (ECR 28 / ECO 1 / ECN 14); /api/digital-staff/logs?staffId=DS-STAT-001 200 (DS-STAT-001 exists, but no recent execution logs total:0).

II. Key Corrections from Source Text Analysis

1. Digital Staff Count: Original text lists 11 → Actual 37~38

Full scan of source code server/digital-staff/ reveals 38 unique DS-* identifiers (including DS-SCSAI-001, DS-STAT-001, DS-DOC-001, DS-ECR-001, DS-PROC-001, DS-VEN-001, DS-DATA-001/002, DS-PLM-BRAIN-001, and newly added DS-CHIP-001~007, DS-BIZ-001, DS-KNOWLEDGE-001, etc.). The original list is an early snapshot; the system has expanded significantly. The original "lists 11 by ID" is outdated.

2. Built-in intent engine rules: Original list shows 20 → actual 15, and names are inconsistent.

Actual tool names (15) in server/core/intent-engine.js BUILTIN_INTENT_RULES:

search_item_types, inspect_quality, get_governance_history, send_inquiry, check_quotations, procurement_decide, send_purchase_order, search_1688_sourcing, search_anysearch, search_sourcing, start_email_listener, procurement_workflow, boss_confirm_procurement, run_compliance_inspection, dashboard_summary

Differences from original (original is an older version):

• Original items query_bom / query_inventory_analysis / query_employee_info / query_complaint_analysis / generate_quality_report / repair_object_class / change_bom_component no longer exist in the code.
• Code actually includes inspect_quality and get_governance_history, which were not listed in the original.

3. Rule count: Original 10,687 → actual measurement 12,507.

COUNT in sciot_rules_v2 table of server/data/rule_engine.db = 12,507 (including built-in + standard library + object class rules). /api/ai-inspector/inspect model scope actually checks 1,517 entries (a subset). Original 10,687 is an outdated figure.

4. Incorrect description of routing mechanism (functionality unaffected)

The original text mentions "router.post('/analyze') line 1548" and other Express-style routing. In reality, the system is not based on Express router; instead, server.js uses a unified if (pathname.startsWith('/api/change/')) to dispatch to various route modules, which then perform secondary routing internally based on pathname (change.js uses url.startsWith('/api/change/analyze')). The endpoint paths themselves are consistent with the original text and functional; only the "mechanism description" is inaccurate.

5. Audit log endpoints: The original text is correct, but the mounted variable name differs.

server.js uses if (pathname.startsWith('/api/audit-logs')) auditLogRoutes(...) for overall dispatch; audit-log.js exports handleAuditLogApi and supports both /api/audit-logs and /api/audit-logs/risks. Testing confirms functionality. The original text's "Endpoint #2 GET /api/audit-logs" is valid.

6. ai-inspector sub-endpoints: The original text listed multiple items; some are not individually named in server.js but are collectively available.

server.js forwards the entire /api/ai-inspector/* namespace to the aiInspector module (aiInspector is initially null and lazily loaded at runtime; it has been confirmed loaded, otherwise it would return 501). Internal module routes /inspect, /inspect-stream, /fix-stream, /logs, /last-result, /itemtypes, and /rules all exist and are functional (tested /inspect and /last-result successfully). The sub-endpoints listed in the original text are essentially accurate, but server.js does not register them individually; it relies on internal module routing—this point was not explained in the original text.

III. Six Capabilities and ToolRegistry: The original text is correct.

• All six capabilities (identify/validate/repair/optimize/compare/generate) in capability-runtime.js exist.
• ToolRegistry only registers PROCESS_OPTIMIZATION_TOOLS from process-optimization-tools.js, which is a relatively new subsystem and not yet widely used—consistent with the original text.

IV. Real Risk Warnings (Not fully covered in the original text)

1. NL→API Routing Real Linkage: The frontend AiWorkbench.vue's checkKeywordRoute + backend /api/staff/match (keyword weighting + IntentEngine L1/L2/L3 fallback) can indeed route intents like "data quality inspection" and "governance records" to corresponding employees/endpoints. However, for change impact analysis intents like "impact scope/P-1001", the original text acknowledges that keyword matching in document employees (DS-DOC-001 contains "impact analysis/impact scope/impact assessment") is required. In actual testing, the impact analysis API itself is robust (automatically parsing part numbers), but whether natural language input stably hits it depends on whether the frontend keyword table includes "impact". It is recommended to manually open the document employee input before the demo or confirm that keyword routing covers it.

1. Full-mode inspection duration: 12,507 rules with scope:all may take >30s. /inspect-stream SSE has been provided for real-time progress; the streaming version is recommended for demos.

1. aiInspector lazy loading: If the service just started and the module is not initialized, the first call to /api/ai-inspector/* returns 501 "Not Enabled". It is confirmed loaded in current testing, but the demo environment needs to verify warm-up.

1. DS-STAT-001 has no recent execution logs (total:0)—the independent cron inspection may not be continuously triggered. It is recommended to manually trigger it once during the demo to show the log stream.

V. Conclusion

• All three demo scenarios are genuinely usable; no need to worry about "whether they work."
• The original analysis framework (layered tool registration / multi-scenario endpoints / multi-level routing / frontend interface) is directionally correct, but specific numbers (digital employees 11→37, intent tools 20→15, rules 10,687→12,507) and descriptions of the tool list and routing mechanism are outdated/incorrect. This actual test should be taken as the reference.
• The only items to confirm before the demo are: natural language input hits for impact analysis + using the streaming inspection endpoint + service is warmed up (aiInspector is loaded).