| # | Role | Agent ID | Public IP | Private IP |
|---|---|---|---|---|
| 1 | agent | ai:alice | 134.122.13.6 | 10.11.2.5 |
| 2 | agent | ai:bob | 138.197.76.170 | 10.11.2.3 |
| 3 | agent | ai:charlie | 104.236.127.86 | 10.11.2.4 |
| 4 | memory-only | — | 165.227.121.142 | 10.11.2.2 |
Per the authoritative baseline spec, every agent node must emit a self-attestation before any scenario is permitted to run. This run's attestation:
Spec version: 1.4.0 — see authoritative baseline.
| Node | Agent | Framework | Authentic | MCP ai-memory | xAI cfg | xAI default | Agent ID | Federation | UFW off | iptables | dead-man | F1 xAI | F2a substrate | F2b agent (non-gating) | Config SHA | Pass |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| node-1 | ai:alice | hermes Hermes Agent v0.12.0 (2026.4.30) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | — | fa358f9a9059 | PASS |
| node-2 | ai:bob | hermes Hermes Agent v0.12.0 (2026.4.30) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | — | 21635cf63640 | PASS |
| node-3 | ai:charlie | hermes Hermes Agent v0.12.0 (2026.4.30) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | — | ce52d772ef5a | PASS |
{
"baseline_pass": true,
"per_node": [
{
"spec_version": "1.4.0",
"agent_type": "hermes",
"agent_id": "ai:alice",
"node_index": "1",
"framework_version": "Hermes Agent v0.12.0 (2026.4.30)",
"ai_memory_version": "0.6.3.1",
"peer_urls": "https://10.11.2.3:9077,https://10.11.2.4:9077,https://10.11.2.2:9077",
"config_file_sha256": "fa358f9a90597243fb96224babd541399bd7b1e972f364605308ab1e2d9dd2c7",
"config_attestation": {
"framework_is_authentic": true,
"mcp_server_ai_memory_registered": true,
"llm_backend_is_xai_grok": true,
"llm_is_default_provider": true,
"mcp_command_is_ai_memory": true,
"agent_id_stamped": true,
"federation_live": true,
"ufw_disabled": true,
"iptables_flushed": true,
"dead_man_switch_scheduled": true
},
"negative_invariants": {
"_description": "Alternative A2A channels must be OFF so a passing scenario is only passing via ai-memory shared memory. Any true here = thesis-preserving.",
"a2a_protocol_off": true,
"sub_agent_or_sessions_spawn_off": true,
"alternative_channels_off": true,
"tool_allowlist_is_memory_only": true,
"a2a_gate_profile_locked": true
},
"functional_probes": {
"xai_grok_chat_reachable": true,
"xai_grok_sample_reply": "READY",
"substrate_http_canary_f2a": true,
"substrate_http_canary_uuid": "527392b4-6046-4b16-aec5-a773b4010cf1",
"agent_mcp_canary_f2b": false,
"agent_mcp_canary_uuid": "50b962fc-50aa-4662-b14f-b651030b831d",
"agent_canary_response_head": " session_id: 20260502_174345_e04586 I'm sorry, but I don't have access to an \"ai-memory MCP\" or the \"mcp_memory_memory_store\" tool you're referring to. My available tools are limited to the ones provided in my configuration, and none match that name or description. If you can clarify or provide more details about the intended tool or how to access it, I may be able to assist further. ",
"_f2b_note": "F2b is LLM-dependent and non-blocking. F2a (deterministic HTTP substrate) gates baseline_pass.",
"mesh_connectivity_f4": true,
"mesh_edges_ok": 3,
"mesh_edges_total": 3,
"mesh_edges_detail": "10.11.2.3:9077:OK,10.11.2.4:9077:OK,10.11.2.2:9077:OK",
"_f4_note": "F4 verifies this local nodes N-1 OUTBOUND mesh edges to every peer via both GET health and POST sync_push dry_run. Aggregator ANDs across N nodes to confirm full N*(N-1) bidirectional reachability. Gates baseline_pass.",
"ai_memory_mcp_stdio_f5": true,
"ai_memory_mcp_stdio_init_ok": true,
"ai_memory_mcp_stdio_tools_ok": true,
"ai_memory_mcp_stdio_tools_found": "memory_agent_list,memory_agent_register,memory_archive_list,memory_archive_purge,memory_archive_restore,memory_archive_stats,memory_auto_tag,memory_capabilities,memory_check_duplicate,memory_consolidate,memory_delete,memory_detect_contradiction,memory_entity_get_by_alias,memory_entity_register,memory_expand_query,memory_forget,memory_gc,memory_get,memory_get_links,memory_get_taxonomy,memory_inbox,memory_kg_invalidate,memory_kg_query,memory_kg_timeline,memory_link,memory_list,memory_list_subscriptions,memory_namespace_clear_standard,memory_namespace_get_standard,memory_namespace_set_standard,memory_notify,memory_pending_approve,memory_pending_list,memory_pending_reject,memory_promote,memory_recall,memory_search,memory_session_start,memory_stats,memory_store,memory_subscribe,memory_unsubscribe,memory_update",
"_f5_note": "F5 spawns the ai-memory stdio MCP subprocess using the framework-configured invocation and verifies initialize + tools/list return memory_store, memory_recall, memory_list. Deterministic (no LLM). Gates baseline_pass.",
"tls_mode": "mtls",
"tls_handshake_f6": true,
"tls_handshake_f6_reason": "",
"mtls_enforcement_f7": true,
"mtls_enforcement_f7_reason": "",
"_f6_f7_note": "F6 verifies the TLS 1.3 handshake against the local serve + CA chain. F7 verifies mTLS enforcement — anonymous client rejected, whitelisted client accepted. Both gate baseline_pass when tls_mode != off / mtls respectively.",
"embedder_loaded_f8": true,
"embedder_loaded_f8_reason": "",
"_f8_note": "F8 verifies /api/v1/capabilities reports features.embedder_loaded=true — i.e. the MiniLM embedder initialised at serve startup. Gates baseline_pass unconditionally. Without this, scenario-18 silently black-holes (semantic recall returns 0 rows).",
"agent_mcp_ai_memory_canary": true,
"canary_uuid": "527392b4-6046-4b16-aec5-a773b4010cf1",
"canary_namespace": "_baseline_canary_f2a"
},
"baseline_pass": true
},
{
"spec_version": "1.4.0",
"agent_type": "hermes",
"agent_id": "ai:bob",
"node_index": "2",
"framework_version": "Hermes Agent v0.12.0 (2026.4.30)",
"ai_memory_version": "0.6.3.1",
"peer_urls": "https://10.11.2.5:9077,https://10.11.2.4:9077,https://10.11.2.2:9077",
"config_file_sha256": "21635cf6364057fd2a004d28aac89abf8438671d85f9fd2ed1e654d812d23ff1",
"config_attestation": {
"framework_is_authentic": true,
"mcp_server_ai_memory_registered": true,
"llm_backend_is_xai_grok": true,
"llm_is_default_provider": true,
"mcp_command_is_ai_memory": true,
"agent_id_stamped": true,
"federation_live": true,
"ufw_disabled": true,
"iptables_flushed": true,
"dead_man_switch_scheduled": true
},
"negative_invariants": {
"_description": "Alternative A2A channels must be OFF so a passing scenario is only passing via ai-memory shared memory. Any true here = thesis-preserving.",
"a2a_protocol_off": true,
"sub_agent_or_sessions_spawn_off": true,
"alternative_channels_off": true,
"tool_allowlist_is_memory_only": true,
"a2a_gate_profile_locked": true
},
"functional_probes": {
"xai_grok_chat_reachable": true,
"xai_grok_sample_reply": "READY",
"substrate_http_canary_f2a": true,
"substrate_http_canary_uuid": "c884e734-d88b-4f3b-9005-cedbe45d8a19",
"agent_mcp_canary_f2b": false,
"agent_mcp_canary_uuid": "9001437a-f954-4998-9cea-332e001bb7a6",
"agent_canary_response_head": " session_id: 20260502_174326_c0ba3f I'm sorry, but I don't have access to an MCP tool named \"mcp_memory_memory_store\" or any AI-memory MCP integration. My available tools are limited to the ones provided (like memory, terminal, etc.). If this is for configuring Hermes Agent or a custom setup, I can help with that using the hermes-agent skill—let me know more details. ",
"_f2b_note": "F2b is LLM-dependent and non-blocking. F2a (deterministic HTTP substrate) gates baseline_pass.",
"mesh_connectivity_f4": true,
"mesh_edges_ok": 3,
"mesh_edges_total": 3,
"mesh_edges_detail": "10.11.2.5:9077:OK,10.11.2.4:9077:OK,10.11.2.2:9077:OK",
"_f4_note": "F4 verifies this local nodes N-1 OUTBOUND mesh edges to every peer via both GET health and POST sync_push dry_run. Aggregator ANDs across N nodes to confirm full N*(N-1) bidirectional reachability. Gates baseline_pass.",
"ai_memory_mcp_stdio_f5": true,
"ai_memory_mcp_stdio_init_ok": true,
"ai_memory_mcp_stdio_tools_ok": true,
"ai_memory_mcp_stdio_tools_found": "memory_agent_list,memory_agent_register,memory_archive_list,memory_archive_purge,memory_archive_restore,memory_archive_stats,memory_auto_tag,memory_capabilities,memory_check_duplicate,memory_consolidate,memory_delete,memory_detect_contradiction,memory_entity_get_by_alias,memory_entity_register,memory_expand_query,memory_forget,memory_gc,memory_get,memory_get_links,memory_get_taxonomy,memory_inbox,memory_kg_invalidate,memory_kg_query,memory_kg_timeline,memory_link,memory_list,memory_list_subscriptions,memory_namespace_clear_standard,memory_namespace_get_standard,memory_namespace_set_standard,memory_notify,memory_pending_approve,memory_pending_list,memory_pending_reject,memory_promote,memory_recall,memory_search,memory_session_start,memory_stats,memory_store,memory_subscribe,memory_unsubscribe,memory_update",
"_f5_note": "F5 spawns the ai-memory stdio MCP subprocess using the framework-configured invocation and verifies initialize + tools/list return memory_store, memory_recall, memory_list. Deterministic (no LLM). Gates baseline_pass.",
"tls_mode": "mtls",
"tls_handshake_f6": true,
"tls_handshake_f6_reason": "",
"mtls_enforcement_f7": true,
"mtls_enforcement_f7_reason": "",
"_f6_f7_note": "F6 verifies the TLS 1.3 handshake against the local serve + CA chain. F7 verifies mTLS enforcement — anonymous client rejected, whitelisted client accepted. Both gate baseline_pass when tls_mode != off / mtls respectively.",
"embedder_loaded_f8": true,
"embedder_loaded_f8_reason": "",
"_f8_note": "F8 verifies /api/v1/capabilities reports features.embedder_loaded=true — i.e. the MiniLM embedder initialised at serve startup. Gates baseline_pass unconditionally. Without this, scenario-18 silently black-holes (semantic recall returns 0 rows).",
"agent_mcp_ai_memory_canary": true,
"canary_uuid": "c884e734-d88b-4f3b-9005-cedbe45d8a19",
"canary_namespace": "_baseline_canary_f2a"
},
"baseline_pass": true
},
{
"spec_version": "1.4.0",
"agent_type": "hermes",
"agent_id": "ai:charlie",
"node_index": "3",
"framework_version": "Hermes Agent v0.12.0 (2026.4.30)",
"ai_memory_version": "0.6.3.1",
"peer_urls": "https://10.11.2.5:9077,https://10.11.2.3:9077,https://10.11.2.2:9077",
"config_file_sha256": "ce52d772ef5a00968db29fb80eea7a14206b0a258a00ff2165db725405474618",
"config_attestation": {
"framework_is_authentic": true,
"mcp_server_ai_memory_registered": true,
"llm_backend_is_xai_grok": true,
"llm_is_default_provider": true,
"mcp_command_is_ai_memory": true,
"agent_id_stamped": true,
"federation_live": true,
"ufw_disabled": true,
"iptables_flushed": true,
"dead_man_switch_scheduled": true
},
"negative_invariants": {
"_description": "Alternative A2A channels must be OFF so a passing scenario is only passing via ai-memory shared memory. Any true here = thesis-preserving.",
"a2a_protocol_off": true,
"sub_agent_or_sessions_spawn_off": true,
"alternative_channels_off": true,
"tool_allowlist_is_memory_only": true,
"a2a_gate_profile_locked": true
},
"functional_probes": {
"xai_grok_chat_reachable": true,
"xai_grok_sample_reply": "READY",
"substrate_http_canary_f2a": true,
"substrate_http_canary_uuid": "c2f0191f-f446-419f-9871-61dc851eea6e",
"agent_mcp_canary_f2b": false,
"agent_mcp_canary_uuid": "423f9fb3-ef9f-44b9-94d6-509b71314272",
"agent_canary_response_head": " session_id: 20260502_174302_b08584 I'm sorry, but I don't have access to an \"ai-memory MCP\" or the \"mcp_memory_memory_store\" tool. The available tools are listed in my system configuration, and this one isn't among them. If you can provide more details or clarify the request using the available tools (like memory or terminal), I can assist further. ",
"_f2b_note": "F2b is LLM-dependent and non-blocking. F2a (deterministic HTTP substrate) gates baseline_pass.",
"mesh_connectivity_f4": true,
"mesh_edges_ok": 3,
"mesh_edges_total": 3,
"mesh_edges_detail": "10.11.2.5:9077:OK,10.11.2.3:9077:OK,10.11.2.2:9077:OK",
"_f4_note": "F4 verifies this local nodes N-1 OUTBOUND mesh edges to every peer via both GET health and POST sync_push dry_run. Aggregator ANDs across N nodes to confirm full N*(N-1) bidirectional reachability. Gates baseline_pass.",
"ai_memory_mcp_stdio_f5": true,
"ai_memory_mcp_stdio_init_ok": true,
"ai_memory_mcp_stdio_tools_ok": true,
"ai_memory_mcp_stdio_tools_found": "memory_agent_list,memory_agent_register,memory_archive_list,memory_archive_purge,memory_archive_restore,memory_archive_stats,memory_auto_tag,memory_capabilities,memory_check_duplicate,memory_consolidate,memory_delete,memory_detect_contradiction,memory_entity_get_by_alias,memory_entity_register,memory_expand_query,memory_forget,memory_gc,memory_get,memory_get_links,memory_get_taxonomy,memory_inbox,memory_kg_invalidate,memory_kg_query,memory_kg_timeline,memory_link,memory_list,memory_list_subscriptions,memory_namespace_clear_standard,memory_namespace_get_standard,memory_namespace_set_standard,memory_notify,memory_pending_approve,memory_pending_list,memory_pending_reject,memory_promote,memory_recall,memory_search,memory_session_start,memory_stats,memory_store,memory_subscribe,memory_unsubscribe,memory_update",
"_f5_note": "F5 spawns the ai-memory stdio MCP subprocess using the framework-configured invocation and verifies initialize + tools/list return memory_store, memory_recall, memory_list. Deterministic (no LLM). Gates baseline_pass.",
"tls_mode": "mtls",
"tls_handshake_f6": true,
"tls_handshake_f6_reason": "",
"mtls_enforcement_f7": true,
"mtls_enforcement_f7_reason": "",
"_f6_f7_note": "F6 verifies the TLS 1.3 handshake against the local serve + CA chain. F7 verifies mTLS enforcement — anonymous client rejected, whitelisted client accepted. Both gate baseline_pass when tls_mode != off / mtls respectively.",
"embedder_loaded_f8": true,
"embedder_loaded_f8_reason": "",
"_f8_note": "F8 verifies /api/v1/capabilities reports features.embedder_loaded=true — i.e. the MiniLM embedder initialised at serve startup. Gates baseline_pass unconditionally. Without this, scenario-18 silently black-holes (semantic recall returns 0 rows).",
"agent_mcp_ai_memory_canary": true,
"canary_uuid": "c2f0191f-f446-419f-9871-61dc851eea6e",
"canary_namespace": "_baseline_canary_f2a"
},
"baseline_pass": true
}
]
}
Workflow-level probe answering "can agents communicate through ai-memory?". Writer ai:alice posted canary UUID 242bab27-4f24-4ddb-bc6a-16e38d2d95d5 to namespace _baseline_peer_canary via node-1's local ai-memory serve HTTP. After W=2 fanout settle, probe confirmed the canary on each of the 3 peer nodes via their local GET /api/v1/memories.
{
"probe": "F3",
"name": "peer-a2a-via-shared-memory",
"description": "Writer agent posts a canary via local ai-memory HTTP on node-1; verifies the row propagates to the 3 peer nodes (W=2/N=4 quorum) before scenarios run.",
"canary_uuid": "242bab27-4f24-4ddb-bc6a-16e38d2d95d5",
"canary_namespace": "_baseline_peer_canary",
"writer_agent": "ai:alice",
"pass": true
}
Run focus
What this campaign tested: The run requested 31 scenarios (1,1b,2,4-6,9-18,22-25,28-42) covering transport protocols, framework integrations, and memory primitives in a 4-node DigitalOcean federation mesh with hermes agents, but no scenarios executed successfully due to reporting failure.
What it demonstrated: The testing infrastructure failed to produce or recover any valid scenario results, demonstrating a critical breakdown in the campaign harness rather than in the ai-memory system itself.
AI NHI analysis · Claude Opus 4.7
FAIL — no scenario reports recovered, only unparseable data
This test run aimed to check if AI agents could reliably share memories across a network, but it didn't work because the system couldn't generate any usable results from the planned checks. No evidence was gathered on whether agents share memory reliably or not. It's like trying to test a car's engine but the diagnostic tool breaks first.
This run represents a complete infrastructure failure with zero valid results, elevating risk in our testing pipeline and delaying validation of ai-memory v0.6.3.1's production readiness; customer claims on agent memory sharing remain unverified from this iteration. Compared to prior runs, this introduces regression in harness reliability, necessitating immediate fixes before scaling deployments. Overall posture shifts to high caution on release timelines.
No scenarios yielded results due to 'no scenario reports recovered', with only scenario-1.json marked unparseable, likely indicating a serialization or logging bug in the harness (harness_sha: ba4d782b12937abf508ebb4b29d7e4bb16ace2c3) during the 4-node DigitalOcean setup; affected primitives unknown as no probes (S#) completed. Probable root cause is incomplete CI workflow execution, given empty ended_at timestamp and overall_pass=false. No specific failure modes in ai-memory primitives identifiable without data.
Fix harness reporting bug to ensure all scenario JSONs are parseable and recoverable before re-running the campaign.
Every scenario that produced a JSON report in this campaign, in testbook order. Click a row's scenario id to jump to its full report below. See the Every test performed page for the authoritative catalog.
| ID | Title | Result | Reason |
|---|---|---|---|
| S1 | Per-agent write + read (MCP stdio) | ? |
phase A: each agent writes 10 memories via MCP ai:alice on 134.122.13.6 !! ssh timeout (60s): root@134.122.13.6 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w1-ai:alice 'scenario1 write 1 from ai:alice' scenario1-ai:alice !! drive_agent store failed for ai:alice i=1: __TIMEOUT_60s__ !! ssh timeout (60s): root@134.122.13.6 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w2-ai:alice 'scenario1 write 2 from ai:alice' scenario1-ai:alice !! drive_agent store failed for ai:alice i=2: __TIMEOUT_60s__ !! ssh timeout (60s): root@134.122.13.6 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w3-ai:alice 'scenario1 write 3 from ai:alice' scenario1-ai:alice !! drive_agent store failed for ai:alice i=3: __TIMEOUT_60s__ !! ssh timeout (60s): root@134.122.13.6 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w4-ai:alice 'scenario1 write 4 from ai:alice' scenario1-ai:alice !! drive_agent store failed for ai:alice i=4: __TIMEOUT_60s__ ai:bob on 138.197.76.170 !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w1-ai:bob 'scenario1 write 1 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=1: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w2-ai:bob 'scenario1 write 2 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=2: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w3-ai:bob 'scenario1 write 3 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=3: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w4-ai:bob 'scenario1 write 4 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=4: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w5-ai:bob 'scenario1 write 5 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=5: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w6-ai:bob 'scenario1 write 6 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=6: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w7-ai:bob 'scenario1 write 7 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=7: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w8-ai:bob 'scenario1 write 8 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=8: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w9-ai:bob 'scenario1 write 9 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=9: __TIMEOUT_60s__ !! ssh timeout (60s): root@138.197.76.170 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w10-ai:bob 'scenario1 write 10 from ai:bob' scenario1-ai:bob !! drive_agent store failed for ai:bob i=10: __TIMEOUT_60s__ ai:charlie on 104.236.127.86 !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w1-ai:charlie 'scenario1 write 1 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=1: __TIMEOUT_60s__ !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w2-ai:charlie 'scenario1 write 2 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=2: __TIMEOUT_60s__ !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w3-ai:charlie 'scenario1 write 3 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=3: __TIMEOUT_60s__ !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w4-ai:charlie 'scenario1 write 4 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=4: __TIMEOUT_60s__ !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w5-ai:charlie 'scenario1 write 5 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=5: __TIMEOUT_60s__ !! ssh timeout (60s): root@104.236.127.86 source /etc/ai-memory-a2a/env 2>/dev/null; bash /root/drive_agent.sh store w6-ai:charlie 'scenario1 write 6 from ai:charlie' scenario1-ai:charlie !! drive_agent store failed for ai:charlie i=6: __TIMEOUT_60s__