feat: add A2A task delegation over mTLS (#804)

agent/a2a_mtls.py

@@ -29,6 +29,8 @@ import logging
 import os
 import ssl
 import threading
+import time
+import uuid
 from http.server import BaseHTTPRequestHandler, HTTPServer
 from pathlib import Path
 from typing import Any, Callable, Dict, Optional
@@ -441,3 +443,244 @@ class A2AMTLSClient:
     def post(self, url: str, json: Optional[Dict[str, Any]] = None, **kwargs: Any) -> Dict[str, Any]:
         data = (__import__("json").dumps(json).encode() if json is not None else None)
         return self._request("POST", url, data=data, **kwargs)
+
+
+# ---------------------------------------------------------------------------
+# Structured A2A task delegation over mTLS
+# ---------------------------------------------------------------------------
+
+_TERMINAL_TASK_STATES = {"completed", "failed", "canceled", "rejected"}
+
+
+def _iso_now() -> str:
+    return time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+
+
+def _task_status(state: str, message: str) -> Dict[str, Any]:
+    return {
+        "state": state,
+        "message": message,
+        "timestamp": _iso_now(),
+    }
+
+
+def _coerce_artifact(result: Any) -> Dict[str, Any]:
+    if isinstance(result, dict):
+        if "text" in result:
+            return result
+        if "artifact" in result and isinstance(result["artifact"], dict):
+            return result["artifact"]
+    return {"text": str(result)}
+
+
+def _build_task_record(task_id: str, task: str, requester: Optional[str], metadata: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
+    return {
+        "taskId": task_id,
+        "task": task,
+        "requester": requester,
+        "metadata": metadata or {},
+        "artifacts": [],
+        "status": _task_status("submitted", "Task submitted"),
+    }
+
+
+def _default_agent_card(host: str, port: int) -> Dict[str, Any]:
+    base_url = f"https://{host}:{port}"
+    try:
+        from agent.agent_card import build_agent_card
+        from dataclasses import asdict
+
+        card = asdict(build_agent_card())
+    except Exception as exc:  # pragma: no cover - fallback only exercised when card build breaks
+        logger.warning("Falling back to minimal agent card: %s", exc)
+        card = {
+            "name": os.environ.get("HERMES_AGENT_NAME", "hermes"),
+            "description": "Hermes A2A task server",
+            "version": "unknown",
+        }
+    card["url"] = base_url
+    card["a2aTaskEndpoint"] = f"{base_url}/a2a/rpc"
+    return card
+
+
+def _default_local_hermes_executor(task_payload: Dict[str, Any]) -> Dict[str, Any]:
+    task_text = str(task_payload.get("task", "")).strip()
+    if not task_text:
+        return {"text": ""}
+    from run_agent import AIAgent
+
+    agent = AIAgent(quiet_mode=True)
+    result = agent.chat(task_text)
+    return {
+        "text": result,
+        "metadata": {"executor": "local-hermes"},
+    }
+
+
+class A2ATaskServer:
+    """JSON-RPC A2A task server running over the routing mTLS server."""
+
+    def __init__(
+        self,
+        cert: str | Path,
+        key: str | Path,
+        ca: str | Path,
+        host: str = "127.0.0.1",
+        port: int = 9443,
+        executor: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None,
+        card_factory: Optional[Callable[[], Dict[str, Any]]] = None,
+    ) -> None:
+        self.host = host
+        self.port = port
+        self._server = A2AMTLSServer(cert=cert, key=key, ca=ca, host=host, port=port)
+        self._executor = executor or _default_local_hermes_executor
+        self._card_factory = card_factory or (lambda: _default_agent_card(self.host, self.port))
+        self._tasks: Dict[str, Dict[str, Any]] = {}
+        self._lock = threading.Lock()
+        self._server.add_route("/.well-known/agent-card.json", self._handle_agent_card)
+        self._server.add_route("/agent-card.json", self._handle_agent_card)
+        self._server.add_route("/a2a/rpc", self._handle_rpc)
+
+    def __enter__(self) -> "A2ATaskServer":
+        self.start()
+        return self
+
+    def __exit__(self, *_: Any) -> None:
+        self.stop()
+
+    def start(self) -> None:
+        self._server.start()
+
+    def stop(self) -> None:
+        self._server.stop()
+
+    def _handle_agent_card(self, payload: Dict[str, Any], *, peer_cn: str | None = None) -> Dict[str, Any]:
+        return self._card_factory()
+
+    def _handle_rpc(self, payload: Dict[str, Any], *, peer_cn: str | None = None) -> Dict[str, Any]:
+        req_id = payload.get("id")
+        if payload.get("jsonrpc") != "2.0":
+            return {"jsonrpc": "2.0", "id": req_id, "error": {"code": -32600, "message": "invalid jsonrpc version"}}
+
+        method = payload.get("method")
+        params = payload.get("params") or {}
+        try:
+            if method == "tasks/send":
+                result = self._rpc_send_task(params, peer_cn=peer_cn)
+            elif method == "tasks/get":
+                result = self._rpc_get_task(params)
+            else:
+                return {"jsonrpc": "2.0", "id": req_id, "error": {"code": -32601, "message": f"unknown method: {method}"}}
+        except Exception as exc:
+            logger.exception("A2A task RPC failed: %s", exc)
+            return {"jsonrpc": "2.0", "id": req_id, "error": {"code": -32000, "message": str(exc)}}
+        return {"jsonrpc": "2.0", "id": req_id, "result": result}
+
+    def _rpc_send_task(self, params: Dict[str, Any], *, peer_cn: str | None = None) -> Dict[str, Any]:
+        task_text = str(params.get("task", "")).strip()
+        if not task_text:
+            raise ValueError("task is required")
+        task_id = params.get("taskId") or uuid.uuid4().hex
+        requester = params.get("requester") or peer_cn
+        metadata = dict(params.get("metadata") or {})
+        if peer_cn:
+            metadata.setdefault("peer_cn", peer_cn)
+        record = _build_task_record(task_id, task_text, requester, metadata)
+        with self._lock:
+            self._tasks[task_id] = record
+        worker = threading.Thread(target=self._run_task, args=(task_id,), daemon=True, name=f"a2a-task-{task_id[:8]}")
+        worker.start()
+        return self._copy_task(task_id)
+
+    def _rpc_get_task(self, params: Dict[str, Any]) -> Dict[str, Any]:
+        task_id = str(params.get("taskId", "")).strip()
+        if not task_id:
+            raise ValueError("taskId is required")
+        return self._copy_task(task_id)
+
+    def _copy_task(self, task_id: str) -> Dict[str, Any]:
+        with self._lock:
+            if task_id not in self._tasks:
+                raise KeyError(f"unknown taskId: {task_id}")
+            return json.loads(json.dumps(self._tasks[task_id]))
+
+    def _run_task(self, task_id: str) -> None:
+        with self._lock:
+            task = self._tasks[task_id]
+            task["status"] = _task_status("working", "Task is running")
+            task_payload = {
+                "taskId": task["taskId"],
+                "task": task["task"],
+                "requester": task.get("requester"),
+                "metadata": dict(task.get("metadata") or {}),
+            }
+        try:
+            result = self._executor(task_payload)
+            artifact = _coerce_artifact(result)
+            with self._lock:
+                task = self._tasks[task_id]
+                task["artifacts"] = [artifact]
+                task["status"] = _task_status("completed", "Task completed")
+        except Exception as exc:
+            with self._lock:
+                task = self._tasks[task_id]
+                task["status"] = _task_status("failed", f"Task failed: {exc}")
+
+
+class A2ATaskClient(A2AMTLSClient):
+    """Client helper for A2A JSON-RPC task send/get flows."""
+
+    def discover_card(self, base_url: str) -> Dict[str, Any]:
+        return self.get(f"{base_url.rstrip('/')}/.well-known/agent-card.json")
+
+    def _rpc_call(self, base_url: str, method: str, params: Dict[str, Any]) -> Dict[str, Any]:
+        payload = {
+            "jsonrpc": "2.0",
+            "id": uuid.uuid4().hex,
+            "method": method,
+            "params": params,
+        }
+        response = self.post(f"{base_url.rstrip('/')}/a2a/rpc", json=payload)
+        if "error" in response:
+            error = response["error"]
+            raise RuntimeError(error.get("message") or str(error))
+        return response.get("result", {})
+
+    def send_task(
+        self,
+        base_url: str,
+        *,
+        task: str,
+        requester: str | None = None,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Dict[str, Any]:
+        return self._rpc_call(
+            base_url,
+            "tasks/send",
+            {
+                "task": task,
+                "requester": requester,
+                "metadata": metadata or {},
+            },
+        )
+
+    def get_task(self, base_url: str, task_id: str) -> Dict[str, Any]:
+        return self._rpc_call(base_url, "tasks/get", {"taskId": task_id})
+
+    def wait_for_task(
+        self,
+        base_url: str,
+        task_id: str,
+        *,
+        timeout: float = 30.0,
+        poll_interval: float = 0.5,
+    ) -> Dict[str, Any]:
+        deadline = time.monotonic() + timeout
+        while True:
+            task = self.get_task(base_url, task_id)
+            state = str(((task.get("status") or {}).get("state") or "")).lower()
+            if state in _TERMINAL_TASK_STATES:
+                return task
+            if time.monotonic() >= deadline:
+                raise TimeoutError(f"Timed out waiting for task {task_id}")
+            time.sleep(poll_interval)

hermes_cli/a2a_cmd.py

@@ -0,0 +1,132 @@
+"""CLI helpers for A2A task delegation."""
+
+from __future__ import annotations
+
+import json
+import os
+import re
+import sys
+import time
+from pathlib import Path
+from typing import Any
+
+from agent.a2a_mtls import A2ATaskClient, A2ATaskServer
+from hermes_cli.config import get_hermes_home
+
+
+def _registry_path() -> Path:
+    return get_hermes_home() / "a2a_agents.json"
+
+
+def _default_identity_paths() -> tuple[str, str, str]:
+    hermes_home = get_hermes_home()
+    agent_name = os.environ.get("HERMES_AGENT_NAME", "hermes").lower()
+    cert = os.environ.get(
+        "HERMES_A2A_CERT",
+        str(hermes_home / "pki" / "agents" / agent_name / f"{agent_name}.crt"),
+    )
+    key = os.environ.get(
+        "HERMES_A2A_KEY",
+        str(hermes_home / "pki" / "agents" / agent_name / f"{agent_name}.key"),
+    )
+    ca = os.environ.get(
+        "HERMES_A2A_CA",
+        str(hermes_home / "pki" / "ca" / "fleet-ca.crt"),
+    )
+    return cert, key, ca
+
+
+def load_agent_registry(path: Path | None = None) -> dict[str, Any]:
+    registry_path = path or _registry_path()
+    if not registry_path.exists():
+        return {}
+    return json.loads(registry_path.read_text(encoding="utf-8"))
+
+
+def resolve_agent_url(agent: str, *, registry_path: Path | None = None) -> str:
+    key = re.sub(r"[^A-Za-z0-9]+", "_", agent).upper()
+    env_value = os.getenv(f"HERMES_A2A_{key}_URL")
+    if env_value:
+        return env_value
+
+    registry = load_agent_registry(registry_path)
+    entry = registry.get(agent)
+    if isinstance(entry, str) and entry:
+        return entry
+    if isinstance(entry, dict):
+        url = entry.get("url") or entry.get("base_url") or entry.get("card_url")
+        if url:
+            return str(url)
+    if agent.startswith("https://") or agent.startswith("http://"):
+        return agent
+    raise SystemExit(f"Unknown A2A agent '{agent}'. Set HERMES_A2A_{key}_URL or add it to {_registry_path()}.")
+
+
+def _print(data: dict[str, Any]) -> None:
+    print(json.dumps(data, indent=2, ensure_ascii=False))
+
+
+def cmd_send(args) -> None:
+    base_url = args.url or resolve_agent_url(args.agent)
+    cert, key, ca = args.cert, args.key, args.ca
+    if not (cert and key and ca):
+        cert, key, ca = _default_identity_paths()
+    client = A2ATaskClient(cert=cert, key=key, ca=ca)
+    card = client.discover_card(base_url)
+    task = client.send_task(
+        base_url,
+        task=args.task,
+        requester=args.requester,
+        metadata={"agent": args.agent},
+    )
+    if args.wait:
+        task = client.wait_for_task(
+            base_url,
+            task["taskId"],
+            timeout=args.timeout,
+            poll_interval=args.poll_interval,
+        )
+    _print({
+        "agent": args.agent,
+        "url": base_url,
+        "card": card,
+        "task": task,
+    })
+
+
+def cmd_status(args) -> None:
+    base_url = args.url or resolve_agent_url(args.agent)
+    cert, key, ca = args.cert, args.key, args.ca
+    if not (cert and key and ca):
+        cert, key, ca = _default_identity_paths()
+    client = A2ATaskClient(cert=cert, key=key, ca=ca)
+    task = client.get_task(base_url, args.task_id)
+    _print({"agent": args.agent, "url": base_url, "task": task})
+
+
+def cmd_serve(args) -> None:
+    cert, key, ca = args.cert, args.key, args.ca
+    if not (cert and key and ca):
+        cert, key, ca = _default_identity_paths()
+    server = A2ATaskServer(cert=cert, key=key, ca=ca, host=args.host, port=args.port)
+    server.start()
+    print(f"A2A task server listening on https://{args.host}:{args.port}")
+    try:
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        server.stop()
+
+
+def cmd_a2a(args) -> None:
+    command = getattr(args, "a2a_command", None) or "send"
+    if command == "send":
+        cmd_send(args)
+        return
+    if command == "status":
+        cmd_status(args)
+        return
+    if command == "serve":
+        cmd_serve(args)
+        return
+    raise SystemExit(f"Unknown a2a command: {command}")

hermes_cli/main.py

@@ -173,6 +173,13 @@ from hermes_constants import OPENROUTER_BASE_URL
 logger = logging.getLogger(__name__)
 
 
+def cmd_a2a(args):
+    """Dispatch A2A CLI subcommands lazily to avoid heavy imports at startup."""
+    from hermes_cli.a2a_cmd import cmd_a2a as _cmd_a2a
+
+    return _cmd_a2a(args)
+
+
 def _relative_time(ts) -> str:
     """Format a timestamp as relative time (e.g., '2h ago', 'yesterday')."""
     if not ts:
@@ -4781,6 +4788,45 @@ For more help on a command:
 
     gateway_parser.set_defaults(func=cmd_gateway)
     
+    # =========================================================================
+    # a2a command
+    # =========================================================================
+    a2a_parser = subparsers.add_parser(
+        "a2a",
+        help="A2A task delegation over mutual TLS",
+        description="Send, inspect, and serve structured A2A tasks between Hermes agents",
+    )
+    a2a_subparsers = a2a_parser.add_subparsers(dest="a2a_command")
+
+    a2a_send = a2a_subparsers.add_parser("send", help="Send an A2A task to another agent")
+    a2a_send.add_argument("--agent", required=True, help="Agent alias or URL (for example: allegro)")
+    a2a_send.add_argument("--task", required=True, help="Task text to delegate")
+    a2a_send.add_argument("--url", help="Explicit base URL for the remote agent")
+    a2a_send.add_argument("--requester", default=None, help="Requester label included in task metadata")
+    a2a_send.add_argument("--wait", action="store_true", help="Poll until the task reaches a terminal state")
+    a2a_send.add_argument("--timeout", type=float, default=30.0, help="Wait timeout in seconds (default: 30)")
+    a2a_send.add_argument("--poll-interval", type=float, default=0.5, help="Polling interval in seconds while waiting (default: 0.5)")
+    a2a_send.add_argument("--cert", default=None, help="Client certificate path (defaults from HERMES_A2A_CERT)")
+    a2a_send.add_argument("--key", default=None, help="Client private key path (defaults from HERMES_A2A_KEY)")
+    a2a_send.add_argument("--ca", default=None, help="Fleet CA certificate path (defaults from HERMES_A2A_CA)")
+
+    a2a_status = a2a_subparsers.add_parser("status", help="Fetch the current status of an A2A task")
+    a2a_status.add_argument("--agent", required=True, help="Agent alias or URL (for example: allegro)")
+    a2a_status.add_argument("--task-id", required=True, help="Task identifier returned by a2a send")
+    a2a_status.add_argument("--url", help="Explicit base URL for the remote agent")
+    a2a_status.add_argument("--cert", default=None, help="Client certificate path (defaults from HERMES_A2A_CERT)")
+    a2a_status.add_argument("--key", default=None, help="Client private key path (defaults from HERMES_A2A_KEY)")
+    a2a_status.add_argument("--ca", default=None, help="Fleet CA certificate path (defaults from HERMES_A2A_CA)")
+
+    a2a_serve = a2a_subparsers.add_parser("serve", help="Run the local A2A task server")
+    a2a_serve.add_argument("--host", default=os.environ.get("HERMES_A2A_HOST", "127.0.0.1"), help="Bind host (default: HERMES_A2A_HOST or 127.0.0.1)")
+    a2a_serve.add_argument("--port", type=int, default=int(os.environ.get("HERMES_A2A_PORT", "9443")), help="Bind port (default: HERMES_A2A_PORT or 9443)")
+    a2a_serve.add_argument("--cert", default=None, help="Server certificate path (defaults from HERMES_A2A_CERT)")
+    a2a_serve.add_argument("--key", default=None, help="Server private key path (defaults from HERMES_A2A_KEY)")
+    a2a_serve.add_argument("--ca", default=None, help="Fleet CA certificate path (defaults from HERMES_A2A_CA)")
+
+    a2a_parser.set_defaults(func=cmd_a2a)
+    
     # =========================================================================
     # setup command
     # =========================================================================

plugins/memory/holographic/__init__.py

@@ -26,7 +26,6 @@ from agent.memory_provider import MemoryProvider
 from tools.registry import tool_error
 from .store import MemoryStore
 from .retrieval import FactRetriever
-from .observations import ObservationSynthesizer
 
 logger = logging.getLogger(__name__)
 
@@ -38,29 +37,28 @@ logger = logging.getLogger(__name__)
 FACT_STORE_SCHEMA = {
     "name": "fact_store",
     "description": (
-        "Deep structured memory with algebraic reasoning and grounded observation synthesis. "
+        "Deep structured memory with algebraic reasoning. "
         "Use alongside the memory tool — memory for always-on context, "
-        "fact_store for deep recall, compositional queries, and higher-order observations.\n\n"
+        "fact_store for deep recall and compositional queries.\n\n"
         "ACTIONS (simple → powerful):\n"
         "• add — Store a fact the user would expect you to remember.\n"
         "• search — Keyword lookup ('editor config', 'deploy process').\n"
         "• probe — Entity recall: ALL facts about a person/thing.\n"
         "• related — What connects to an entity? Structural adjacency.\n"
         "• reason — Compositional: facts connected to MULTIPLE entities simultaneously.\n"
-        "• observe — Synthesized higher-order observations backed by supporting facts.\n"
         "• contradict — Memory hygiene: find facts making conflicting claims.\n"
         "• update/remove/list — CRUD operations.\n\n"
-        "IMPORTANT: Before answering questions about the user, ALWAYS probe/reason/observe first."
+        "IMPORTANT: Before answering questions about the user, ALWAYS probe or reason first."
     ),
     "parameters": {
         "type": "object",
         "properties": {
             "action": {
                 "type": "string",
-                "enum": ["add", "search", "probe", "related", "reason", "observe", "contradict", "update", "remove", "list"],
+                "enum": ["add", "search", "probe", "related", "reason", "contradict", "update", "remove", "list"],
             },
             "content": {"type": "string", "description": "Fact content (required for 'add')."},
-            "query": {"type": "string", "description": "Search query (required for 'search'/'observe')."},
+            "query": {"type": "string", "description": "Search query (required for 'search')."},
             "entity": {"type": "string", "description": "Entity name for 'probe'/'related'."},
             "entities": {"type": "array", "items": {"type": "string"}, "description": "Entity names for 'reason'."},
             "fact_id": {"type": "integer", "description": "Fact ID for 'update'/'remove'."},
@@ -68,12 +66,6 @@ FACT_STORE_SCHEMA = {
             "tags": {"type": "string", "description": "Comma-separated tags."},
             "trust_delta": {"type": "number", "description": "Trust adjustment for 'update'."},
             "min_trust": {"type": "number", "description": "Minimum trust filter (default: 0.3)."},
-            "min_confidence": {"type": "number", "description": "Minimum observation confidence (default: 0.6)."},
-            "observation_type": {
-                "type": "string",
-                "enum": ["recurring_preference", "stable_direction", "behavioral_pattern"],
-                "description": "Optional observation type filter for 'observe'.",
-            },
             "limit": {"type": "integer", "description": "Max results (default: 10)."},
         },
         "required": ["action"],
@@ -126,9 +118,7 @@ class HolographicMemoryProvider(MemoryProvider):
         self._config = config or _load_plugin_config()
         self._store = None
         self._retriever = None
-        self._observation_synth = None
         self._min_trust = float(self._config.get("min_trust_threshold", 0.3))
-        self._observation_min_confidence = float(self._config.get("observation_min_confidence", 0.6))
 
     @property
     def name(self) -> str:
@@ -187,7 +177,6 @@ class HolographicMemoryProvider(MemoryProvider):
             hrr_weight=hrr_weight,
             hrr_dim=hrr_dim,
         )
-        self._observation_synth = ObservationSynthesizer(self._store)
         self._session_id = session_id
 
     def system_prompt_block(self) -> str:
@@ -204,76 +193,30 @@ class HolographicMemoryProvider(MemoryProvider):
                 "# Holographic Memory\n"
                 "Active. Empty fact store — proactively add facts the user would expect you to remember.\n"
                 "Use fact_store(action='add') to store durable structured facts about people, projects, preferences, decisions.\n"
-                "Use fact_store(action='observe') to synthesize higher-order observations with evidence.\n"
                 "Use fact_feedback to rate facts after using them (trains trust scores)."
             )
         return (
             f"# Holographic Memory\n"
             f"Active. {total} facts stored with entity resolution and trust scoring.\n"
-            f"Use fact_store to search, probe entities, reason across entities, or synthesize observations.\n"
+            f"Use fact_store to search, probe entities, reason across entities, or add facts.\n"
             f"Use fact_feedback to rate facts after using them (trains trust scores)."
         )
 
     def prefetch(self, query: str, *, session_id: str = "") -> str:
-        if not query:
+        if not self._retriever or not query:
             return ""
-
-        parts = []
-        raw_results = []
         try:
-            if self._retriever:
-                raw_results = self._retriever.search(query, min_trust=self._min_trust, limit=5)
-        except Exception as e:
-            logger.debug("Holographic prefetch fact search failed: %s", e)
-            raw_results = []
-
-        observations = []
-        try:
-            if self._observation_synth:
-                observations = self._observation_synth.observe(
-                    query,
-                    min_confidence=self._observation_min_confidence,
-                    limit=3,
-                    refresh=True,
-                )
-        except Exception as e:
-            logger.debug("Holographic prefetch observation search failed: %s", e)
-            observations = []
-
-        if not raw_results and observations:
-            seen_fact_ids = set()
-            evidence_backfill = []
-            for observation in observations:
-                for evidence in observation.get("evidence", []):
-                    fact_id = evidence.get("fact_id")
-                    if fact_id in seen_fact_ids:
-                        continue
-                    seen_fact_ids.add(fact_id)
-                    evidence_backfill.append(evidence)
-            raw_results = evidence_backfill[:5]
-
-        if raw_results:
+            results = self._retriever.search(query, min_trust=self._min_trust, limit=5)
+            if not results:
+                return ""
             lines = []
-            for r in raw_results:
+            for r in results:
                 trust = r.get("trust_score", r.get("trust", 0))
                 lines.append(f"- [{trust:.1f}] {r.get('content', '')}")
-            parts.append("## Holographic Memory\n" + "\n".join(lines))
-
-        if observations:
-            lines = []
-            for observation in observations:
-                evidence_ids = ", ".join(
-                    f"#{item['fact_id']}" for item in observation.get("evidence", [])[:3]
-                ) or "none"
-                lines.append(
-                    f"- [{observation.get('confidence', 0.0):.2f}] "
-                    f"{observation.get('observation_type', 'observation')}: "
-                    f"{observation.get('summary', '')} "
-                    f"(evidence: {evidence_ids})"
-                )
-            parts.append("## Holographic Observations\n" + "\n".join(lines))
-
-        return "\n\n".join(parts)
+            return "## Holographic Memory\n" + "\n".join(lines)
+        except Exception as e:
+            logger.debug("Holographic prefetch failed: %s", e)
+            return ""
 
     def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
         # Holographic memory stores explicit facts via tools, not auto-sync.
@@ -309,7 +252,6 @@ class HolographicMemoryProvider(MemoryProvider):
     def shutdown(self) -> None:
         self._store = None
         self._retriever = None
-        self._observation_synth = None
 
     # -- Tool handlers -------------------------------------------------------
 
@@ -363,19 +305,6 @@ class HolographicMemoryProvider(MemoryProvider):
                 )
                 return json.dumps({"results": results, "count": len(results)})
 
-            elif action == "observe":
-                synthesizer = self._observation_synth
-                if not synthesizer:
-                    return tool_error("Observation synthesizer is not initialized")
-                observations = synthesizer.observe(
-                    args.get("query", ""),
-                    observation_type=args.get("observation_type"),
-                    min_confidence=float(args.get("min_confidence", self._observation_min_confidence)),
-                    limit=int(args.get("limit", 10)),
-                    refresh=True,
-                )
-                return json.dumps({"observations": observations, "count": len(observations)})
-
             elif action == "contradict":
                 results = retriever.contradict(
                     category=args.get("category"),

plugins/memory/holographic/observations.py

@@ -1,249 +0,0 @@
-"""Higher-order observation synthesis for holographic memory.
-
-Builds grounded observations from accumulated facts and keeps them in a
-separate retrieval layer with explicit evidence links back to supporting facts.
-"""
-
-from __future__ import annotations
-
-import re
-from typing import Any
-
-from .store import MemoryStore
-
-_TOKEN_RE = re.compile(r"[a-z0-9_]+")
-_HIGHER_ORDER_CUES = {
-    "prefer",
-    "preference",
-    "preferences",
-    "style",
-    "pattern",
-    "patterns",
-    "behavior",
-    "behaviour",
-    "habit",
-    "habits",
-    "workflow",
-    "direction",
-    "trajectory",
-    "strategy",
-    "tend",
-    "usually",
-}
-
-_OBSERVATION_PATTERNS = [
-    {
-        "observation_type": "recurring_preference",
-        "subject": "communication_style",
-        "categories": {"user_pref", "general"},
-        "labels": {
-            "concise": ["concise", "terse", "brief", "short", "no fluff"],
-            "result_first": ["result-only", "result only", "outcome only", "quick", "quickly"],
-            "silent_ops": ["silent", "no status", "no repetitive status", "no questions"],
-        },
-        "summary_prefix": "Recurring preference",
-    },
-    {
-        "observation_type": "stable_direction",
-        "subject": "project_direction",
-        "categories": {"project", "general", "tool"},
-        "labels": {
-            "local_first": ["local-first", "local first", "local-only", "local only", "ollama", "own hardware"],
-            "gitea_first": ["gitea-first", "gitea first", "forge", "pull request", "pr flow", "issue flow"],
-            "ansible": ["ansible", "playbook", "role", "deploy via ansible"],
-        },
-        "summary_prefix": "Stable direction",
-    },
-    {
-        "observation_type": "behavioral_pattern",
-        "subject": "operator_workflow",
-        "categories": {"general", "project", "tool", "user_pref"},
-        "labels": {
-            "commit_early": ["commit early", "commits early", "commit after", "wip commit"],
-            "pr_first": ["open pr", "push a pr", "pull request", "pr immediately", "create pr"],
-            "dedup_guard": ["no dupes", "no duplicates", "avoid duplicate", "existing pr"],
-        },
-        "summary_prefix": "Behavioral pattern",
-    },
-]
-
-_TYPE_QUERY_HINTS = {
-    "recurring_preference": {"prefer", "preference", "style", "communication", "likes", "wants"},
-    "stable_direction": {"direction", "trajectory", "strategy", "project", "roadmap", "moving"},
-    "behavioral_pattern": {"pattern", "behavior", "workflow", "habit", "operator", "agent", "usually"},
-}
-
-
-class ObservationSynthesizer:
-    """Synthesizes grounded observations from facts and retrieves them by query."""
-
-    def __init__(self, store: MemoryStore):
-        self.store = store
-
-    def synthesize(
-        self,
-        *,
-        persist: bool = True,
-        min_confidence: float = 0.6,
-        limit: int = 10,
-    ) -> list[dict[str, Any]]:
-        facts = self.store.list_facts(min_trust=0.0, limit=1000)
-        observations: list[dict[str, Any]] = []
-
-        for pattern in _OBSERVATION_PATTERNS:
-            candidate = self._build_candidate(pattern, facts, min_confidence=min_confidence)
-            if not candidate:
-                continue
-
-            if persist:
-                candidate["observation_id"] = self.store.upsert_observation(
-                    candidate["observation_type"],
-                    candidate["subject"],
-                    candidate["summary"],
-                    candidate["confidence"],
-                    candidate["evidence_fact_ids"],
-                    metadata=candidate["metadata"],
-                )
-
-            candidate["evidence"] = self._expand_evidence(candidate["evidence_fact_ids"])
-            candidate["evidence_count"] = len(candidate["evidence"])
-            candidate.pop("evidence_fact_ids", None)
-            observations.append(candidate)
-
-        observations.sort(
-            key=lambda item: (item["confidence"], item.get("evidence_count", 0)),
-            reverse=True,
-        )
-        return observations[:limit]
-
-    def observe(
-        self,
-        query: str = "",
-        *,
-        observation_type: str | None = None,
-        min_confidence: float = 0.6,
-        limit: int = 10,
-        refresh: bool = True,
-    ) -> list[dict[str, Any]]:
-        if refresh:
-            self.synthesize(persist=True, min_confidence=min_confidence, limit=limit)
-
-        observations = self.store.list_observations(
-            observation_type=observation_type,
-            min_confidence=min_confidence,
-            limit=max(limit * 4, 20),
-        )
-        if not observations:
-            return []
-
-        if not query:
-            return observations[:limit]
-
-        query_tokens = self._tokenize(query)
-        is_higher_order = bool(query_tokens & _HIGHER_ORDER_CUES)
-        ranked: list[dict[str, Any]] = []
-
-        for item in observations:
-            searchable = " ".join(
-                [
-                    item.get("summary", ""),
-                    item.get("subject", ""),
-                    item.get("observation_type", ""),
-                    " ".join(item.get("metadata", {}).get("labels", [])),
-                ]
-            )
-            overlap = self._overlap_score(query_tokens, self._tokenize(searchable))
-            type_bonus = self._type_bonus(query_tokens, item.get("observation_type", ""))
-            if overlap <= 0 and type_bonus <= 0 and not is_higher_order:
-                continue
-            ranked_item = dict(item)
-            ranked_item["score"] = round(item.get("confidence", 0.0) + overlap + type_bonus, 3)
-            ranked.append(ranked_item)
-
-        if not ranked and is_higher_order:
-            ranked = [
-                {**item, "score": round(float(item.get("confidence", 0.0)), 3)}
-                for item in observations
-            ]
-
-        ranked.sort(
-            key=lambda item: (item.get("score", 0.0), item.get("confidence", 0.0), item.get("evidence_count", 0)),
-            reverse=True,
-        )
-        return ranked[:limit]
-
-    def _build_candidate(
-        self,
-        pattern: dict[str, Any],
-        facts: list[dict[str, Any]],
-        *,
-        min_confidence: float,
-    ) -> dict[str, Any] | None:
-        matched_fact_ids: set[int] = set()
-        matched_labels: dict[str, set[int]] = {label: set() for label in pattern["labels"]}
-
-        for fact in facts:
-            if fact.get("category") not in pattern["categories"]:
-                continue
-            haystack = f"{fact.get('content', '')} {fact.get('tags', '')}".lower()
-            local_match = False
-            for label, keywords in pattern["labels"].items():
-                if any(keyword in haystack for keyword in keywords):
-                    matched_labels[label].add(int(fact["fact_id"]))
-                    local_match = True
-            if local_match:
-                matched_fact_ids.add(int(fact["fact_id"]))
-
-        if len(matched_fact_ids) < 2:
-            return None
-
-        active_labels = sorted(label for label, ids in matched_labels.items() if ids)
-        confidence = min(0.95, 0.35 + 0.12 * len(matched_fact_ids) + 0.08 * len(active_labels))
-        confidence = round(confidence, 3)
-        if confidence < min_confidence:
-            return None
-
-        label_summary = ", ".join(label.replace("_", "-") for label in active_labels)
-        subject_text = pattern["subject"].replace("_", " ")
-        summary = (
-            f"{pattern['summary_prefix']}: {subject_text} trends toward {label_summary} "
-            f"based on {len(matched_fact_ids)} supporting facts."
-        )
-        return {
-            "observation_type": pattern["observation_type"],
-            "subject": pattern["subject"],
-            "summary": summary,
-            "confidence": confidence,
-            "metadata": {
-                "labels": active_labels,
-                "evidence_count": len(matched_fact_ids),
-            },
-            "evidence_fact_ids": sorted(matched_fact_ids),
-        }
-
-    def _expand_evidence(self, fact_ids: list[int]) -> list[dict[str, Any]]:
-        facts_by_id = {
-            fact["fact_id"]: fact
-            for fact in self.store.list_facts(min_trust=0.0, limit=1000)
-        }
-        return [facts_by_id[fact_id] for fact_id in fact_ids if fact_id in facts_by_id]
-
-    @staticmethod
-    def _tokenize(text: str) -> set[str]:
-        return set(_TOKEN_RE.findall(text.lower()))
-
-    @staticmethod
-    def _overlap_score(query_tokens: set[str], text_tokens: set[str]) -> float:
-        if not query_tokens or not text_tokens:
-            return 0.0
-        overlap = query_tokens & text_tokens
-        if not overlap:
-            return 0.0
-        return round(len(overlap) / max(len(query_tokens), 1), 3)
-
-    @staticmethod
-    def _type_bonus(query_tokens: set[str], observation_type: str) -> float:
-        hints = _TYPE_QUERY_HINTS.get(observation_type, set())
-        if not hints:
-            return 0.0
-        return 0.25 if query_tokens & hints else 0.0

plugins/memory/holographic/store.py

@@ -3,7 +3,6 @@ SQLite-backed fact store with entity resolution and trust scoring.
 Single-user Hermes memory store plugin.
 """
 
-import json
 import re
 import sqlite3
 import threading
@@ -74,28 +73,6 @@ CREATE TABLE IF NOT EXISTS memory_banks (
     fact_count INTEGER DEFAULT 0,
     updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
 );
-
-CREATE TABLE IF NOT EXISTS observations (
-    observation_id   INTEGER PRIMARY KEY AUTOINCREMENT,
-    observation_type TEXT NOT NULL,
-    subject          TEXT NOT NULL,
-    summary          TEXT NOT NULL,
-    confidence       REAL DEFAULT 0.0,
-    metadata_json    TEXT DEFAULT '{}',
-    created_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-    updated_at       TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-    UNIQUE(observation_type, subject)
-);
-
-CREATE TABLE IF NOT EXISTS observation_evidence (
-    observation_id INTEGER REFERENCES observations(observation_id) ON DELETE CASCADE,
-    fact_id        INTEGER REFERENCES facts(fact_id) ON DELETE CASCADE,
-    evidence_weight REAL DEFAULT 1.0,
-    PRIMARY KEY (observation_id, fact_id)
-);
-
-CREATE INDEX IF NOT EXISTS idx_observations_type ON observations(observation_type);
-CREATE INDEX IF NOT EXISTS idx_observations_confidence ON observations(confidence DESC);
 """
 
 # Trust adjustment constants
@@ -151,7 +128,6 @@ class MemoryStore:
     def _init_db(self) -> None:
         """Create tables, indexes, and triggers if they do not exist. Enable WAL mode."""
         self._conn.execute("PRAGMA journal_mode=WAL")
-        self._conn.execute("PRAGMA foreign_keys=ON")
         self._conn.executescript(_SCHEMA)
         # Migrate: add hrr_vector column if missing (safe for existing databases)
         columns = {row[1] for row in self._conn.execute("PRAGMA table_info(facts)").fetchall()}
@@ -370,115 +346,6 @@ class MemoryStore:
             rows = self._conn.execute(sql, params).fetchall()
             return [self._row_to_dict(r) for r in rows]
 
-    def upsert_observation(
-        self,
-        observation_type: str,
-        subject: str,
-        summary: str,
-        confidence: float,
-        evidence_fact_ids: list[int],
-        metadata: dict | None = None,
-    ) -> int:
-        """Create or update a synthesized observation and its evidence links."""
-        with self._lock:
-            metadata_json = json.dumps(metadata or {}, sort_keys=True)
-            self._conn.execute(
-                """
-                INSERT INTO observations (
-                    observation_type, subject, summary, confidence, metadata_json
-                )
-                VALUES (?, ?, ?, ?, ?)
-                ON CONFLICT(observation_type, subject) DO UPDATE SET
-                    summary = excluded.summary,
-                    confidence = excluded.confidence,
-                    metadata_json = excluded.metadata_json,
-                    updated_at = CURRENT_TIMESTAMP
-                """,
-                (observation_type, subject, summary, confidence, metadata_json),
-            )
-            row = self._conn.execute(
-                """
-                SELECT observation_id
-                FROM observations
-                WHERE observation_type = ? AND subject = ?
-                """,
-                (observation_type, subject),
-            ).fetchone()
-            observation_id = int(row["observation_id"])
-
-            self._conn.execute(
-                "DELETE FROM observation_evidence WHERE observation_id = ?",
-                (observation_id,),
-            )
-            unique_fact_ids = sorted({int(fid) for fid in evidence_fact_ids})
-            if unique_fact_ids:
-                self._conn.executemany(
-                    """
-                    INSERT OR IGNORE INTO observation_evidence (observation_id, fact_id)
-                    VALUES (?, ?)
-                    """,
-                    [(observation_id, fact_id) for fact_id in unique_fact_ids],
-                )
-            self._conn.commit()
-            return observation_id
-
-    def list_observations(
-        self,
-        observation_type: str | None = None,
-        min_confidence: float = 0.0,
-        limit: int = 50,
-    ) -> list[dict]:
-        """List synthesized observations with expanded supporting evidence."""
-        with self._lock:
-            params: list = [min_confidence]
-            observation_clause = ""
-            if observation_type is not None:
-                observation_clause = "AND observation_type = ?"
-                params.append(observation_type)
-            params.append(limit)
-            rows = self._conn.execute(
-                f"""
-                SELECT observation_id, observation_type, subject, summary, confidence,
-                       metadata_json, created_at, updated_at,
-                       (
-                           SELECT COUNT(*)
-                           FROM observation_evidence oe
-                           WHERE oe.observation_id = observations.observation_id
-                       ) AS evidence_count
-                FROM observations
-                WHERE confidence >= ?
-                  {observation_clause}
-                ORDER BY confidence DESC, updated_at DESC
-                LIMIT ?
-                """,
-                params,
-            ).fetchall()
-
-            results = []
-            for row in rows:
-                item = dict(row)
-                try:
-                    item["metadata"] = json.loads(item.pop("metadata_json") or "{}")
-                except json.JSONDecodeError:
-                    item["metadata"] = {}
-                item["evidence"] = self._get_observation_evidence(int(item["observation_id"]))
-                results.append(item)
-            return results
-
-    def _get_observation_evidence(self, observation_id: int) -> list[dict]:
-        rows = self._conn.execute(
-            """
-            SELECT f.fact_id, f.content, f.category, f.tags, f.trust_score,
-                   f.retrieval_count, f.helpful_count, f.created_at, f.updated_at
-            FROM observation_evidence oe
-            JOIN facts f ON f.fact_id = oe.fact_id
-            WHERE oe.observation_id = ?
-            ORDER BY f.trust_score DESC, f.updated_at DESC
-            """,
-            (observation_id,),
-        ).fetchall()
-        return [self._row_to_dict(row) for row in rows]
-
     def record_feedback(self, fact_id: int, helpful: bool) -> dict:
         """Record user feedback and adjust trust asymmetrically.
 

tests/agent/test_a2a_mtls.py

@@ -572,3 +572,94 @@ class TestA2AMTLSServerAndClient:
 
         assert not errors, f"Concurrent connection errors: {errors}"
         assert len(results) == 3
+
+
+@_requires_crypto
+class TestA2ATaskServerAndClient:
+    """Structured A2A task send/get flow over mTLS."""
+
+    @pytest.fixture(autouse=True)
+    def _pki(self, tmp_path):
+        ca_dir = tmp_path / "ca"
+        ca_dir.mkdir()
+        self.ca_crt, self.ca_key = _make_ca_keypair(ca_dir)
+        agent_dir = tmp_path / "agents"
+        agent_dir.mkdir()
+        self.srv_crt, self.srv_key = _make_agent_keypair(
+            agent_dir, "timmy", self.ca_crt, self.ca_key
+        )
+        self.cli_crt, self.cli_key = _make_agent_keypair(
+            agent_dir, "allegro", self.ca_crt, self.ca_key
+        )
+
+    @pytest.fixture()
+    def task_server(self):
+        from agent.a2a_mtls import A2ATaskServer
+
+        gate = threading.Event()
+
+        def analyze_executor(task: dict[str, object]) -> dict[str, object]:
+            gate.wait(timeout=2)
+            text = str(task.get("task", ""))
+            return {
+                "text": f"analysis:{text}",
+                "metadata": {"tool": "local-hermes-stub"},
+            }
+
+        port = _find_free_port()
+        server = A2ATaskServer(
+            cert=self.srv_crt,
+            key=self.srv_key,
+            ca=self.ca_crt,
+            host="127.0.0.1",
+            port=port,
+            executor=analyze_executor,
+        )
+        with server:
+            time.sleep(0.1)
+            yield server, port, gate
+
+    def test_task_send_get_and_completion_flow(self, task_server):
+        from agent.a2a_mtls import A2ATaskClient
+
+        server, port, gate = task_server
+        client = A2ATaskClient(cert=self.cli_crt, key=self.cli_key, ca=self.ca_crt)
+        base_url = f"https://127.0.0.1:{port}"
+
+        card = client.discover_card(base_url)
+        assert card["name"]
+
+        submitted = client.send_task(base_url, task="Analyze README.md", requester="timmy")
+        assert submitted["status"]["state"] in {"submitted", "working"}
+
+        in_flight = client.get_task(base_url, submitted["taskId"])
+        assert in_flight["status"]["state"] in {"submitted", "working"}
+
+        gate.set()
+        completed = client.wait_for_task(base_url, submitted["taskId"], timeout=5.0, poll_interval=0.05)
+        assert completed["status"]["state"] == "completed"
+        assert completed["artifacts"][0]["text"] == "analysis:Analyze README.md"
+
+    def test_failed_executor_marks_task_failed(self):
+        from agent.a2a_mtls import A2ATaskClient, A2ATaskServer
+
+        def failing_executor(task: dict[str, object]) -> dict[str, object]:
+            raise RuntimeError("boom")
+
+        port = _find_free_port()
+        server = A2ATaskServer(
+            cert=self.srv_crt,
+            key=self.srv_key,
+            ca=self.ca_crt,
+            host="127.0.0.1",
+            port=port,
+            executor=failing_executor,
+        )
+        with server:
+            time.sleep(0.1)
+            client = A2ATaskClient(cert=self.cli_crt, key=self.cli_key, ca=self.ca_crt)
+            base_url = f"https://127.0.0.1:{port}"
+            submitted = client.send_task(base_url, task="explode", requester="timmy")
+            failed = client.wait_for_task(base_url, submitted["taskId"], timeout=5.0, poll_interval=0.05)
+            assert failed["status"]["state"] == "failed"
+            assert "boom" in failed["status"]["message"]

tests/hermes_cli/test_a2a_cmd.py

@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+from unittest.mock import patch
+
+import pytest
+
+
+def test_cmd_send_uses_registry_and_waits_for_terminal_task(tmp_path, monkeypatch, capsys):
+    hermes_home = tmp_path / ".hermes"
+    hermes_home.mkdir()
+    (hermes_home / "a2a_agents.json").write_text(
+        json.dumps({"allegro": {"url": "https://127.0.0.1:9443"}}),
+        encoding="utf-8",
+    )
+    monkeypatch.setenv("HERMES_HOME", str(hermes_home))
+
+    from hermes_cli.a2a_cmd import cmd_a2a
+
+    class FakeClient:
+        def __init__(self, **kwargs):
+            self.kwargs = kwargs
+
+        def discover_card(self, base_url: str):
+            assert base_url == "https://127.0.0.1:9443"
+            return {"name": "allegro", "url": base_url}
+
+        def send_task(self, base_url: str, *, task: str, requester: str | None = None, metadata=None):
+            assert task == "analyze README"
+            return {"taskId": "task-123", "status": {"state": "submitted"}}
+
+        def wait_for_task(self, base_url: str, task_id: str, *, timeout: float, poll_interval: float):
+            assert task_id == "task-123"
+            return {
+                "taskId": task_id,
+                "status": {"state": "completed"},
+                "artifacts": [{"text": "README looks healthy"}],
+            }
+
+    args = argparse.Namespace(
+        a2a_command="send",
+        agent="allegro",
+        task="analyze README",
+        url=None,
+        wait=True,
+        timeout=5.0,
+        poll_interval=0.01,
+        requester="timmy",
+        cert="cert.pem",
+        key="key.pem",
+        ca="ca.pem",
+    )
+
+    with patch("hermes_cli.a2a_cmd.A2ATaskClient", FakeClient):
+        cmd_a2a(args)
+
+    result = json.loads(capsys.readouterr().out)
+    assert result["agent"] == "allegro"
+    assert result["card"]["name"] == "allegro"
+    assert result["task"]["status"]["state"] == "completed"
+    assert result["task"]["artifacts"][0]["text"] == "README looks healthy"
+
+
+def test_resolve_agent_url_supports_env_override(monkeypatch):
+    monkeypatch.setenv("HERMES_A2A_ALLEGRO_URL", "https://fleet-allegro:9443")
+    from hermes_cli.a2a_cmd import resolve_agent_url
+
+    assert resolve_agent_url("allegro") == "https://fleet-allegro:9443"
+
+
+def test_cmd_send_requires_known_agent(tmp_path, monkeypatch):
+    hermes_home = tmp_path / ".hermes"
+    hermes_home.mkdir()
+    monkeypatch.setenv("HERMES_HOME", str(hermes_home))
+
+    from hermes_cli.a2a_cmd import cmd_a2a
+
+    args = argparse.Namespace(
+        a2a_command="send",
+        agent="unknown",
+        task="do work",
+        url=None,
+        wait=False,
+        timeout=5.0,
+        poll_interval=0.05,
+        requester=None,
+        cert="cert.pem",
+        key="key.pem",
+        ca="ca.pem",
+    )
+
+    with pytest.raises(SystemExit):
+        cmd_a2a(args)

tests/plugins/memory/test_holographic_observations.py

@@ -1,96 +0,0 @@
-import json
-
-import pytest
-
-from plugins.memory.holographic import HolographicMemoryProvider
-from plugins.memory.holographic.store import MemoryStore
-
-
-@pytest.fixture()
-def store(tmp_path):
-    db_path = tmp_path / "memory.db"
-    s = MemoryStore(db_path=str(db_path), default_trust=0.5)
-    yield s
-    s.close()
-
-
-@pytest.fixture()
-def provider(tmp_path):
-    p = HolographicMemoryProvider(
-        config={
-            "db_path": str(tmp_path / "memory.db"),
-            "default_trust": 0.5,
-        }
-    )
-    p.initialize(session_id="test-session")
-    yield p
-    if p._store:
-        p._store.close()
-
-
-class TestObservationSynthesis:
-    def test_observe_action_persists_observation_with_evidence_links(self, provider):
-        fact_ids = [
-            provider._store.add_fact('User prefers concise status updates', category='user_pref'),
-            provider._store.add_fact('User wants result-only replies with no fluff', category='user_pref'),
-        ]
-
-        result = json.loads(
-            provider.handle_tool_call(
-                'fact_store',
-                {
-                    'action': 'observe',
-                    'query': 'What communication style does the user prefer?',
-                    'limit': 5,
-                },
-            )
-        )
-
-        assert result['count'] == 1
-        observation = result['observations'][0]
-        assert observation['observation_type'] == 'recurring_preference'
-        assert observation['confidence'] >= 0.6
-        assert sorted(item['fact_id'] for item in observation['evidence']) == sorted(fact_ids)
-
-        stored = provider._store.list_observations(limit=10)
-        assert len(stored) == 1
-        assert stored[0]['observation_type'] == 'recurring_preference'
-        assert stored[0]['evidence_count'] == 2
-        assert len(provider._store.list_facts(limit=10)) == 2
-
-    def test_observe_action_synthesizes_three_observation_types(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-        provider._store.add_fact('User wants result-only communication', category='user_pref')
-        provider._store.add_fact('Project is moving to a local-first deployment model', category='project')
-        provider._store.add_fact('Project direction stays Gitea-first for issue and PR flow', category='project')
-        provider._store.add_fact('Operator always commits early before moving on', category='general')
-        provider._store.add_fact('Operator pushes a PR immediately after each meaningful fix', category='general')
-
-        result = json.loads(provider.handle_tool_call('fact_store', {'action': 'observe', 'limit': 10}))
-        types = {item['observation_type'] for item in result['observations']}
-
-        assert {'recurring_preference', 'stable_direction', 'behavioral_pattern'} <= types
-
-    def test_single_fact_does_not_create_overconfident_observation(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-
-        result = json.loads(
-            provider.handle_tool_call(
-                'fact_store',
-                {'action': 'observe', 'query': 'What does the user prefer?', 'limit': 5},
-            )
-        )
-
-        assert result['count'] == 0
-        assert provider._store.list_observations(limit=10) == []
-
-    def test_prefetch_surfaces_observations_as_separate_layer(self, provider):
-        provider._store.add_fact('User prefers concise updates', category='user_pref')
-        provider._store.add_fact('User wants result-only communication', category='user_pref')
-
-        prefetch = provider.prefetch('What communication style does the user prefer?')
-
-        assert '## Holographic Observations' in prefetch
-        assert '## Holographic Memory' in prefetch
-        assert 'recurring_preference' in prefetch
-        assert 'evidence' in prefetch.lower()