feat(agents): manifest plumbing + GET /agents/registry (ADR-0014 step 3)

Each agent now exports a module-level MANIFEST declaring id, version,
pref_schema, required_consents, ttl_sec, and silenced_in_contexts. The
registry surfaces both the agent and its manifest, and rejects on
mismatch so the two cannot drift.

ml/serving exposes GET /agents/registry; services/api proxies it as
GET /api/agents/registry with a 60s in-process cache so admin pageviews
don't hammer upstream. Failures aren't cached.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ml/agents/manifest.py

@@ -0,0 +1,70 @@
+"""Agent manifest dataclass (ADR-0014).
+
+A manifest is the single point of registration for an agent. The orchestrator,
+admin UI, registry endpoint, and inference framework all read from it. Adding
+an agent is adding a manifest + agent class — never editing a list elsewhere.
+
+The manifest lives next to the agent code (each agent module in ml/agents/
+exposes a module-level `MANIFEST` constant). The registry surfaces both the
+agent instance and its manifest.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any, Callable
+
+
+@dataclass(frozen=True)
+class InferredParam:
+    """One auto-inferred preference key (#111-#116).
+
+    The inference framework owns scheduling, history reads, persistence, and
+    cold-start. Each agent's `inferred_params` list declares what to infer and
+    how, leaving each agent to implement just `infer()`.
+    """
+    key: str                                  # e.g. 'quietStart'
+    ttl_sec: int                              # how often to recompute
+    cold_start_default: Any                   # value used until min_history is met
+    min_history: int                          # event count threshold
+    # Pure function: given a UserHistory snapshot, return the inferred value.
+    # Typed as a generic callable here; concrete signature lives in the framework.
+    infer: Callable[[Any], Any] | None = None
+
+
+@dataclass(frozen=True)
+class AgentManifest:
+    """Declarative description of an agent — see ADR-0014 §1."""
+    id: str                                   # 'time-of-day'
+    version: str                              # bump invalidates cached outputs + inferences
+    description: str                          # one-line human summary for admin UI
+    pref_schema: dict                         # JSON Schema for user-tunable knobs
+    context_schema: list[str]                 # signals it reads, e.g. ['todoist.tasks']
+    required_consents: list[str]              # ['data:todoist', 'agent:time-of-day']
+    output_contract: dict                     # snippet shape (free text + optional tags)
+    ttl_sec: int                              # snippet freshness for agent_outputs
+    silenced_in_contexts: list[str] = field(default_factory=list)  # active context names that suppress this agent
+    inferred_params: list[InferredParam] = field(default_factory=list)
+
+    def to_dict(self) -> dict:
+        """Serialise for the registry endpoint. `inferred_params` drops `infer`
+        (callable) since the wire format only carries metadata."""
+        return {
+            "id": self.id,
+            "version": self.version,
+            "description": self.description,
+            "pref_schema": self.pref_schema,
+            "context_schema": self.context_schema,
+            "required_consents": self.required_consents,
+            "output_contract": self.output_contract,
+            "ttl_sec": self.ttl_sec,
+            "silenced_in_contexts": list(self.silenced_in_contexts),
+            "inferred_params": [
+                {
+                    "key": p.key,
+                    "ttl_sec": p.ttl_sec,
+                    "cold_start_default": p.cold_start_default,
+                    "min_history": p.min_history,
+                }
+                for p in self.inferred_params
+            ],
+        }