M7.1: extract nisse-core

What isn't the dev agent's moves to nisse-core, unchanged in behaviour,
with its tests: canonical, render, render_anthropic, llm, catalog, probe,
context, views, state, reconcile, worker, cancel, dump, transport, matrix,
execution, testing, vault, memory, oplog, envfile and gitea (whole).

- nisse_core.state.StateStore holds the tables every agent has; an
  agent's subclass adds its tables (version, migrations), roles and
  views. nisse_dev.state.StateStore adds the build VM blocks (v5).
- views.project takes what each role is shown, rather than a fixed table.
- Vault takes the agent's name (agent=), for provenance.
- A test that nisse_core never imports an agent.
- The loop, config, git, delegation, expert, tools and evals stay in
  nisse-dev until nisse-ops has a loop to share.

Docs: the Development Plan marks M7.1 done and notes that Phase 6 waits on
the agent host and Terraform; Architecture Part L names the package.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk

nisse-core/src/nisse_core/canonical.py

@@ -0,0 +1,173 @@
+"""Canonical transcript schema (architecture L7).
+
+The durable record is this event log, never a provider-shaped ``messages``
+array; provider request bodies are rendered from it at call time. Canonical
+tool-call IDs are minted locally — provider IDs are mapped at the boundary and
+never used as a join key.
+
+Transcript appends are the conversation record itself, not state-machine
+mutations, so they are deliberately outside the L12 state-change taxonomy.
+"""
+
+import uuid
+from dataclasses import asdict, dataclass, fields
+from typing import Any
+
+
+@dataclass(frozen=True)
+class UserMessage:
+    text: str
+    source: str  # e.g. a Matrix event ID
+
+
+@dataclass(frozen=True)
+class AssistantText:
+    text: str
+    model: str
+
+
+@dataclass(frozen=True)
+class ToolCall:
+    call_id: str  # canonical, minted locally via mint_call_id()
+    tool: str
+    arguments: dict[str, Any]
+
+
+@dataclass(frozen=True)
+class ToolResult:
+    call_id: str
+    result: str
+    success: bool
+
+
+@dataclass(frozen=True)
+class PlanSubmitted:
+    plan: str
+    model: str
+
+
+@dataclass(frozen=True)
+class GateOpened:
+    gate: str
+    reason: str
+
+
+@dataclass(frozen=True)
+class DelegationStarted:
+    brief: str
+    role: str
+    model: str  # the alias asked for, e.g. "remote-architecture"
+    caps: dict[str, Any]  # turns / tokens / wall-clock limits
+    # What the alias resolved to at task start. An alias is free to change
+    # models between tasks, so eval history (L9) keyed on the alias alone
+    # would average results across whatever it happened to point at.
+    backing_model: str = ""
+
+
+@dataclass(frozen=True)
+class DelegationCompleted:
+    handback: str
+    artifacts: list[str]
+    tokens: int
+    duration_s: float
+    exit_status: str
+
+
+@dataclass(frozen=True)
+class Fact:
+    """Something the orchestrator knows that the models must too (L6, L7):
+    a plan approved, a milestone finished, a PR opened. Written by the
+    orchestrator; every role sees it, as a statement rather than a turn."""
+
+    text: str
+
+
+@dataclass(frozen=True)
+class ActionVerdict:
+    """What the fast path made of a tool call before it ran (P4, L4): a
+    record for the log, the operator and the classifier's evaluation set,
+    never shown to a model."""
+
+    call_id: str
+    tool: str
+    effect: str  # harmless | contained | unknown | dangerous | refused
+    rule: str
+    reason: str
+    decision: str  # ran | refused | asked | allowed | classified
+    # Who decided: the fast path's rules, or the classifier (L4), with the
+    # model it ran on and exactly what it was shown (the evaluation set, L9).
+    source: str = "fast_path"
+    model: str = ""
+    input: str = ""
+
+
+@dataclass(frozen=True)
+class Compaction:
+    summary: str
+    model: str
+    replaces: list[int]  # [first_id, last_id] inclusive range replaced
+
+
+CanonicalEvent = (
+    UserMessage
+    | AssistantText
+    | ToolCall
+    | ToolResult
+    | PlanSubmitted
+    | GateOpened
+    | DelegationStarted
+    | DelegationCompleted
+    | Fact
+    | ActionVerdict
+    | Compaction
+)
+
+EVENT_TYPES: dict[str, type] = {
+    "user_message": UserMessage,
+    "assistant_text": AssistantText,
+    "tool_call": ToolCall,
+    "tool_result": ToolResult,
+    "plan_submitted": PlanSubmitted,
+    "gate_opened": GateOpened,
+    "delegation_started": DelegationStarted,
+    "delegation_completed": DelegationCompleted,
+    "fact": Fact,
+    "action_verdict": ActionVerdict,
+    "compaction": Compaction,
+}
+
+_TYPE_NAMES = {cls: name for name, cls in EVENT_TYPES.items()}
+
+
+@dataclass(frozen=True)
+class StoredEvent:
+    id: int
+    ts: str
+    event: CanonicalEvent
+    # The work item it belongs to (None: agent-level, L6) and the role that
+    # produced it (L7). Rendering uses both.
+    work_item: str | None = None
+    actor: str = ""
+
+
+def mint_call_id() -> str:
+    return f"call-{uuid.uuid4().hex}"
+
+
+def event_type(event: CanonicalEvent) -> str:
+    return _TYPE_NAMES[type(event)]
+
+
+def to_payload(event: CanonicalEvent) -> dict[str, Any]:
+    return asdict(event)
+
+
+def from_payload(type_name: str, payload: dict[str, Any]) -> CanonicalEvent:
+    cls = EVENT_TYPES.get(type_name)
+    if cls is None:
+        raise ValueError(f"unknown canonical event type: {type_name!r}")
+    known = {f.name for f in fields(cls)}
+    unknown = payload.keys() - known
+    if unknown:
+        raise ValueError(f"unknown fields for {type_name}: {sorted(unknown)}")
+    return cls(**payload)