v1.3.0

[1.3.0]

Added — hardening for Continuous Synthetic Functional Agency

• Continuous agent daemon (continuous_agent.py): a top-level orchestrator
  that embodies the OBSERVE → GATE → DECIDE → EXECUTE → EVALUATE → RECORD →
  CONSOLIDATE loop in a single entry point. Bounded iteration counts, bounded
  interval pacing, and graceful shutdown. CLI:
  python3 continuous_agent.py --interval 2.0 --max-iterations 1000.
• HMAC-signed audit chains (audit.py): AuditChain now accepts an
  optional hmac_key (operator-held, e.g. via SecretResolver). Entries carry
  an HMAC-SHA256 tag over the chain hash + payload, making history
  tamper-evident and authenticated when the audit file lives on shared
  storage. Verification is backward-compatible with unsigned (1.2.x) chains.
  Includes a verify_audit_file() helper and python3 audit.py <file> CLI.
• Real embeddings for Tier 2 (vector_db.py): environment observations
  were previously stored with all-zero placeholder vectors; they now use
  deterministic n-gram hashed embeddings (hashed_embedding()), making
  similarity search meaningful without any third-party dependency.
• Pluggable embedding backends (vector_db.py): VectorDB accepts an
  injectable embedding function, so operators can swap in a learned encoder
  (sentence-transformers, OpenAI, etc.) without touching storage logic.
• Shogunet optional dependency (pyproject.toml): the networking runtime
  is now installable via pip install shugocore[shogunet].

Hardened — ethics surface

• EthicalGovernor placeholder predicates (can_explain, detect_bias,
  is_privacy_compliant, can_audit) no longer return hardcoded values.
  They now evaluate real signals: decision provenance/audit-trail presence,
  input attribute screening for protected-category bias, and data-subject
  consent coverage for privacy compliance.

Fixed

• pyproject.toml version was left at 1.2.0 after the 1.2.1 bump; both now
  share the single source of truth in version.py values.