v0.7.0

[0.7.0] - 2026-07-26

Added

• registry/tr-registry.yaml — TR-SEC-011 (content provenance tracked and
  trust derived fail-closed at retrieval), TR-SEC-012 (strict LLM
  output-schema validation — reject, never coerce), exported from the
  2026-07-13 Zero-Trust-for-AI-Agents review (private monorepo)
• scripts/spotlighting-drift-guard.py — single-sourced spotlighting
  constants (security notice + untrusted-content delimiters) enforcement:
  fails CI if any LLM boundary re-inlines a copy instead of importing the
  designated constants module
• examples/spotlighting/ — worked example + planted re-inlined-copy
  fixture for the drift guard above (TR-SEC-005);
  .github/workflows/spotlighting-drift-guard-demo.yml proves the guard
  still catches it
• examples/provenance-trust-tags/ — reference implementation of a
  fail-closed source-type → trust-level mapping with its own drift guard
  (every content type must be explicitly classified), and a quarantine
  helper routing untrusted/unverified content into the spotlighting layer
  (TR-SEC-011)
• examples/strict-output-schema/ — before/after reference parser for LLM
  JSON output, with a live repro of the bool("false") is True fail-open
  coercion bug and the reject-never-coerce fix (TR-SEC-012)
• AGENTS.md — "Spotlighting at the Reasoning Boundary", "Memory /
  Provenance Hygiene", and "Strict LLM Output-Schema Validation" sections
• docs/requirements-implementation-map.md — rows for all three exports;
  the TR-SEC-005 row upgraded from "Documented" to "Documented + script +
  example"
• ATTRIBUTIONS.md — Microsoft public research on prompt-injection defenses
  (the "spotlighting" technique name and its measured effectiveness),
  cited via the same Anthropic eBook review

Full changelog: https://github.com/onesimplecode/ai-engineering-standards/blob/main/CHANGELOG.md