v0.5.0

Gnomon 0.5.0 adds a governed context-intelligence layer without surrendering
numeric authority to an LLM. The history-only primary remains immutable;
context may be rejected, represented as a conditional scenario, or lead a
human-review recommendation only through explicit typed evidence contracts.

Highlights

• Add strict, best-effort, and conditional-scenario publication modes with
  explicit support, provenance, primary-versus-selected relationships, and
  automation authority.
• Compile deterministic schedules, recurrences, relationships, categorical
  states, cited covariate tables, and bounded model-authored candidates into
  the same replay-tested publication machinery. Unresolved or weak claims fail
  closed or remain visibly conditional.
• Expand the MCP boundary for production agents with compact evidence-first
  profiles, reusable data and context references, structured recovery actions,
  bounded repairs, and verifier-enforced human-facing explanations.
• Preserve the immutable primary across every prior-assisted path. Uncertain
  timing and structurally indistinct changes remain scenario-only or report
  no_distinct_numeric_path; neither can silently mutate the primary or
  authorize automation.
• Add prospective, series-scoped outcome learning for candidate evidence,
  including cutoff-safe tracking, conservative multiplicity handling, and a
  fixed compromise path for supported best-effort recommendations.
• Extend decision and threshold-risk outputs with bounded assessments,
  evidence sufficiency, explicit automation eligibility, action utility, and
  independently scored human judgment.
• Add and harden ContextBench, OutcomeLearningBench, BreachBench, RecallBench,
  CiK, and workflow adapters with crash-safe checkpoints, strict resume
  identities, bounded concurrency, retained diagnostics, and sealed evidence.
• Improve bitemporal safety, context provenance, scenario consequence
  reporting, gate explanations, rejection-reason accounting, and agent
  preservation measurement throughout the CLI, Python, MCP, and artifact
  surfaces.

Validation

• Full repository suite: 2,528 passed, 1 skipped.
• Crash-safe ContextBench engine stress run: 112/112 completed, every declared
  gate passed, zero temporal leakage, 100% empirical admission precision, and
  45.833% empirical admission recall.
• Final Evidence/DeepSeek agent-boundary shard: 2/2 completed with publication
  parity, one exposed no_distinct_numeric_path relationship preserved 1/1,
  one exposed conditional-scenario contract preserved 1/1, and an exact
  zero-call resume replay.
• CI passes on Python 3.11, 3.12, and 3.13, including package installation,
  deterministic benchmark evidence, and container smoke tests.

The complete change-by-change record follows and remains part of the source
distribution for auditability.