Aleph Skill v2.0.0

Aleph Skill 2.0.0

Aleph 2.0 is a production-oriented rewrite of the evidence-grounded causal timeline simulation skill. It remains portable across AI CLIs and IDEs and does not require a unified CLI or MCP server.

Highlights

• Strict schema 2.0 contracts, typed public issue codes, recursive unknown-field rejection, bounded loaders, formula replay, and fail-closed assurance gates.
• Deterministic and Monte Carlo simulation with counter-based RNG, intervention handling, convergence checks, sensitivity analysis, hindcasting, and reproducible run hashes.
• Numerical run/replay binding to the declared model, trace, saved results, engine trajectory, and branch ledger.
• Sealed D Research 3.x integration with package discovery, claim-only ledger import, evidence regeneration, HMAC verification, and provenance receipts.
• Explicit separation of research and roleplay tracks, with public-role actor dossiers, knowledge packets, privacy controls, and Tier A receipt verification.
• Secure transactional installer for Codex, .agents, supported IDEs, and external AI CLIs, backed by a distribution allowlist and rollback receipts.
• Migration from schema 1.2 to 2.0 with sibling output, check mode, source-tree digest, and canonical dual-run verification.
• Seven validated data-only domain packs and eleven generated adapter targets.

Breaking changes

• New artifacts are written as schema 2.0.0; migrate 1.2 workspaces with sim:migrate.
• Assurance tiers are now experimental, limited, verified, and calibrated; a score cannot override a hard gate.
• Uncalibrated scenarios use relative_weight. Probability output requires declared calibration and hindcast evidence.
• Propagation traces are recomputed and replayed; forged or stale effects are rejected.
• Run, trace, branch, research, and roleplay integrity gates are stricter and may reject previously accepted workspaces.

See CHANGELOG.md and Upgrade plan.md in the source archive for the complete contract and migration details.

Verification

• 178 automated tests pass.
• GitHub Actions passes on Windows, macOS, and Ubuntu with Python 3.10, 3.11, 3.12, and 3.13, plus the quality job.
• Release gates include Ruff, strict mypy, 80% branch-coverage threshold, package validation, adapter drift checks, all seven domain packs, deterministic replay, adversarial rejection, and complete lifecycle acceptance.
• Release commit: f5af157f5c2bd3ec0b8fcc408e161ff30994729f.
• CI run: https://github.com/d-init-d/aleph-skill/actions/runs/29318391629
• Distribution tree: 209 files; tree SHA-256 30d946076d1a2a8f86a0eb94d368b0c86358d73f2416cb8302853b74d70e1ea8.
• Archive SHA-256: d2c2a2dd4e9b9afa9e8edba8f68d77ba975012c06ae2c8c959d31e4852323d0a.
• Manifest SHA-256: 0f8fe27f68729bfe7be42b9152f14049b2c6004559799a4b9507bebb53fdfab6.

Residual engineering limits

• Installer commit-time path rechecks materially narrow TOCTOU exposure, but a fully atomic OS-level guarantee would require platform-native directory-handle and no-follow APIs.
• Model/run pair promotion is exception-safe and rolls back ordinary failures; power-loss atomicity would additionally require a durable recovery journal.

These limits are documented explicitly so downstream users can choose controls appropriate to their threat model.