AKTA integrates with adjacent systems in the AI-for-science trust stack. This guide summarizes reference-implementation integration points by release. AKTA is not a safety certification.
| Component | Path | Purpose |
|---|---|---|
| Grant-exact re-gate | akta/review_context.py, akta/review_loop.py |
prior_review_allowed_tools / prior_review_blocked_tools after SCOPE grant |
| SCOPE akta-review CLI | adapters/scope/client.py |
SCOPE_CLI_MODE=akta-review → scope akta review + summary.json validation |
| Reconstructable demo Cases A/B/C | scripts/demo_reconstructable_experiment.py |
Post-grant admissibility assertions (grant does not override evidence/profile) |
| Review summary schema | schemas/scope_akta_review_summary.schema.json |
Validates SCOPE akta-review CLI output |
# Grant-exact re-gate after SCOPE authorization
from akta import AKTAGate
gate = AKTAGate.from_policy_dir("policy/")
decision = gate.evaluate_with_grant(ai_output=..., requested_tool=..., scope_grant=grant, ...)
# SCOPE akta-review CLI mode
export SCOPE_CLI=scope
export SCOPE_CLI_MODE=akta-review
python scripts/verify_scope_live_chain.py --mode akta-review
python scripts/demo_reconstructable_experiment.pySee scope_live_conformance.md and limitations.md.
| Component | Path | Purpose |
|---|---|---|
| Live SCOPE verify | scripts/verify_scope_live_chain.py |
python-import, cli, akta-review modes; fails on simulated fallback |
| Policy integrity modes | akta/policy_signing.py |
dev_unsigned, deployment_hmac_attested, release_ed25519_signed |
| Closed-loop review | akta/review_loop.py |
Grant allowlist, protocol/evidence invalidation, blocked_tools preservation |
| Adversarial F01–F15 | evals/adversarial_transitions.py |
Per-class transition reporting |
| Holdout governance | evals/run_holdout_eval.py |
Private holdout slice for release acceptance |
export AKTA_REQUIRE_SIGNED_POLICY=1 # Ed25519 release mode
python evals/adversarial_transitions.py --out evals/reports/adversarial_transitions.json
make eval-holdout| Component | Path | Purpose |
|---|---|---|
| Cross-repo CI | .github/CROSS_REPO_CI.md |
Optional PF/PCS/SCOPE/PCS-Bench jobs |
| Closed-loop review | akta/review_decision.py |
Human review packet export/import |
| Ed25519 signing | akta/policy_signing.py |
Release authenticity via policy/release_keys.yaml |
| VSA rich report | adapters/vsa/import_report.py |
PCS vsa_report.json artifact |
| Scientific Memory / PCS-Bench | adapters/scientific_memory/, adapters/pcs_bench/ |
Import/export reference contracts |
| REST auth | adapters/generic_rest/server.py |
AKTA_REST_API_KEY, rate limiting |
| Component | Path | Purpose |
|---|---|---|
| SCOPE adapter | adapters/scope/client.py |
Simulated, python-import (SCOPE_REPO_PATH), or CLI (SCOPE_CLI) |
| SCOPE engine protocol | adapters/scope/engine_protocol.py |
Expected methods for python-import mode |
| PCS v0.5 full chain | adapters/pcs/export_artifact.py |
Per-file file_hashes, tamper validation |
| Production policy integrity | akta/policy_integrity.py |
Dev vs production HMAC; manifest required in production |
| Overlay governance | akta/overlays.py |
Tiers; production refuses experimental overlays |
| LLM trust boundary | docs/classifier_trust_boundary.md |
Tool registry overrides LLM; advisory metadata only |
# Production mode
export AKTA_PRODUCTION_MODE=1
export AKTA_POLICY_HMAC_KEY="<deployment-secret>"
python scripts/regenerate_policy_manifest.py # after policy edits
# SCOPE modes
export SCOPE_REPO_PATH=/path/to/SCOPE # python-import
export SCOPE_CLI=scope # CLI subprocess
python scripts/demo_akta_scope_protocol_drift.py
# PCS full-chain validate
akta export pcs --record akta_record.json --decision akta_decision.json --out pcs_bundle/ --validate| Component | Path | Purpose |
|---|---|---|
| MCP stdio server | adapters/mcp/server.py |
akta_evaluate, akta_export over JSON-RPC |
| Guardrail adapters | adapters/guardrails/ |
OpenAI / Anthropic tool-call checks |
| Transition runner | evals/transition_runner.py |
SCOPE grant → re-gate verification |
| Oracle-independent eval | evals/run_oracle_independent.py |
Hand-written expected labels |
| Domain overlays | overlays/biology_v0.yaml, etc. |
Hazard triggers and scope overrides |
Cross-repo contract tests: tests/contracts/README.md.
- VSA answers: Is this scientific claim/report grounded in evidence?
- AKTA answers: Is this AI-generated output admissible to become scientific action?
Import VSA reports via adapters/vsa/import_report.py to populate evidence context. AKTA does not blindly trust VSA outputs.
- AKTA decides scientific admissibility
- PF-Core proves the runtime respected the AKTA decision
akta export pf --record akta_record.json --decision akta_decision.json --out dist/pf_obligations/ --validateSee pf_core_bridge.md.
akta export pcs --record akta_record.json --decision akta_decision.json --out dist/pcs_bundle/ --validateWhen review is required, the bundle includes review_trigger.json. See pcs_export.md.
AKTA emits SCOPE-compatible review triggers on review_required and authorization_required:
akta review-trigger export --decision akta_decision.json --out review_trigger.jsonSee scope_bridge.md and review_integration.md.
from akta import AKTAGate, AKTAContext
gate = AKTAGate.from_policy_dir("policy/")
decision = gate.evaluate(
ai_output={"summary": "..."},
requested_tool="lab_scheduler.prioritize",
requested_action="prioritize_next_run",
context=AKTAContext.from_file("context.json"),
deployment_profile="P2_analysis_assistant",
domain_overlay="generic_lab_v0",
)
record = decision.to_record()akta gate --output ai_output.json --tool lab_scheduler.prioritize --profile P2_analysis_assistant --context context.json --out decision.json
akta record --decision decision.json --out record.json
akta eval --scenarios scenarios/canonical_5.jsonl --expected scenarios/expected_decisions.jsonl
akta eval --scenarios scenarios/public_100.jsonl --expected scenarios/expected_decisions.jsonl
akta export pcs --record record.json --decision decision.json --out pcs_bundle/ --validate
akta export pf --record record.json --decision decision.json --out pf_obligations/ --validate
akta review-trigger export --decision decision.json --out review_trigger.jsonpython scripts/demo_integrated_weak_evidence.py # AKTA → PF → PCS (no SCOPE)
python scripts/demo_akta_scope_protocol_drift.py # AKTA → SCOPE → PF → PCS
python scripts/demo_reconstructable_experiment.py # Full reconstructable chainPublic release checklist: RELEASE.md.