agent-runtime-governance 0.8.1

Action Commit Safety for AI agents: exact-call approval, UNKNOWN outcome recording, idempotent execution, and signed audit.

Agent Runtime Governance

The action a reviewer approved is the action that executes. A side effect with an uncertain outcome is recorded as UNKNOWN, and automatic reuse stays blocked while that idempotency record is retained.

Two failures motivate this project. An agent retries a payment call after a network timeout and charges a customer twice. A reviewer approves one tool call, and something different executes because arguments or governance state changed between approval and execution. Agent Runtime Governance is an embeddable, framework-agnostic Python runtime that closes both gaps at the final execution boundary - the moment a proposed tool call is about to touch the real world within the configured storage guarantees. It runs inside the agent stack you already use rather than replacing it. The default in-memory idempotency store has bounded TTL/LRU retention and does not survive restarts; longer-lived protection requires a durable store. v0.7 adds durable, deterministic reconciliation for UNKNOWN outcomes, and v0.8 adds portable evidence verification and cross-framework conformance.

Quick start

pip install agent-runtime-governance

from pathlib import Path

from agent_runtime_governance import ExecutionMode, Runtime

runtime = Runtime()
WORKSPACE_ROOT = Path.cwd().resolve()

@runtime.tool(execution_mode=ExecutionMode.READ_ONLY)
def read_file(path: str) -> str:
    candidate = (WORKSPACE_ROOT / path).resolve()
    try:
        candidate.relative_to(WORKSPACE_ROOT)
    except ValueError as exc:
        raise ValueError("path must remain inside the workspace") from exc
    return candidate.read_text(encoding="utf-8")

print(read_file("README.md"))

Add deterministic rules, semantic review, human decisions, and signed audit:

import os

from agent_runtime_governance import (
    ApprovalMiddleware, AuditMiddleware, HumanDecisionProvider,
    InvocationOptions, JSONLAuditSink, LLMMiddleware, RiskTier,
    Rule, RuleMiddleware, Runtime,
)

runtime = Runtime([
    RuleMiddleware([Rule("explicit-wipe", r"\bwipe\s+all\b", "bulk wipe is forbidden")]),
    LLMMiddleware(lambda ctx: True),
    ApprovalMiddleware(HumanDecisionProvider(lambda ctx, request: True)),
    AuditMiddleware(
        JSONLAuditSink("audit.log", sign_key=os.environ["ARG_AUDIT_HMAC_KEY"])
    ),
])

@runtime.tool(risk=RiskTier.HIGH, requires_approval=True)
def delete_file(path: str) -> bool:
    return True

delete_file(
    "old.log",
    _governance=InvocationOptions(input_text="remove the old application log"),
)

Shipped guarantees and regression evidence

Every shipped guarantee links to its regression test:

Shipped in v0.5.1	Evidence
Approval is bound to request ID, tool name, argument digest, risk tier, policy version/digest, subject, tenant, identity issuer, and request expiry. A mismatch or expired request/decision is rejected before the tool body runs	test_decision_binding_rejects_wrong_request_or_arguments
Caller-supplied metadata cannot forge approval, policy, or identity state	test_caller_metadata_cannot_forge_required_approval
A mutating call with an uncertain outcome is recorded as UNKNOWN instead of being retried	test_cancellation_propagates_and_marks_context_unknown
Idempotency keys are mandatory for idempotent mutating tools and bound to the parameter fingerprint	test_idempotency_key_is_bound_to_parameter_fingerprint
JSONL audit is hash-chained and signable; deletion and tampering are detected	test_jsonl_audit_hash_chain_detects_deletion_and_tamper

v0.6 binds one immutable action across the final execution boundary. Every claim below is covered by a regression test or recorded benchmark:

Shipped in v0.6.0	Evidence
The exact frozen parameter snapshot covered by action_digest reaches the tool body and cannot be replaced by middleware or hooks	test_exact_bound_snapshot_reaches_tool_and_audit, test_middleware_cannot_replace_or_mutate_bound_action
Key, policy, and external-precondition drift fail before tool entry	test_key_rotation_fails_before_tool_entry, test_policy_identity_mismatch_fails_closed, test_precondition_change_fails_before_tool_entry
Approval and idempotency consume action_digest; v0.5 records remain readable but cannot authorize or satisfy a contracted v0.6 action	test_approval_is_bound_to_action_digest, test_v05_approval_fails_closed_for_contracted_tool, test_v05_compatibility.py
Success and terminal exception/timeout/cancellation paths retain the same action identity	test_exact_bound_snapshot_reaches_tool_and_audit, test_exception_and_timeout_keep_bound_action_in_audit, test_cancellation_keeps_bound_action_in_audit
Audit evidence carries the action identity without duplicating raw parameters, and OpenTelemetry exports the same contract/action attributes	test_audit_bound_action_never_duplicates_raw_parameters, test_opentelemetry_exports_bound_action_identity
At 1,000 requests and concurrency 100 on the recorded Windows/Python 3.12 host, the median of three alternating paired runs measured action bind plus verification at 1.553x mean, 1.720x p95, 1.850x p99, and 1.040x peak traced memory versus its strict baseline	v0.6.0-windows-python312.json, v0.6.0 budget

v0.7 keeps UNKNOWN recovery on a durable, compare-and-set ledger. The following behaviors are implemented and covered by regression tests; they are not a claim that an external side effect is exactly-once unless the downstream system independently supports that property.

Shipped in v0.7.0	Evidence
Before an idempotent side effect can be dispatched, the SQLite claim and bounded recovery descriptor (excluding raw caller key and tool parameters) are created in one transaction; an expired prepared lease materializes an UNKNOWN head instead of becoming retryable	test_runtime_atomically_prepares_recovery_descriptor_before_dispatch, test_expired_atomically_prepared_lease_materializes_reconciliation_head
Reconciliation records are append-only and revision-checked. The provider identity, protocol version, and supported evidence kinds persisted with the action must still match after restart	test_reconciliation_rejects_provider_drift_after_restart
Reconciliation head/event lineage intent is committed to a SQLite outbox with the matching mutation. Delivery is ordered per execution, retryable, and deduplicated by a stable source event ID at SQLiteAuditSink	test_reconciliation_audit_outbox_is_ordered_and_redacted, test_sqlite_audit_source_id_prevents_duplicate_after_ack_failure
Strict control-plane operations require separate probe, manual-resolution, and audit-drain permissions, plus tenant binding for per-action access	test_strict_reconciliation_denies_cross_tenant_probe_without_attempt, test_strict_global_audit_recovery_requires_its_own_permission
A durable started probe is finalized under an independent budget. An expired unclosed probe is closed with recovery_required and moved to MANUAL_REVIEW; a second provider probe is not started	test_cancellation_during_finish_keeps_finalization_running, test_restart_quarantines_an_expired_unfinished_provider_attempt
Control-plane caller deadlines bound audit recovery and delivery; a stalled sink leaves the durable envelope pending rather than corrupting the ledger or holding the process open after shutdown	test_global_audit_recovery_honors_its_caller_deadline, test_blocked_reconciliation_audit_sink_cannot_hold_python_process_open
Shared SQLite migration rejects orphaned staging objects and cannot upgrade idempotency independently of an existing reconciliation authority	test_sqlite_idempotency_rejects_orphaned_migration_staging_table, test_standalone_idempotency_migration_rejects_colocated_reconciliation
Async shutdown rejects self- and cross-loop deadlocks, stops new admission, and waits for already-admitted, cancellation-ignoring, and thread-backed runtime work before releasing executors	test_aclose_waits_for_active_public_operation, test_aclose_waits_for_detached_uncooperative_async_tool, test_aclose_waits_for_timed_out_uncooperative_sync_hook, test_aclose_waits_for_timed_out_uncooperative_sync_audit_sink, test_aclose_waits_for_timed_out_sync_tool_on_external_executor, test_aclose_waits_for_a_cancellation_ignoring_provider, test_aclose_rejects_self_shutdown_from_active_operation, test_aclose_rejects_cross_loop_shutdown_while_work_is_active

v0.8 makes evidence portable and keeps asynchronous extension behavior explicit. Its claims remain bounded: integrity, signer authenticity, and configured external outcome verification are distinct; no row below claims certification, generic external verification, or exactly-once side effects.

The v0.8.0 GitHub Release was withdrawn before it gained verified assets, provenance, or a PyPI distribution. v0.8.1 is the release-validation patch that retains the implementation scope and corrects that path.

v0.8 implementation evidence	Evidence
Evidence Bundle v1 is a closed, immutable RFC 8785 commitment over allowlisted values and never serializes raw parameters, identity values, secrets, or receipts	test_evidence_bundle_matches_v1_golden_fixture, test_bundle_projects_only_allowlisted_values_and_never_serializes_secrets, test_historical_v1_vector_is_packaged_and_byte_stable
Detached Ed25519 signatures validate only against explicit trust roots; trusted, rotated, unknown, revoked, and expired keys have deterministic outcomes	test_ed25519_signature_verifies_without_mutating_v1_bundle, test_rotated_trust_roots_verify_signatures_from_each_configured_key, test_verification_rejects_unknown_key, test_verification_rejects_revoked_key, test_verification_rejects_expired_key
The offline verifier reports integrity, signer authenticity, and external outcome separately and rejects mutation, binding substitution, and broken reconciliation lineage	test_cli_verifies_signed_bundle_and_never_claims_an_external_outcome, test_cli_detects_mutation_against_detached_signature_and_expected_digest, test_cli_detects_cross_tenant_and_stale_binding_substitution, test_cli_rejects_broken_reconciliation_lineage
External anchor continuity and receipt outcomes are verified only through an explicitly selected provider; absent or unsupported providers report unsupported	test_anchor_provider_detects_deletion_and_reordering_without_changing_bundle, test_absent_or_unsupported_anchor_never_claims_continuity, test_receipt_verifier_projects_only_bounded_identity_and_never_leaks_receipt, test_receipt_binding_and_outcome_disagreement_fail_closed
The release workflow derives and validates a closed Release Verification Manifest, then protects the manifest with release checksums and provenance before distribution	test_generates_and_validates_same_job_release_evidence, test_release_and_publish_workflows_gate_manifest_before_distribution
The v0.8.1 release workflow audit is limited to the frozen external production dependency closure, fails on audit collection errors, and continues to reject every skipped dependency entry before distribution	test_release_and_publish_workflows_gate_manifest_before_distribution, test_generation_rejects_a_dependency_audit_with_skipped_dependency
Standalone Runtime, LangGraph, and OpenAI Agents SDK real tool entries preserve shared success, policy-denial, and approval-denial governance semantics	test_standalone_runtime_keeps_protected_semantics, test_langgraph_node_matches_standalone_protected_semantics, test_openai_agents_tool_matches_standalone_protected_semantics
Native asynchronous extensions stay on the caller loop; synchronous fallback has bounded worker and queue capacity, while OPA and Slack native transports retain asynchronous behavior	test_native_async_callable_instances_and_partials_stay_on_calling_loop, test_sync_capacity_separates_workers_from_admitted_queue, test_sync_observer_does_not_stall_a_ten_millisecond_ticker, test_runtime_opa_timeout_cancels_native_transport_without_warning, test_runtime_slack_native_async_transport_stays_on_calling_loop
v0.7 public imports and call signatures remain compatible while private services are grouped by domain; terminal events are immutable, redacted, and failure-isolated for consumers	test_v070_public_call_signatures_remain_compatible, test_v070_wheel_and_sdist_expose_stable_imports, test_private_services_are_grouped_under_explicit_internal_domains, test_runtime_event_projection_is_versioned_immutable_and_redacted, test_failing_event_subscriber_does_not_block_other_consumers
The CI-sized extension-dispatch matrix passed its committed same-host ratio budget on the recorded Windows/Python 3.12 host; this is point-in-time measurement evidence, not a service-level promise	v0.8.0-windows-python312.json, v0.8 dispatch budget, test_extension_dispatch_budget_uses_same_host_mode_ratios

The staged v0.9-v1.0 direction and its exit criteria are in ROADMAP.md and docs/production-roadmap.md. Planned capabilities are never presented as shipped.

The v0.8 verifier, its detached external-evidence boundaries, and its input/exit-code contract are documented in docs/evidence-verification.md. Its closed v1 schema and future-version policy are in docs/evidence-schema-compatibility.md.

How it compares

Human approval, policy interception, audit, retries, and telemetry are industry baseline; this project does not claim to have invented them. The narrow claim is the governed execution boundary. Rows cite each project's own public documentation and describe scope, not quality.

Alternative	What it provides	Where this project is narrower and deeper
Framework-native approvals: OpenAI Agents SDK, LangGraph, pydantic-ai deferred tools	Pause-and-approve flows inside one framework	One framework-neutral runtime where approval is revalidated against the normalized call immediately before execution, combined with idempotent commit and UNKNOWN semantics
Microsoft Agent Governance Toolkit	Broad policy, identity, sandboxing, and SRE toolkit	Its versioned limitations document records that audit captures attempts and allow/deny results, with outcome attestation planned; this project's entire scope is that commit-and-outcome boundary
Durable execution engines: Temporal, Restate, DBOS	Durable workflow state with automatic retries	The governance-layer default is different: an uncertain side effect is recorded as UNKNOWN and is not automatically retried while unresolved. v0.7 adds a receipt/probe reconciliation ledger and explicit manual-review path; human approval remains bound to the action identity
Content guardrails: NeMo Guardrails, Guardrails AI	Input, output, and dialog rails	A different layer that composes with this one; this project governs the side-effect boundary, not prompts or content

Prompt instructions are useful guidance, but they are not an authorization boundary. This project places deterministic policy, explicit decisions, and audit outside the model while remaining independent from agent planning and model providers.

Architecture

Tool Registry
     |
     v
Immutable ExecutionContext
     |
     v
Runtime Pipeline
  Prepare -> Bind Action -> Policy -> Human Decision
     |
     v
Action Digest -> Idempotency -> Executor Revalidation -> Tool
     |
     v
Terminal Context -> Evidence-safe Audit Snapshot

Gating middleware may stop execution and fails closed. Observing middleware cannot grant permission and normally cannot interrupt an allowed tool. An audit sink explicitly configured as critical is the exception: failed delivery stops the call because an unaudited privileged action is not allowed. Earlier denials cannot be overridden by later middleware.

Design principles

1. Deterministic first - code and policy establish the execution boundary.
2. Policy over prompt - prompts guide behavior; policies authorize actions.
3. Defense in depth - independent controls can only tighten a decision.
4. Framework agnostic - the runtime does not own planning or model calls.
5. Human in the loop - applications supply the decision channel.
6. Observability by default - each transition produces traceable state.
7. Immutable context - middleware returns a new context instead of mutating shared state.

Examples

• examples/standalone_demo.py: framework-free pipeline
• examples/cli_approval_demo.py: interactive human decision provider
• examples/langgraph_integration.py: LangGraph tool-node integration
• examples/openai_agents_integration.py: OpenAI Agents SDK tool integration
• examples/crewai_integration.py: CrewAI decorated tool
• examples/agno_integration.py: Agno function tool
• examples/llamaindex_integration.py: LlamaIndex FunctionTool
• examples/autogen_integration.py: Microsoft AutoGen FunctionTool
• examples/strict_action_contract.py: sealed contracted side-effecting runtime
• scripts/replay.py: print the snapshots for a trace from JSONL audit data

Each framework adapter is intentionally an example rather than a runtime dependency. The governed function remains ordinary Python and can be wrapped by the framework's native tool interface. The optional LangGraph node and OpenAI Agents SDK FunctionTool invocation paths have an extras-gated conformance suite in tests/conformance; it compares their governed tool boundary with standalone Runtime behavior. The OpenAI path uses the native Runner with a deterministic in-process Model, makes no provider API call, and does not add a general adapter marketplace.

Engineering controls

v0.2 adds immutable pipeline composition, lifecycle hooks, Python-native policy, metrics, retries, timeouts, and optional OpenTelemetry export:

from agent_runtime_governance import (
    MetricsMiddleware, Pipeline, PolicyMiddleware, RetryMiddleware,
    SimplePolicy, TimeoutMiddleware,
)

pipeline = Pipeline([
    PolicyMiddleware(SimplePolicy(admin_only={"restart_service"})),
    RetryMiddleware(max_attempts=2),
    TimeoutMiddleware(5.0),
    MetricsMiddleware(),
])
runtime = Runtime(pipeline)

@runtime.before_tool
def attach_region(ctx):
    return ctx.evolve(metadata={**ctx.metadata, "region": "cn-beijing"})

Pipeline edits return a new Pipeline; a live runtime is never mutated behind concurrent calls. Hooks may enrich context but cannot change status or decisions.

Policies, snapshots, and regression

Load a versioned policy with separate semantic and exact-artifact digests:

from agent_runtime_governance import Runtime, YAMLPolicyLoader

document = YAMLPolicyLoader.load("examples/policy.yaml")
runtime = Runtime([document.artifact_middleware()])
print(document.version, document.digest, document.artifact_digest)

Duplicate tool entries, unknown fields, invalid risks, and unsafe YAML tags are rejected. YAML remains a configuration format over the deliberately small SimplePolicy model; it is not a general policy language. digest identifies normalized policy semantics for compatibility and drift comparison; artifact_digest identifies the exact loaded bytes and is the value strict production profiles must bind.

SnapshotMiddleware records immutable lifecycle snapshots. ReplayDebugger prints timelines and field-level diffs, while EvaluationSuite runs governance without executing tools. PolicyDriftDetector reapplies deterministic policy to the same recorded request identity and reports decision or risk changes. Runtime.areplay() is deliberately non-authoritative: historical identity fields are analysis inputs, verification metadata is stripped, no tool runs, and no BoundAction is created. Use apreview() with current trusted identity claims when a fresh bound action preview is required.

python scripts/trace_debug.py snapshots.jsonl TRACE_ID
python scripts/trace_debug.py snapshots.jsonl TRACE_ID --diff 0 1
python scripts/trace_debug.py snapshots.jsonl TRACE_ID --mermaid

Plugins and integrations

Plugins register components during construction; the built runtime remains immutable:

from agent_runtime_governance import OPAClient, OPAPlugin, PluginManager

manager = PluginManager()
manager.load(OPAPlugin(OPAClient("http://localhost:8181", "agents/tools/allow")))
runtime = manager.build()

Third-party plugins can publish the Python entry-point group agent_runtime_governance.plugins. Entry points execute Python code and must be treated as trusted dependencies. The project does not download plugins or provide a marketplace.

Integration	Extra	Behavior
Prometheus	prometheus	Terminal status and duration; no trace/user labels
Slack	none	Denial/failure notifications; official HTTPS webhooks only
OPA	none	Minimal decision input; fail closed by default
LangGraph	langgraph	Governed function in a graph node
OpenAI Agents SDK	openai-agents	Governed async function tool
CrewAI	crewai	Decorated governed async tool
Agno	agno	Typed governed Python function
LlamaIndex	llamaindex	Governed FunctionTool async function
Microsoft AutoGen	autogen	Governed FunctionTool async function

Install only the integrations an application uses:

pip install "agent-runtime-governance[yaml,prometheus,crewai]"

Production reliability

v0.5 establishes the production reliability baseline:

• idempotent tool execution with mandatory keys and in-memory or SQLite stores;
• durable approval recovery with leased reserve/commit/release transitions;
• absolute deadline propagation through admission, middleware, identity, tools, and idempotency waits;
• cancellation handling that records mutating in-flight work as UNKNOWN;
• trusted HMAC identity envelopes with replay protection;
• contract validation for parameters, results, and payload size limits;
• reliable JSONL and SQLite audit sinks with hash-chain verification;
• bounded concurrency, external integration circuit breakers, and fault tests.

v0.6 adds strict startup inventory and sealing, one BoundAction.action_digest across approval/idempotency/execution/audit, executor-boundary revalidation, policy and precondition identity checks, and versioned v0.5 migration readers. See docs/migration-v0.6.md and the runnable strict_action_contract.py example.

The current v0.7 implementation adds an explicit recovery protocol for idempotent actions whose external outcome is uncertain. Strict deployments co-locate SQLiteIdempotencyStore and SQLiteReconciliationLedger in the same SQLite database so a claim and its recovery descriptor are created before dispatch. Reconciliation head/event lineage mutations and their audit envelopes commit together; SQLiteAuditSink deduplicates retried envelope delivery with the outbox source ID. The application must supply a read-only receipt/probe provider; the runtime binds its identifier, protocol version, and evidence kinds to the persisted action but cannot prove that third-party provider code has no side effects. Pre-outbox reconciliation databases require the dedicated offline SQLiteReconciliationLedger.migrate_legacy(...) operation; ordinary runtime construction fails closed rather than recreating an outbox. A pre-versioned standalone idempotency database likewise requires the dedicated offline SQLiteIdempotencyStore.migrate_legacy(...) operation; normal startup accepts only the current protected idempotency schema. See docs/production.md and docs/migration-v0.7.md before enabling it for production traffic.

The example hashes the exact policy artifact in examples/policies/, passes that identity through PolicyMiddleware and ProductionProfile, seals the runtime, and persists signed audit plus idempotency state:

python -m pip install -e .
$env:ARG_IDENTITY_DIGEST_KEY = python -c "import secrets; print(secrets.token_urlsafe(32))"
$env:ARG_AUDIT_HMAC_KEY = python -c "import secrets; print(secrets.token_urlsafe(32))"
$env:ARG_STATE_DIR = ".arg-state-example"
python examples/strict_action_contract.py
Remove-Item -Recurse -Force $env:ARG_STATE_DIR

python -m pip install -e .
export ARG_IDENTITY_DIGEST_KEY="$(python -c 'import secrets; print(secrets.token_urlsafe(32))')"
export ARG_AUDIT_HMAC_KEY="$(python -c 'import secrets; print(secrets.token_urlsafe(32))')"
export ARG_STATE_DIR=.arg-state-example
python examples/strict_action_contract.py
rm -rf -- "$ARG_STATE_DIR"

StaticIdentityProvider in this example represents one identity already authenticated by a trusted single-service host boundary. It must not be used to authenticate arbitrary multi-user requests; use a validating identity provider at that boundary in production.

The production smoke suite starts real Docker services for OPA and the OpenTelemetry Collector, exports through OTLP HTTP, scrapes a real HTTP /metrics exposition endpoint, and can build the local package into a pinned Python image before running a hardened Runtime Job in a local Kind cluster:

python integration/production_smoke.py --skip-kind
python integration/production_smoke.py

Production deployments must configure a trusted identity provider with require_verified_identity=True; caller-supplied user, tenant, and permissions fields are compatibility inputs, not a trust boundary. SQLite stores coordinate processes on one host and require a distributed adapter for multi-host deployments. For strict v0.7 reconciliation, configure a signed, durable, source-idempotent audit sink behind a fail-closed AuditMiddleware. SQLiteAuditSink is the built-in tested implementation; JSONL audit cannot deduplicate a replayed outbox envelope. A recovery worker invokes Runtime.adrain_reconciliation_audit_outbox() with a separately authorized trusted identity, while Runtime.areconcile() and Runtime.aresolve_reconciliation() use their own control-plane permissions.

Release verification

Before a GitHub release is published, maintainers review the protected CI matrix required by branch protection (Python 3.10-3.13) and Docker-backed integration smoke. The post-publication release workflow then repeats the full Python suite and Docker-backed smoke on Python 3.13, runs dependency audit and package installation checks, and attaches the SPDX SBOM, SHA256 checksums, and GitHub provenance. PyPI Trusted Publishing is a separate workflow that consumes those verified release artifacts. Migration restore drills and public-index installation checks are recorded release evidence, not inferred from a successful build. Complete point-in-time records for published releases are in docs/release-verification.md.

Benchmarks measure incremental runtime overhead for baseline, Rule, OPA, Audit, OpenTelemetry, 10-middleware pipelines, and paired strict runtimes with and without action binding:

python benchmarks/benchmark_runtime.py --requests 100,500,1000 --concurrency 100

The committed Windows/Python 3.12 measurement is available in benchmarks/results/v0.5.0-windows-python312.json. Its 100-waiter, zero-hold FIFO admission test measured 2.93 ms p99 wait time. This point-in-time result is regression evidence for that machine, not a cross-platform latency SLA.

The v0.6 final measurement, earlier pre-release measurement, and enforced paired budget are in benchmarks/results/v0.6.0-windows-python312.json, benchmarks/results/v0.6.0-rc-windows-python312.json, and benchmarks/budgets/v0.6.0.json.

The v0.8 extension-dispatch matrix is recorded in benchmarks/results/v0.8.0-windows-python312.json and checked against benchmarks/budgets/v0.8.0-extension-dispatch.json. It compares paired native-async and legacy-sync callbacks on the same host; it is not a production latency or throughput promise.

Version history

Version	Scope
v0.1.0	Immutable context, registry, rule/LLM/approval/audit middleware, basic replay
v0.2.0	Hooks, Python policy, metrics, retry, timeout, and OpenTelemetry bridge
v0.3.0	Strict YAML policy, snapshots, replay diff, evaluation, and policy drift
v0.4.0	Trusted plugins, Prometheus, Slack, OPA, and six framework integrations
v0.4.1	Mandatory linked issues and merge-policy verification
v0.4.2	Fail-closed CodeRabbit review verification for the current commit
v0.5.0	Production reliability: idempotency, identity, durable approvals, audit, deadlines, cancellation, contracts, real integration smoke
v0.5.1	Security hardening: caller metadata isolation and exact approval binding
v0.6.0	Immutable action contracts from admission through approval, idempotency, executor revalidation, telemetry, and audit
v0.7.0	Durable UNKNOWN reconciliation, strict recovery authorization, and a source-idempotent reconciliation-audit outbox
v0.8.0 (withdrawn before distribution)	Portable governance evidence, configured external verification, cross-framework conformance, async-first extension dispatch, and internal service boundaries
v0.8.1 (release-validation patch)	The v0.8 implementation scope with a strict audit of its frozen external production dependencies

Released versions are preserved as immutable Git tags. A withdrawn prerelease remains visible as a tag, but is not a verified distribution. See CHANGELOG.md for the detailed compatibility and security notes.

Non-goals

• Agent planning, prompting, model routing, or memory
• Multi-agent communication or distributed execution
• Approval UI or a hosted control plane
• A general policy language, plugin marketplace, or mutable live pipeline
• Production-grade time-travel debugging
• Arbitrary condition evaluation, policy inheritance, or conflict resolution

See ARCHITECTURE.md for invariants and ROADMAP.md for the deliberately staged scope. Security reports and integration boundaries are documented in SECURITY.md. Contributor workflow and plugin contribution rules are documented in CONTRIBUTING.md. Production configuration and recovery are covered in docs/production.md, and the release procedure is defined in RELEASING.md. The evidence-backed v0.6-v1.0 strategy is specified in docs/production-roadmap.md.

Development

python -m pip install -e ".[dev]"
pytest
python integration/production_smoke.py --skip-kind
python -m build

Python 3.10+ is supported. The core package depends on filelock and jsonschema; optional integrations are installed via extras.

Pull requests must link an existing issue in this repository with a closing keyword such as Fixes #123. A repository workflow closes unlinked pull requests automatically. Pull requests to main must also pass every CI job and the CodeRabbit status, receive a verified CodeRabbit approval for the current head commit, and resolve blocking reviews. A skipped, rate-limited, stale, or missing CodeRabbit review fails closed. GitHub does not allow a pull request author to approve their own change, so the single-maintainer phase has no human approval count; one code-owner approval and last-push approval become mandatory when a second maintainer is added. Maintainers still use the same issue and pull request flow as external contributors, and administrators cannot push directly to main or bypass protection.

License

MIT