Action Commit Safety for AI agents: exact-call approval, UNKNOWN outcome recording, idempotent execution, and signed audit.
Project description
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.
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 v0.9 development contract for detached, privacy-safe policy-decision
attachments is documented in
docs/decision-explanations.md. It remains
separate from v0.8 Evidence Bundle and receipt-verification protocols.
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
- Deterministic first - code and policy establish the execution boundary.
- Policy over prompt - prompts guide behavior; policies authorize actions.
- Defense in depth - independent controls can only tighten a decision.
- Framework agnostic - the runtime does not own planning or model calls.
- Human in the loop - applications supply the decision channel.
- Observability by default - each transition produces traceable state.
- Immutable context - middleware returns a new context instead of mutating shared state.
Examples
examples/standalone_demo.py: framework-free pipelineexamples/cli_approval_demo.py: interactive human decision providerexamples/langgraph_integration.py: LangGraph tool-node integrationexamples/openai_agents_integration.py: OpenAI Agents SDK tool integrationexamples/crewai_integration.py: CrewAI decorated toolexamples/agno_integration.py: Agno function toolexamples/llamaindex_integration.py: LlamaIndexFunctionToolexamples/autogen_integration.py: Microsoft AutoGenFunctionToolexamples/strict_action_contract.py: sealed contracted side-effecting runtimescripts/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
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