While Open Policy Agent (OPA) is a mature, general-purpose engine using the Rego language, Spctre is a specialized governance control plane tailored for AI agent runtimes. Spctre supports prompt-scoped policy evaluation, native human-in-the-loop workflows, and structured audit logs that verify AI decision compliance.
Features Comparison
| Governance Area | Spctre | Open Policy Agent (OPA) |
|---|---|---|
| Primary Focus | AI agent tool-call governance with audit provenance | General-purpose policy evaluation for APIs and microservices |
| Policy Language | Declarative YAML/JSON (AGT-compatible bundles) | Rego — a custom query language with a learning curve |
| Human-in-the-Loop | Built-in review queues with Slack/Teams notifications | Not supported — requires full custom integration |
| Audit Logging | Immutable hash-chained records per tool call | Decision logs written to stdout/file — no tamper evidence |
| LLM Tool Schema Awareness | Native — policies target tool names and parameter shapes | None — requires custom Rego rules for each tool schema |
| Compliance Evidence | Provenance certificates ready for SOC 2 / ISO 27001 | Raw JSON decision logs — compliance packaging not provided |
| Deployment | SaaS control plane or self-hosted; CLI init in minutes | Self-hosted sidecar or standalone server |
Key Architecture Differences
OPA evaluates JSON documents against Rego policies, which works well for infrastructure authorization (e.g. Kubernetes admission control, API gateway rules). Writing Rego rules to handle the dynamic, nested parameter shapes produced by LLM tool calls — including handling hallucinated keys and partial JSON — quickly becomes difficult to maintain and audit.
Spctre uses a standardized declarative policy model designed around the AGT tool-call schema. Rules target tool names, parameter fields, and runtime context (agent identity, workspace, session budget) without requiring a custom query language. Policy changes are authored in the control plane, reviewed by your team, and published as versioned bundles — no Rego compilation step required. Every evaluation is recorded as a tamper-evident ledger entry, so you can replay any agent decision and prove exactly which policy revision authorized it.
When to Use OPA Instead
OPA is the right choice when your enforcement needs span infrastructure authorization beyond agents: Kubernetes admission webhooks, Envoy proxy rules, or existing API gateway policy pipelines that your team already manages in Rego. If your primary use case is governing what AI agents are allowed to do at runtime and producing compliance evidence for those decisions, Spctre is purpose-built for that problem.