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WAIL v1.3 — Execution Control & Governance Evidence
Official Verification & Evidence Repository
WAIL is an AI, Agent & MCP Execution Control & Governance Layer designed to observe, control, govern, and verify AI execution across models, agents, and MCP tools.
Control what you can’t control. Prove what actually happened.
This repository is the evidence publication destination for WAIL v1.3, including execution traces, governance enforcement evidence, cryptographic verification records, and reproducible test reports.
Explore WAIL:
- WAIL Verification Lab — Technical verification overview.
- Official Website — Product and platform information.
- GitHub Runtime — Public developer runtime.
Execution Control & Governance
WAIL operates around existing AI applications without replacing their orchestration frameworks or requiring a gateway.
Its execution lifecycle follows:
OBSERVE → DETECT → DECIDE → ACT → VERIFY → PROVE
Key capabilities include:
- Runtime observability, anomaly detection, and behavioral baselines.
- Controlled observe, retry, and reroute actions.
- Agent, model, and MCP execution tracking.
- Continuous Governance Enforcement across active executions.
- Cryptographically signed evidence and chronological governance records.
- On-premises and private-cloud deployment architecture.
Verification Domains
V-01 — Mid-Execution Governance Enforcement
Verification of authorization and policy changes during active execution, including REVOKE handling, intervention in affected operations, and prevention of unauthorized subsequent dispatch.
Evidence must distinguish local enforcement from independently confirmed remote termination.
V-02 — Agent, MCP & Model Execution
Verification of connected execution relationships across Agent Runs, MCP tool operations, and model requests, including chronological evidence and signed audit records.
V-03 — Controlled Runtime Recovery
Verification of controlled retry and reroute behavior, provider transitions, execution authority, and observable recovery outcomes.
V-04 — Signed Evidence & Ledger Integrity
Verification of cryptographic signatures, evidence chronology, ledger linkage, checkpoint integrity, and trusted-head validation within the documented trust model.
Evidence Publication
Verification packages are organized by domain and may include:
- Test reports and execution summaries.
- Sanitized execution traces and signed records.
- Cryptographic manifests and SHA-256 checksums.
- Verification scripts and reproduction instructions.
- Explicit verification scope, limitations, and results.
A verification claim is supported only by the artifacts and checks documented in its corresponding evidence package.
A recorded decision is not proof of enforcement.
Verification Principles
WAIL distinguishes between:
- A control decision.
- An attempted action.
- An observed local enforcement outcome.
- An independently verified remote outcome.
These states must not be represented as equivalent without supporting evidence.
Hugging Face Verification Architecture
WAIL maintains two complementary resources on Hugging Face.
Verification Lab — Technical Presentation
Provides an accessible overview of WAIL's execution control architecture, governance enforcement, verification domains, and evidence methodology.
Evidence Repository — Technical Artifacts
Serves as the repository for version-specific verification artifacts, integrity manifests, test reports, and reproduction instructions.
The Verification Lab presents the technical context; the Evidence Repository provides the underlying artifacts for independent inspection.
Resources
- Official website: https://wailinfra.com
- GitHub: https://github.com/wailinfra/wail-runtime
- PyPI: https://pypi.org/project/wail-runtime/
- Hugging Face Verification Lab: https://huggingface.co/spaces/wail-runtime/wail-verification-lab
- WAIL v1.3 Evidence Dataset: https://huggingface.co/datasets/wailinfra/wail-v1.3-evidence
WAIL — AI, Agent & MCP Execution Control & Governance Layer
This repository is dedicated to verifiable technical evidence, not marketing-only performance claims.
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