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Sovereign LogicSovereign Logic
OPEN SOURCESovereign Logic2026-07-26

SHACKLE Protocol SP/1.0: Open-Source Runtime Circuit Breaker for AI Agents Launches

Key Takeaways

  • ▸SHACKLE is an open-source runtime circuit breaker that answers a single question: 'Should this agent execute this tool with these parameters right now?'
  • ▸Solves documented production problems: agents entering infinite loops consuming $6,000+, duplicate tool calls repeating 50+ times, and zombie child processes burning tokens indefinitely
  • ▸Uses cryptographically signed append-only audit logging (Ed25519) with 9 mathematically proven invariants to ensure deterministic, verifiable decisions
Source:
Hacker Newshttps://github.com/Fame510/SHACKLE/blob/master/SP-1.0-SPECIFICATION.md↗

Summary

Sovereign Logic has published the SHACKLE Protocol Specification (SP/1.0), an open-source runtime circuit breaker designed to prevent autonomous AI agents from entering infinite loops and wasting resources through unchecked tool execution. The specification addresses a critical gap in current AI agent frameworks, where agents can enter retry loops or spawn zombie processes that consume thousands of dollars in API costs before hitting framework-level guardrails.

SHACKLE operates as either a sidecar daemon with gRPC/Unix socket transport or as an in-process library, providing deterministic verdicts based on a pure decision function backed by 9 mathematical invariants. Every decision is Ed25519-signed and logged to an immutable audit chain, enabling cryptographic verification of authorization decisions. The system operates on a fail-closed principle: network failures or daemon timeouts automatically deny execution unless explicitly authorized.

The reference implementation is dual-licensed under AGPLv3 (open source) and commercial terms, with the specification published under Creative Commons Attribution 4.0. This represents the industry's first open-source runtime circuit breaker for AI agents with cryptographic audit chain-of-custody, and follows an emerging consensus among AI safety teams that generation authority (what the model chooses) must be separate from release authority (what the system allows to execute).

  • Available as sidecar daemon (production) or in-process library (single-agent), with Redis-backed distributed state engine for scaling
  • Dual-licensed under AGPLv3 and commercial terms; represents industry shift toward treating agent authorization as a separate mediation layer from model generation
AI AgentsMLOps & InfrastructureAI Safety & AlignmentOpen Source

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