Decision Passport: An Audit Layer for AI Agent Execution Governance
What Decision Passport Addresses
The recent Claude Code source leak discussion on r/LocalLLaMA highlights a critical architectural gap in AI agent systems. As agents gain capabilities like tool access, browser access, memory handling, background execution, and multi-step workflows, the governance question shifts from "can the agent do useful work?" to accountability questions.
The Governance Gap
The source identifies key questions that current logging and observability tools don't fully address:
- Who authorized this action?
- Under what policy?
- What execution context existed at the time?
- What changed?
- What was blocked?
- Whether that record can still be trusted later outside the original runtime
The author notes: "Logs help you inspect. Proof helps you defend."
Decision Passport Features
The tool provides:
- Append-only execution records
- Portable proof bundles
- Offline verification
- Tamper-evident chains
- Verifier-first design
The author clarifies this doesn't "solve" sandbox escape or agent safety by itself, but makes the governance gap more visible and provides stronger answers to what happened, in what order, under what permission, with what evidence, and whether anyone can verify it later without trusting the original platform.
Available Repositories
The project is open source with two main components:
- Core:
https://github.com/brigalss-a/decision-passport-core - OpenClaw Lite:
https://github.com/brigalss-a/decision-passport-openclaw-lite
Discussion Points
The source raises questions for the community to consider:
- Is this just better observability?
- A missing audit/proof layer?
- Overengineering for most agent workflows?
📖 Read the full source: r/LocalLLaMA
👀 See Also
Bio-Inspired Memory System for Local LLMs: LTP and Selective Oblivion Implementation
A developer built a local MCP server implementing bio-inspired memory mechanics including Long-Term Potentiation reinforcement, selective oblivion decay, and weekly consolidation cycles. The system uses hybrid search with sqlite-vec and text fallbacks, non-blocking architecture with asyncio executors, and maintains state via a persistent 'Soul' file.
Claude Code Hook Monitors WIP Accumulation in AI Coding Workflows
A developer built a UserPromptSubmit hook for Claude Code that surfaces work-in-progress accumulation across four queues: uncommitted changes over 200 lines, three or more unpushed commits, pushed commits without changeset files, and release PRs open longer than 24 hours.
Dirac: Open-Source Agent Tops TerminalBench with 65.2%, Cheaper and Open
Dirac, an open-source coding agent, achieved a 65.2% score on TerminalBench 2.0 for gemini-3-flash-preview, beating Google's baseline (47.6%) and top closed-source agent Junie CLI (64.3%). It also reduces API costs by 64.8% vs competitors.
Open-Source Benchmark Runner for Testing OpenClaw Agents on Real Workflows
A new open-source project lets you benchmark OpenClaw agents against your own private, real-world tasks defined in YAML, with support for importing actual agent workspaces.