mlsanityData to 14 Oct 2026

Property-Level Reconstructability of Agent Decisions: An Anchor-Level Pilot Across Vendor SDK Adapter Regimes

arXiv 2605.12078 ↗First posted 12 May 2026cs.SE cs.AIcited by 0

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Agentic AI failures need post-hoc reconstruction: what the agent did, on whose authority, against which policy, and from what reasoning. Cross-regime feasibility remains unmeasured under one property-level schema. We apply the Decision Trace Reconstructor unmodified to pinned worked-example anchors from six public vendor SDK regimes spanning cloud-agent, observability, tool-use, telemetry, and protocol traces, plus two comparator columns. Each Decision Event Schema (DES) property is classified as fully fillable, partially fillable, structurally unfillable, or opaque. Per-property reconstructability of an agent decision already varies between regimes at this anchor scale. Strict-governance-completeness separates into three tiers ranging from 42.9% to 85.7%, yielding one regime-independent gap (reasoning trace), four regime-dependent gaps, and one Mixed property; the pilot is single-annotator, one anchor per cell, descriptive, with outputs checksum-verifiable from a deposited reproducibility package.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 4 of its 12 references that are in the map. First posted on arXiv 12 May 2026.

Builds on

4 of 12 references.

References · 4

  1. 2026Towards a Science of AI Agent Reliabilitycited by 65
  2. 2026CodeTracer: Towards Traceable Agent Statescited by 16
  3. 2026Detecting Safety Violations Across Many Agent Tracescited by 14
  4. 2026Governance-Aware Agent Telemetry for Closed-Loop Enforcement in Multi-Agent AI Systemscited by 1

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  5. 2026DNative-Twin: Decision Graphs and Digital Twins for Reconstructable Agentic Decisions
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  7. 2026Reasoning Provenance for Autonomous AI Agents: Structured Behavioral Analytics Beyond State Checkpoints and Execution Traces
  8. 2026From Traceability to Justifiability: Accountability Structures in Agentic Software Engineering