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Agent Control Protocol: Admission Control for Agent Actions

Marcelo Fernandez · Mar 19, 2026 · Citations: 0

How to use this page

Low trust

Use this as background context only. Do not make protocol decisions from this page alone.

Best use

Background context only

What to verify

Read the full paper before copying any benchmark, metric, or protocol choices.

Evidence quality

Low

Derived from extracted protocol signals and abstract evidence.

Abstract

Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments. Before any agent action reaches execution, it passes a cryptographic admission check validating identity, capability scope, delegation chain, and policy compliance -- an admission control layer between agent intent and system state mutation. ACP defines cryptographic identity (Ed25519, JCS), capability-based authorization, deterministic risk evaluation (integer arithmetic, no ML inference), chained delegation, transitive revocation, and cryptographically-chained auditing. It operates on top of RBAC and Zero Trust, addressing what neither model solves: governing agent actions with deterministic enforcement, temporal limits, and full traceability across organizational boundaries. The protocol is compute-cheap but state-sensitive: decision evaluation costs ~820 ns while throughput reaches 920k req/s -- a separation enabling state backend replacement without modifying protocol semantics. Adversarial evaluation confirms ACP-RISK-2.0 enforcement holds under active evasion: 99% (495/500) single-agent evasion attempts are blocked after only five requests, per-agent isolation is preserved across 100 coordinated agents, and throughput degradation under stress is attributable to state-backend latency. The v1.19 specification comprises 38 technical documents, a Go reference implementation (23 packages), 73 signed conformance test vectors, 65 RISK-2.0 vectors, an OpenAPI 3.1.0 specification (18 endpoints), a TLC-checked TLA+ formal model (3 invariants, 0 violations), an ACR-1.0 sequence compliance runner, and adversarial evaluation scripts in compliance/adversarial/.

Abstract-only analysis — low confidence

All signals on this page are inferred from the abstract only and may be inaccurate. Do not use this page as a primary protocol reference.

  • This paper looks adjacent to evaluation work, but not like a strong protocol reference.
  • The available metadata is too thin to trust this as a primary source.
  • The abstract does not clearly describe the evaluation setup.
  • The abstract does not clearly name benchmarks or metrics.

Should You Rely On This Paper?

This paper is adjacent to HFEPX scope and is best used for background context, not as a primary protocol reference.

Best use

Background context only

Use if you need

Background context only.

Main weakness

This paper looks adjacent to evaluation work, but not like a strong protocol reference.

Trust level

Low

Usefulness score

0/100 • Low

Treat as adjacent context, not a core eval-method reference.

Human Feedback Signal

Not explicit in abstract metadata

Evaluation Signal

Weak / implicit signal

Usefulness for eval research

Adjacent candidate

Extraction confidence 15%

What We Could Verify

These are the protocol signals we could actually recover from the available paper metadata. Use them to decide whether this paper is worth deeper reading.

Human Feedback Types

missing

None explicit

No explicit feedback protocol extracted.

"Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments."

Evaluation Modes

missing

None explicit

Validate eval design from full paper text.

"Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments."

Quality Controls

missing

Not reported

No explicit QC controls found.

"Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments."

Benchmarks / Datasets

missing

Not extracted

No benchmark anchors detected.

"Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments."

Reported Metrics

missing

Not extracted

No metric anchors detected.

"Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments."

Human Feedback Details

  • Uses human feedback: No
  • Feedback types: None
  • Rater population: Not reported
  • Expertise required: General

Evaluation Details

  • Evaluation modes:
  • Agentic eval: None
  • Quality controls: Not reported
  • Evidence quality: Low
  • Use this page as: Background context only

Protocol And Measurement Signals

Benchmarks / Datasets

No benchmark or dataset names were extracted from the available abstract.

Reported Metrics

No metric terms were extracted from the available abstract.

Research Brief

Metadata summary

Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments.

Based on abstract + metadata only. Check the source paper before making high-confidence protocol decisions.

Key Takeaways

  • Agent Control Protocol (ACP) is a formal technical specification for admission control governance of autonomous agents in B2B institutional environments.
  • Before any agent action reaches execution, it passes a cryptographic admission check validating identity, capability scope, delegation chain, and policy compliance -- an admission control layer between agent intent and system state mutation.
  • ACP defines cryptographic identity (Ed25519, JCS), capability-based authorization, deterministic risk evaluation (integer arithmetic, no ML inference), chained delegation, transitive revocation, and cryptographically-chained auditing.

Researcher Actions

  • Compare this paper against nearby papers in the same arXiv category before using it for protocol decisions.
  • Check the full text for explicit evaluation design choices (raters, protocol, and metrics).
  • Use related-paper links to find stronger protocol-specific references.

Caveats

  • Generated from abstract + metadata only; no PDF parsing.
  • Signals below are heuristic and may miss details reported outside the abstract.

Recommended Queries

Research Summary

Contribution Summary

  • Agent Control Protocol (ACP) is a formal technical specification for governance of autonomous agents in B2B institutional environments.
  • ACP acts as an admission control layer between agent intent and system state mutation: before execution, every agent action must pass a cryptographic admission check that validates identity, capability scope, delegation chain, and policy…
  • ACP defines mechanisms for cryptographic identity, capability-based authorization, deterministic risk evaluation, verifiable chained delegation, transitive revocation, and immutable auditing, enabling autonomous agents to operate under…

Why It Matters For Eval

  • Agent Control Protocol (ACP) is a formal technical specification for governance of autonomous agents in B2B institutional environments.
  • ACP acts as an admission control layer between agent intent and system state mutation: before execution, every agent action must pass a cryptographic admission check that validates identity, capability scope, delegation chain, and policy…

Researcher Checklist

  • Gap: Human feedback protocol is explicit

    No explicit human feedback protocol detected.

  • Gap: Evaluation mode is explicit

    No clear evaluation mode extracted.

  • Gap: Quality control reporting appears

    No calibration/adjudication/IAA control explicitly detected.

  • Gap: Benchmark or dataset anchors are present

    No benchmark/dataset anchor extracted from abstract.

  • Gap: Metric reporting is present

    No metric terms extracted.

Related Papers

Papers are ranked by protocol overlap, extraction signal alignment, and semantic proximity.

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