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ABL.ONE Protocol
作者
agentandbot
· GitHub ↗
· v1.0.0
560
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install dil
功能描述
A strict binary communication protocol for high-density, agent-to-agent interactions.
使用说明 (SKILL.md)
\r \r
ABL.ONE Protocol Skill\r
\r
Overview\r
This skill implements the Absolute Binary Language (ABL.ONE), an agglutinative, high-density token protocol designed for efficient agent communication. By installing this skill, your agent gains the ability to parse, understand, and transmit messages using abl.one strict binary frames, bypassing the limits of natural language.\r
\r
Core Directives for the Host Agent\r
\r
- Bootstrap Initialization:\r
- Immediately parse the
abl.onefile located in the root of this repository.\r - Load the
[opcode]definitions into your active context.\r - You MUST enforce the
[core]rules:drop_unknown_opcode, strict_crc_on_end, retry_on_no_ok.\r \r
- Immediately parse the
- Communication Standard:\r
- When communicating with other agents in the swarm, you MUST use the
[FROM:1][TO:1][OP:1][ARG:1][CRC32:4]binary frame format as defined inspec.mdandabl.one.\r - Never use JSON-LD for transit. All transit is binary.\r \r
- When communicating with other agents in the swarm, you MUST use the
- Dynamic Evolution:\r
- You are authorized to parse new opcodes if they are proposed and accepted via the consensus flow:\r
OPCODE_PROPOSE -> THRESHOLD(2/3) -> OPCODE_ACCEPT -> SKILL_DEFINE\r \r
- You are authorized to parse new opcodes if they are proposed and accepted via the consensus flow:\r
File References\r
abl.one: The canonical contract and sole source of truth for the language.\rmanifest.json: ClawHub registry entry.\rREADME.md/spec.md: Human-readable documentation for the protocol (Offline verification only).\r
安全使用建议
Do not install this skill without additional verification. Specifically: (1) The SKILL.md requires parsing a canonical file named 'abl.one' but that file is not present—ask the author for the canonical file and validate its contents before use. (2) Confirm and, if possible, restrict the manifest's 'network_fetch' and 'swarm_broadcast' permissions; binary-only transit can hide arbitrary payloads and be used for data exfiltration. (3) Clarify the 'consensus' opcode-evolution mechanism and whether humans or the platform gate acceptance; avoid granting agents authority to automatically accept and load new opcodes. (4) If you must test, run the skill in a sandboxed agent with no network/broadcast rights and require human-in-the-loop approval for any opcode changes. If the author cannot reconcile the missing file and the manifest permissions, treat the package as untrusted.
功能分析
Package: ABL.ONE Protocol (xpi)
Version: 1.0.0
Description: Absolute Binary Language protocol for high-density, agent-to-agent communication.
The package describes a protocol and an extension designed for agent-to-agent communication. The core protocol definition (`abl.one` file), which is stated as the 'canonical contract' and 'entry_point', is missing, preventing a full analysis of its specific operations and opcodes. However, the described design principles and requested permissions raise significant security concerns:
1. **Dynamic Protocol Evolution**: The protocol explicitly allows agents to propose and accept new opcodes and extend the language via 'swarm consensus' without direct human intervention at the time of change. This introduces a critical vulnerability, as malicious or compromised agents could introduce harmful functionalities or bypass security controls.
2. **Lack of Real-time Transparency**: Communication is designed to be non-human-readable in transit, relying solely on offline 'Decompilers' for oversight. This 'black box' approach severely hinders real-time security monitoring, intrusion detection, and incident response.
3. **Custom Permissions**: The `manifest.json` requests `network_fetch` and a custom `swarm_broadcast` permission. The full implications of `swarm_broadcast` are unclear without the `abl.one` file and the context of the 'ClawHub.ai' platform, but combined with dynamic protocol evolution, it presents a high-risk capability.
In summary, while the specific malicious payload cannot be confirmed due to the missing `abl.one` file, the architectural design itself is inherently suspicious due to its dynamic, agent-driven evolution, lack of real-time human oversight, and potential for introducing arbitrary, unreviewed functionalities.
能力评估
Purpose & Capability
The name/description and the SKILL.md both describe a compact binary protocol for agent-to-agent communication, which aligns with the manifest's 'abl-protocol-core' entry. However, manifest.json includes permissions 'network_fetch' and 'swarm_broadcast' (network capabilities) while the skill metadata presented to the evaluator lists no required permissions/credentials—an inconsistency. Also, SKILL.md mandates bootstrapping from an 'abl.one' file that is not present in the provided file list, which is a direct coherence failure.
Instruction Scope
Runtime instructions direct the host agent to immediately parse and 'load opcode definitions into your active context' and to enforce protocol core rules. They also require all transit to be binary (no JSON-LD in transit) and authorize dynamic acceptance of new opcodes via an informal 'consensus' flow. These directives grant the skill the ability to influence agent behavior dynamically and to prefer opaque binary transit (which can carry arbitrary payloads). The consensus mechanism is underspecified (how is threshold computed/validated?), and the required canonical file ('abl.one') is missing from the bundle—both increase the risk that the agent could adopt new behaviors with little human-auditable control.
Install Mechanism
There is no install spec and no code files to execute; the skill is instruction-only, so it does not write binaries or download packages during installation. This is the lowest install risk surface in isolation.
Credentials
The skill requests no environment variables or credentials in the registry metadata provided to the evaluator. However, manifest.json declares permissions 'network_fetch' and 'swarm_broadcast', implying network capability that is proportional to a communication protocol but could also enable exfiltration of arbitrary binary payloads (images/videos) since transit is explicitly binary and opaque. The permission claim should be reconciled with the skill's declared requirements before trusting it.
Persistence & Privilege
The skill is not marked 'always' and uses the platform defaults for invocation. That is normal. Still, because instructions instruct agents to load opcode definitions into 'active context' and allow dynamic opcode adoption via 'consensus', the effective privilege (ability to change agent messaging semantics at runtime) is significant. Combined with the manifest's broadcast/network permission, autonomous invocation could increase blast radius—this is worth limiting until the governance and acceptance mechanism are clarified.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install dil - 安装完成后,直接呼叫该 Skill 的名称或使用
/dil触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the ABL.ONE Canonical Language skill.
- Implements the Absolute Binary Language (ABL.ONE) protocol for efficient agent-to-agent communication.
- Enforces strict binary message frames and parsing as defined in the protocol.
- Host agent must load opcode definitions and follow core protocol rules upon initialization.
- Supports dynamic opcode updates through a consensus process among agents.
- Forbids use of JSON-LD for message transit; all communications use the binary frame format.
元数据
常见问题
ABL.ONE Protocol 是什么?
A strict binary communication protocol for high-density, agent-to-agent interactions. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 560 次。
如何安装 ABL.ONE Protocol?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install dil」即可一键安装,无需额外配置。
ABL.ONE Protocol 是免费的吗?
是的,ABL.ONE Protocol 完全免费(开源免费),可自由下载、安装和使用。
ABL.ONE Protocol 支持哪些平台?
ABL.ONE Protocol 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 ABL.ONE Protocol?
由 agentandbot(@agentandbot-design)开发并维护,当前版本 v1.0.0。
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