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Signal vs Noise
作者
Mauricio Z.
· GitHub ↗
· v2.0.0
· MIT-0
149
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install signal-vs-noise
功能描述
Filter relevant information from noise; extract claims, dedupe, rank impact, and preserve evidence.
安全使用建议
This skill appears coherent and low-risk in structure, but remember: it will process whatever dataset you give it. Before using it on sensitive material, (1) test with non-sensitive/sample data to confirm outputs and evidence formatting, (2) avoid feeding secrets or private identifiers you don't want preserved in evidence pointers, and (3) confirm you trust the skill owner (owner id appears generic). If you plan to run this in an environment where agent outputs are logged or shared, consider redacting sensitive fields upstream.
功能分析
Type: OpenClaw Skill
Name: signal-vs-noise
Version: 2.0.0
The skill bundle is a text-processing utility designed to filter and rank information from a provided dataset. It contains no executable code, network requests, or instructions to access sensitive system resources or environment variables. The logic in SKILL.md and signal-vs-noise.md is entirely focused on data normalization, claim extraction, and deduplication within the provided input context, with no evidence of malicious intent or prompt-injection attacks.
能力标签
能力评估
Purpose & Capability
The skill's name and description (filtering signals from noise) align with the SKILL.md steps (normalization, claim extraction, dedupe, ranking, evidence preservation). No unrelated capabilities, binaries, or credentials are requested.
Instruction Scope
The instructions are narrowly scoped to processing a provided dataset and producing ranked signals and a noise bucket. They do not instruct the agent to read system files, call external endpoints, or access environment variables. Note: because the skill preserves evidence (source/item ids), users should avoid supplying datasets that contain secrets or PII they don't want recorded or shared.
Install Mechanism
There is no install spec and no bundled code—this is instruction-only, which means nothing is written to disk or fetched during install.
Credentials
The skill requests no environment variables, credentials, or config paths. The requested surface is proportionate to the stated functionality.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request permanent presence or elevated privileges and does not modify other skills or system-wide settings.
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 signal-vs-noise - 安装完成后，直接呼叫该 Skill 的名称或使用
/signal-vs-noise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
v2.0.0
signal-vs-noise version 2.0.0 is a major update with a formalized filtering and ranking workflow.
- Adds clear input/output formats and step-by-step filtering process.
- Introduces evidence preservation, deduplication, and impact-based ranking of signals.
- Includes validation checks for duplicate removal and evidence requirements.
- Provides usage examples and explicit safety/bias rules.
- Updates description and usage guidance for better clarity.
v1.0.0
- Initial release of signal-vs-noise skill.
- Helps users distinguish real progress from performative activity.
- Focuses on filtering for informed insights, structural value, and genuine intelligence.
- Aims to protect users from information overload and highlight meaningful content.
元数据
常见问题
Signal vs Noise 是什么？
Filter relevant information from noise; extract claims, dedupe, rank impact, and preserve evidence. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 149 次。
如何安装 Signal vs Noise？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install signal-vs-noise」即可一键安装，无需额外配置。
Signal vs Noise 是免费的吗？
是的，Signal vs Noise 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Signal vs Noise 支持哪些平台？
Signal vs Noise 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 Signal vs Noise？
由 Mauricio Z.（@mzfshark）开发并维护，当前版本 v2.0.0。
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