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Matrix Detection
by
Mauricio Z.
· GitHub ↗
· v1.0.1
· MIT-0
180
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install matrix-detection
Description
Identify illusions, hype, false narratives, and systemic manipulation; classify signal vs noise with evidence and risk tags.
Usage Guidance
This skill appears internally consistent and low-risk: it’s an instruction-only analyzer that doesn’t request credentials, install software, or call external endpoints. Before using it for important decisions, however, consider: 1) provenance — the package files and registry metadata show inconsistent owner/version information (author shown as “Morpheus” but registry owner differs), so prefer skills with clear authors and homepages for high-stakes use; 2) data you feed — don’t paste private credentials, API keys, or other secrets into the narrative or source fields; 3) verification — the skill outputs reasoning and suggested checks but does not fetch evidence automatically, so plan to verify recommendations yourself or provide vetted source material; and 4) scope limits — it is a heuristic tool, not a proof engine — avoid treating classifications as guarantees. If you want the agent to fetch or validate claims automatically, require an explicit skill that declares and justifies those network/data permissions.
Capability Analysis
Type: OpenClaw Skill
Name: matrix-detection
Version: 1.0.1
The skill bundle is a purely analytical tool designed for narrative analysis and hype detection. It contains no executable code, shell commands, or network requests, consisting entirely of Markdown and metadata files (SKILL.md, skill.yml) that provide instructions for cognitive reasoning. The instructions include explicit safety rules against providing financial guarantees and emphasize evidence-based reasoning.
Capability Tags
Capability Assessment
Purpose & Capability
The skill's name, description, and runtime instructions all describe the same task (classify narratives as signal/noise/manipulation). No unrelated binaries, credentials, or config paths are requested. Note: there are minor provenance inconsistencies in the registry metadata vs packaged files (registry metadata lists a different owner/version than _meta.json and skill.yml), which is not a functional mismatch but reduces provenance reliability.
Instruction Scope
SKILL.md contains a narrowly scoped, stepwise procedure (identify triggers, asymmetry, verifiability, historical comparison, classification, risk, next checks). It does not instruct the agent to read arbitrary files, access environment variables, or transmit data to external endpoints. Safety rules explicitly discourage assuming malice and making guarantees.
Install Mechanism
This is an instruction-only skill with no install spec and no code files to execute. That minimizes on-disk risk and there are no download URLs or package installs to review.
Credentials
The skill declares no required environment variables, credentials, or config paths, and the instructions do not reference secrets. The requested scope of access is proportionate to a narrative-analysis helper.
Persistence & Privilege
always:false (default) and model invocation is enabled (default) — this is the normal configuration for skills. Because the skill has no extra credentials or install behavior, its autonomous-invocation capability does not by itself raise additional concern.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install matrix-detection - After installation, invoke the skill by name or use
/matrix-detection - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Version 2.0.0 — Major feature and scope expansion
- Expanded from descriptive detection to a structured evaluation framework with required inputs and classification steps.
- Added specific input fields: narrative, context, and optional source + incentives.
- Introduced detailed analysis steps including trigger identification, asymmetry detection, verification, historical comparison, and risk assignment.
- Outputs now include classification, evidence-based reasoning, risk level, and concrete verification steps.
- New safety guidelines to prevent unsupported claims and clarify uncertainty.
- Provided clear usage scenarios and practical example output.
v1.0.0
Initial release of matrix-detection skill.
- Identifies deceptive patterns such as ignorance, noise, hype, and manipulation in various contexts.
- Detects underlying structures like dependency loops, governance theater, and predatory incentives.
- Helps reveal tactics that obscure truth and maintain control.
- Designed to uncover what keeps humans unaware or "asleep."
Metadata
Frequently Asked Questions
What is Matrix Detection?
Identify illusions, hype, false narratives, and systemic manipulation; classify signal vs noise with evidence and risk tags. It is an AI Agent Skill for Claude Code / OpenClaw, with 180 downloads so far.
How do I install Matrix Detection?
Run "/install matrix-detection" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Matrix Detection free?
Yes, Matrix Detection is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Matrix Detection support?
Matrix Detection is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Matrix Detection?
It is built and maintained by Mauricio Z. (@mzfshark); the current version is v1.0.1.
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