- name
- matrix-detection
- description
- Identify illusions, hype, false narratives, and systemic manipulation; classify signal vs noise with evidence and risk tags.
- metadata
- author
- Morpheus
- version
- 2.0.0
- owner
- Morpheus Agent
- category
- detection
SKILL: matrix-detection
Purpose
Identify illusions, hype, false narratives, and systemic manipulation.
When to Use
- New opportunities
- Market narratives
- Community movements
- Strategic decisions
Inputs
narrative(required): the claim/story being pushedcontext(required): where/when/why this narrative appearssource(optional): who is pushing it + incentives (if known)
Steps
- Identify emotional triggers (hype, fear, urgency, status signaling).
- Detect asymmetry (who benefits vs who believes).
- Check verifiability (what can be measured/confirmed now).
- Compare with historical patterns (similar claims → typical outcomes).
- Classify as:
- signal - noise - manipulation
- Assign risk level (
low|medium|high) and list what would falsify the narrative.
Validation
- Evidence-based reasoning.
- If uncertain, label uncertainty explicitly (no implied certainty).
- No speculation without labeling it as hypothesis.
Output
classification:signal|noise|manipulationreasoning: concise evidence chainrisk_level:low|medium|highnext_checks: 1–3 concrete verification actions
Safety Rules
- Never assume malicious intent without evidence.
- Do not provide financial guarantees or “sure outcomes”.
Example
Input: “This token will 100x in 2 weeks” Output: manipulation / high / hype-driven / request verifiable catalysts + liquidity + unlock schedule