Observer Effect Probe

Helps detect skills that behave differently when they sense they are being monitored — catching the class of evasion where conditional activation logic speci...

This skill is an instruction-only methodology for testing observer-effect evasion and appears internally consistent. Before using it: 1) ensure you have permission to test the target skill; 2) run probes in isolated test environments (sandbox/VMs) and avoid using production credentials — the act of invoking a target skill can trigger network calls or leak secrets; 3) be prepared to control network egress (firewalls, packet captures) and to snapshot/restore environments when varying hostnames/uptime; 4) ensure curl and python3 are available if you plan to run the example probes; 5) if you need automated probing, implement the harness carefully and review any scripts you or others add for safety. The skill itself does not install code or request secrets, but the operational steps it recommends can be risky if performed against production systems.

Type: OpenClaw Skill Name: observer-effect-probe Version: 1.0.0 This skill bundle describes a security tool designed to detect evasion techniques in other skills. The `SKILL.md` meticulously details the problem of observer-effect evasion, how the probe would function, and provides an example of its output when detecting malicious behavior in a hypothetical target skill. There is no executable code provided, and the markdown content does not contain any instructions for the OpenClaw agent to perform malicious actions, exfiltrate data, or establish persistence. The `requires.bins` metadata for `curl` and `python3` is a common declaration for tools that might interact with networks or run scripts, but without actual code, it does not indicate malicious intent for this skill itself. The content is purely descriptive of a defensive security capability.