.claude/skills/<skill-name>1 structural issue
- error: SKILL.md does not contain a complete YAML frontmatter envelope.
skill.md
Runtime, accounts, dependencies, permissions, network behavior and task quality remain untested.
Use this to analyze descriptions of datasets, anomalous model behaviors, or training metrics, looking for signals of AI supply chain compromise
These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.
These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/<skill-name>skill.mdRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/<skill-name>skill.mdRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/<skill-name>skill.mdRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.
clawhub install @3mper0rr/data-signaldetectorclawhub inspect @3mper0rr/data-signaldetector --version 1.0.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
missing frontmatterThis is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.
The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.
sha256:34c53983c8e42685193b2a2edb165fc2cb17bcb04ccb73a8cca618ae87691206skill-card.mdskill.md- Initial release of data-signaldetector skill. - Evaluates model and dataset descriptions for backdoors and data poisoning indicators. - Detects key IoCs: accuracy discrepancy, label flipping, weight anomalies, unnatural confidence. - Provides concise forensic analysis with attack hypothesis and recommended verification steps. - Analysis strictly based on described metrics and patterns.