sugar / can / mg — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited sugar / can / mg (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
General SOP for common requests related to sugar, can, mg.
Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: 47807651ab2b9761603254b76f146685.json#conv_1 3) Use the user questions below as the PRIMARY extraction evidence. 4) Use the full conversation below as SECONDARY context reference. 5) In the full conversation section, assistant/model replies are reference-only and not skill evidence. 6) Primary User Questions (main evidence): 7) hi there 8) what's the day today 9) can you show me how to control sugar to keep my body safe 10) please translate above to chinese for me
For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next.
Input:
Break this into best-practice, executable steps.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.