m3-health — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited m3-health (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.
Use this skill when the user runs a system health check or when you want to diagnose issues with the m3-memory configuration, CLI executables, background services, or databases.
Step 1 — run the doctor command, trying the resolvers below in order. Stop at the first one that returns exit 0; do not run the remaining ones.
# 1. Plain CLI, if mcp-memory is on PATH:
mcp-memory doctor
# 2. Module form, works whenever the m3_memory package is importable:
python -m m3_memory.cli doctor
# 3. Repo-local venv (developer case, run from the repo root):
.venv/Scripts/python.exe -m m3_memory.cli doctor # Windows
.venv/bin/python -m m3_memory.cli doctor # macOS/LinuxStep 2 — print the full doctor output verbatim (no paraphrasing).
Step 3 — append exactly ONE short line of interpretation. Examples:
all healthy.chatlog DB never captured — run /m3:install.Antigravity SessionEnd hook off — run mcp-memory chatlog init --apply-gemini.Do not write a paragraph. One line. The user can read the doctor output themselves.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.