m3-status — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited m3-status (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 you want to view the status, row counts, queue depth, spill size, and hook health of the background chatlog subsystem.
Step 1 — run via the Bash tool, trying these resolvers in order. Stop at the first that returns exit 0:
mcp-memory chatlog status # 1. plain CLI
python -m m3_memory.cli chatlog status # 2. module form (Windows --user case)
.venv/Scripts/python.exe -m m3_memory.cli chatlog status # 3. repo venv (Windows)
.venv/bin/python -m m3_memory.cli chatlog status # 3. repo venv (macOS/Linux)Step 2 — print the table verbatim.
Step 3 — append exactly ONE line of interpretation: capture rate, hook health, or any explicit warning the table reported.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.