Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add skynetcmd/m3-memory --skill m3-healthgit clone --depth 1 https://github.com/skynetcmd/m3-memoryWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/skynetcmd/m3-memory/m3-health)<a href="https://agentmods.dev/skills/skynetcmd/m3-memory/m3-health"><img src="https://agentmods.dev/badge/skills/skynetcmd/m3-memory/m3-health/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/skynetcmd/m3-memory/m3-health"><img src="https://agentmods.dev/badge/skills/skynetcmd/m3-memory/m3-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.00468 |
| Opus 5 | $0.00012 | $0.00234 |
| Sonnet 5 | $0.00005 | $0.00094 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
m3-health scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
M3 Health
When to Use
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.
Instructions
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/Linux
Step 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.
Step 4 — if (and only if) doctor reported a repairable problem (a stale/dead agent
config path, a duplicate bridge, a disabled plugin, or a "run doctor --fix" hint),
OFFER to auto-repair. doctor --fix repoints dead config paths, de-duplicates MCP
registrations, and re-syncs agent hooks — it is non-destructive to data. Run the
same resolver that worked above, with --fix:
mcp-memory doctor --fix
# or: python -m m3_memory.cli doctor --fix
Then re-run plain doctor to confirm the fix took. If doctor was already all
healthy, do NOT run --fix.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 47 lines · 24 tokens per session scan A ba7029b9a0bb
m3-health is a skill published in the GitHub repository skynetcmd/m3-memory (24 stars, last pushed today), licensed Apache-2.0. It adds 24 tokens to every session and 468 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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