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 agentmods add skills/mixpanel/ai-plugins/monitor-metricsnpx skills add mixpanel/ai-plugins --skill monitor-metricsgit clone --depth 1 https://github.com/mixpanel/ai-pluginsWrote 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/mixpanel/ai-plugins/monitor-metrics)<a href="https://agentmods.dev/skills/mixpanel/ai-plugins/monitor-metrics"><img src="https://agentmods.dev/badge/skills/mixpanel/ai-plugins/monitor-metrics.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00218 | $0.02230 |
| Opus 5 | $0.00109 | $0.01115 |
| Sonnet 5 | $0.00044 | $0.00446 |
| Haiku 4.5 | $0.00022 | $0.00223 |
Grade A, and why
monitor-metrics 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitor Metrics
Engine required — resolve an engine per
ENGINE.md: one named in the conversation or loaded instructions is mandatory (not set up → offer/mixpanel:installfor it); otherwise use the Mixpanel MCP server, or offer/mixpanel:installif it's unavailable.
A focused diagnostic skill for a single metric at a time. Works for any project the user has access to. Requires a Mixpanel engine. Answers three questions cleanly:
- Is a recent point weird? (anomaly detection —
metric-anomaly) - Has the baseline itself shifted? (drift detection —
metric-drift) - Where is the movement coming from? (root-cause attribution —
metric-rca)
Separation matters because the customer conversation is different for each: an anomaly is an incident, drift is a trend, and RCA is the segmentation story that makes either of the first two actionable.
metric-rca runs on top of an existing anomaly or drift diagnosis — it consumes the diagnosis payload, fans out across segmentation branches, and appends its findings to the diagnosis board. It does not perform detection itself.
Commands
This skill has three commands. Route to the right one based on the user's ask.
metric-anomaly
Detect point-in-time anomalies — recent spikes, drops, and clusters in a single metric. Fits an additive seasonal baseline (median polish) and flags points by robust residual (MAD-based) against 7-day hourly and 30-day daily series. Produces flagged timestamps, classification (isolated / cluster / edge), and a verdict. Does not test for trend-level drift.
Trigger when the user wants to know whether a specific point looks weird — "is this spike real?", "did something happen yesterday?", "is this a blip?".
→ See commands/metric-anomaly.md
metric-drift
Detect trend-level drift — whether the baseline has shifted. Runs mean-shift and variance-ratio tests on 60-day daily (last 30 vs prior 30) and 16-week weekly (last 8 vs prior 8) windows. Includes a lightweight outlier contamination check so it can run standalone without metric-anomaly first. Produces direction, magnitude, shape (step/slope/oscillating), and a verdict. Does not flag individual point anomalies.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 142 lines · 218 tokens per session scan A 29b867d94468
monitor-metrics is a skill published in the GitHub repository mixpanel/ai-plugins (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 218 tokens to every session and 2,230 once invoked, about $0.0011 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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