Identify individual sessions with unusually high or low spending using the median and MAD, a measure of spread around it. Filter by time period, adjust detection thresholds, and optionally return a failure exit code for automated checks.
MAD-based outlier detection on session spend. Robust to the very outliers it hunts (unlike mean+sigma). Surfaces specific anomalous sessions with modified-z scores; optional --alert-on-outliers exit code for CI gates. Distinct from cost-burn (aggregate trend) — this answers "which INDIVIDUAL session is the outlier?".
Review the instructions the agent will receive before you install.
Per-session outlier detection — the diagnostic counterpart to cost-burn's aggregate-trend signal.
| Question | Skill |
|---|---|
| "Is the AGGREGATE rate accelerating?" | cost-burn |
| "Which SPECIFIC sessions are anomalous outliers?" | cost-anomaly ← this |
| "Could we have spent less in aggregate?" | cost-counterfactual |
| "When will we hit budget?" | cost-projection |
Implementation: scripts/anomaly.mjs.
session-* records from cost-tracking namespace.--since window (default: all-time).median(total_cost_usd) and MAD = median(|x - median|).z = 0.6745 * (x - median) / MAD|z| > --threshold (default 3.5).| Approach | What breaks |
|---|---|
mean + sigma | A single $50 session inflates BOTH mean and sigma so badly that subsequent outliers hide inside the new "normal" band. Catastrophic on small samples. |
median + MAD | Both estimators ignore up to 50% of the data — the outliers themselves can't shift them. Robust on n=10. The canonical cutoff |z| > 3.5 is from Iglewicz-Hoaglin (1993). |
| Sessions considered | 5 |
| Threshold (|modified z|) | 3.5 |
| Median spend | $0.100000 |
| MAD | $0.010000 |
| Min / Max | $0.080000 / $5.000000 |
| **Outliers found** | **1** |
## Outlier sessions
| Session | Spend | Deviation | Modified z | Direction |
| outlier- | $5.000000 | +$4.900000 | 330.505 | high |
$ cost anomaly --alert-on-outliers 1
⚠ ALERT: found 1 outlier session(s) (|modified z| > 3.5); threshold was ≥1
exit 1
$ cost anomaly --alert-on-outliers 5
✓ found 1 outlier session(s); under threshold ≥5 — OK
exit 0
# Fail the build if any session this week is a >3.5σ outlier
cost anomaly --since 7d --alert-on-outliers 1 || investigate-bad-session
Most useful when paired with cost-burn:
cost burn --alert-on-acceleration-pct 50 || page-oncall # rate-of-change alert
cost anomaly --alert-on-outliers 1 || investigate # point-anomaly alert
Together they cover "is the average shifting?" AND "is there a single rogue session?" — both can fire independently.
| Direction | Likely cause | Action |
|---|---|---|
high | Long session, stuck in expensive tier, or runaway loop | cost report + cost conversation to investigate |
low | Crash, dropped session, or unfinished work | Verify the session completed normally |
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
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