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 sukirman1901/frontend-expert --skill monitoringgit clone --depth 1 https://github.com/sukirman1901/frontend-expertWrote 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/sukirman1901/frontend-expert/monitoring)<a href="https://agentmods.dev/skills/sukirman1901/frontend-expert/monitoring"><img src="https://agentmods.dev/badge/skills/sukirman1901/frontend-expert/monitoring.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 5.1 | $0.00065 | $0.00546 |
| Opus 5 | $0.00032 | $0.00273 |
| Sonnet 5 | $0.00013 | $0.00109 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
monitoring 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 7d 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
Monitoring
Overview
Ship UI with enough production signal: errors, performance, and product analytics — without boiling the ocean.
When to use
- Add/fix Sentry (or similar) + error boundaries
- Performance monitoring / CWV in production
- Analytics events for key UI flows
- Alerting on error spikes or CWV regressions
When to skip
- Pure visual polish (
ui-feel//polish) - Local-only prototypes with no deploy target
MUST (when adding observability)
| Signal | Minimum |
|---|---|
| Errors | Boundary on app shell / critical routes + reporting; scrub PII |
| Secrets | DSN / keys via env — never commit |
| Sample rates | Sane defaults for traffic (don’t 100% trace huge apps blindly) |
| Analytics | Few high-value events (signup, checkout, critical CTA) — not every click |
| Alerts | Error rate or CWV budget with a named owner |
Lab Lighthouse ≠ production monitoring — use fe-devtools for local audits; this skill for shipped signal.
Workflow
- Errors — boundary + reporting; scrub PII
- Performance — sample traces; watch LCP/INP/CLS on key routes
- Analytics — few high-value events, not every click
- Alert — error rate / CWV budgets that someone will actually see
Agent boundaries
- May decide: Vendor (Sentry vs other), which 3–5 analytics events matter
- Must not: Hardcode DSNs; log emails/tokens; add analytics spam on every hover
Checklist
- Error boundary on app shell / critical routes
- DSN/env via env vars — not hardcoded secrets in git
- Sample rates sane for traffic
- No PII in events by default
- Alerts have an owner
- Key product events listed (not clickstream noise)
Depth
Full guide: references/monitoring.md.
Related: web-performance for build-time CWV; fe-devtools for lab audits.
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.
- 7d ago First seen · 65 lines · 65 tokens per session scan A 1519b6427fab
monitoring is a skill published in the GitHub repository sukirman1901/frontend-expert (10 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 546 once invoked, about $0.0003 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 2026-08-31.
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