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 latestaiagents/agent-skills --skill alerting-strategiesgit clone --depth 1 https://github.com/latestaiagents/agent-skillsWrote 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/latestaiagents/agent-skills/alerting-strategies)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/alerting-strategies"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/alerting-strategies/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/latestaiagents/agent-skills/alerting-strategies"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/alerting-strategies.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00069 | $0.01734 |
| Opus 5.5 | $0.00028 | $0.00694 |
| Sonnet 5.5 | $0.00014 | $0.00347 |
| Haiku 4.5 | $0.00007 | $0.00173 |
Grade A, and why
alerting-strategies 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 1mo 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alerting Strategies
Get paged for real problems, not noise.
Alerting Philosophy
"Every alert should be actionable, and every action should have a runbook."
The Goal
- Page for symptoms (user impact), not causes (internal metrics)
- Every page should require human judgment
- False positives erode trust; false negatives cause outages
Alert Severity Levels
| Level | Response | Time to Ack | Example |
|---|---|---|---|
| P1/Critical | Page immediately | 5 min | Service down, data loss |
| P2/High | Page during hours | 30 min | Degraded performance |
| P3/Medium | Ticket | Next day | Non-critical feature broken |
| P4/Low | Review weekly | N/A | Cleanup tasks, warnings |
Alert Types
1. Symptom-Based (Recommended)
Alert on what users experience:
# Good: Users are experiencing errors
- alert: HighErrorRate
expr: |
sum(rate(http_requests_total{status=~"5.."}[5m]))
/
sum(rate(http_requests_total[5m]))
> 0.01
for: 5m
labels:
severity: critical
annotations:
summary: "Error rate above 1%"
runbook: "https://wiki/runbooks/high-error-rate"
2. Cause-Based (Use Sparingly)
Alert on infrastructure issues that will cause symptoms:
# Acceptable: Will cause problems soon
- alert: DiskSpaceLow
expr: node_filesystem_avail_bytes / node_filesystem_size_bytes < 0.1
for: 15m
labels:
severity: warning
annotations:
summary: "Disk space below 10%"
3. SLO-Based (Best Practice)
Alert on error budget consumption:
# Excellent: Based on SLO burn rate
- alert: SLOBurnRateHigh
expr: |
(
sum(rate(http_requests_total{status=~"5.."}[1h]))
/
sum(rate(http_requests_total[1h]))
) > (14.4 * 0.001) # 14.4x burn rate
for: 5m
labels:
severity: critical
annotations:
summary: "Burning error budget 14x faster than sustainable"
Multi-Window, Multi-Burn-Rate Alerts
Google SRE's recommended approach:
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.
- 1mo ago First seen · 280 lines · 69 tokens per session scan A bda6b632371b
alerting-strategies is a skill published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 1,734 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
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