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 sawrus/agent-guides --skill slo-sli-designgit clone --depth 1 https://github.com/sawrus/agent-guidesWrote 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/sawrus/agent-guides/slo-sli-design)<a href="https://agentmods.dev/skills/sawrus/agent-guides/slo-sli-design"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/slo-sli-design/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/sawrus/agent-guides/slo-sli-design"><img src="https://agentmods.dev/badge/skills/sawrus/agent-guides/slo-sli-design.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 | $0.00028 | $0.01204 |
| Opus 5 | $0.00014 | $0.00602 |
| Sonnet 5 | $0.00006 | $0.00241 |
| Haiku 4.5 | $0.00003 | $0.00120 |
Grade A, and why
slo-sli-design 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 12d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: SLO/SLI Design
Expertise: SLI selection, SLO target setting, error budget calculation, burn rate alerting, Sloth/pyrra integration.
When to load
When defining SLOs for a new service, setting up error budget tracking, or reviewing existing SLOs after an incident.
SLI Selection Framework
Step 1: What does the user care about?
→ "The checkout completes successfully and quickly"
Step 2: What CAN we measure?
→ HTTP 2xx responses, p99 latency
Step 3: Define the SLI formula
→ Availability SLI: good_requests / total_requests
where good = status < 500 AND latency < 500ms
Step 4: Pick SLO target (start conservative, tighten later)
→ 99.5% (don't chase 99.99% without data — high budget wasted on caution)
Step 5: Calculate error budget
→ 100% - 99.5% = 0.5% over 28 days = 0.5% × 28 × 24 × 60 = 201.6 minutes
Prometheus SLO Implementation (manual)
# Recording rules for SLO tracking
groups:
- name: slo.checkout-service
interval: 30s
rules:
# Good requests (2xx, latency < 500ms)
- record: slo:http_requests_good:rate5m
expr: |
sum(rate(http_requests_total{
service="checkout-service",
status=~"2..",
duration_bucket="0.5"
}[5m]))
# Total requests
- record: slo:http_requests_total:rate5m
expr: |
sum(rate(http_requests_total{service="checkout-service"}[5m]))
# SLI = good / total
- record: slo:http_availability:ratio_rate5m
expr: slo:http_requests_good:rate5m / slo:http_requests_total:rate5m
# 28-day rolling availability
- record: slo:http_availability:ratio_rate28d
expr: |
sum_over_time(slo:http_availability:ratio_rate5m[28d]) / (28 * 24 * 12)
Burn Rate Alerts (multiwindow)
# Multi-window, multi-burn-rate alerting (Google SRE Workbook pattern)
groups:
- name: slo.checkout-service.burn-rate
rules:
# Fast burn: 14.4× rate (burns 1h of budget in 5 min)
- alert: SLOFastBurn
expr: |
(
slo:http_availability:ratio_rate1h{service="checkout-service"} < (1 - 14.4 * 0.005)
) and (
slo:http_availability:ratio_rate5m{service="checkout-service"} < (1 - 14.4 * 0.005)
)
labels:
severity: critical
slo: checkout-service-availability
annotations:
summary: "Fast error budget burn — checkout-service (> 14.4× rate)"
runbook_url: "https://runbooks.internal/slo-fast-burn"
# Slow burn: 3× rate (burns 10% of budget in 6h)
- alert: SLOSlowBurn
expr: |
(
slo:http_availability:ratio_rate6h{service="checkout-service"} < (1 - 3 * 0.005)
) and (
slo:http_availability:ratio_rate30m{service="checkout-service"} < (1 - 3 * 0.005)
)
labels:
severity: warning
slo: checkout-service-availability
annotations:
summary: "Slow error budget burn — checkout-service (> 3× rate)"
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.
- 12d ago First seen · 146 lines · 28 tokens per session scan A fad3d3d8fe51
slo-sli-design is a skill published in the GitHub repository sawrus/agent-guides (17 stars, last pushed 11d ago), licensed MIT. It adds 28 tokens to every session and 1,204 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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