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 slo-sli-error-budgetsgit 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/slo-sli-error-budgets)<a href="https://agentmods.dev/skills/latestaiagents/agent-skills/slo-sli-error-budgets"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/slo-sli-error-budgets/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/slo-sli-error-budgets"><img src="https://agentmods.dev/badge/skills/latestaiagents/agent-skills/slo-sli-error-budgets.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 | $0.00085 | $0.02082 |
| Opus 5 | $0.00043 | $0.01041 |
| Sonnet 5 | $0.00017 | $0.00416 |
| Haiku 4.5 | $0.00009 | $0.00208 |
Grade A, and why
slo-sli-error-budgets 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.
How it starts
The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SLOs, SLIs, and Error Budgets
Define and measure reliability in terms that matter to users.
Terminology
| Term | Definition | Example |
|---|---|---|
| SLI | Service Level Indicator - What you measure | 99.2% of requests succeed |
| SLO | Service Level Objective - Your target | 99.9% availability |
| SLA | Service Level Agreement - Contract with customers | 99.5% with refund clause |
| Error Budget | Allowed unreliability (100% - SLO) | 0.1% = 43 min/month downtime |
Common SLI Types
Availability
availability = successful_requests / total_requests
# Prometheus query
sum(rate(http_requests_total{status!~"5.."}[30d]))
/
sum(rate(http_requests_total[30d]))
Latency
latency_sli = requests_under_threshold / total_requests
# Example: 99% of requests under 200ms
sum(rate(http_request_duration_seconds_bucket{le="0.2"}[30d]))
/
sum(rate(http_request_duration_seconds_count[30d]))
Throughput
throughput_sli = successful_operations / attempted_operations
# Example: Batch jobs
sum(job_succeeded_total) / sum(job_attempted_total)
Freshness
freshness_sli = fresh_data_requests / total_requests
# Example: Data updated within 1 minute
sum(data_age_seconds < 60) / count(data_age_seconds)
Choosing SLO Targets
The Nines Table
| Availability | Downtime/Year | Downtime/Month | Downtime/Week |
|---|---|---|---|
| 99% | 3.65 days | 7.31 hours | 1.68 hours |
| 99.5% | 1.83 days | 3.65 hours | 50.4 min |
| 99.9% | 8.77 hours | 43.8 min | 10.1 min |
| 99.95% | 4.38 hours | 21.9 min | 5.04 min |
| 99.99% | 52.6 min | 4.38 min | 1.01 min |
| 99.999% | 5.26 min | 26.3 sec | 6.05 sec |
Guidelines for Setting SLOs
1. Start with user expectations
- What do users actually need?
- What are they getting today?
2. Consider dependencies
- Your SLO can't exceed your dependencies
- If database is 99.9%, you can't be 99.99%
3. Start conservative, tighten later
- Easier to tighten SLO than loosen
- Build confidence before committing
4. Different SLOs for different tiers
- Premium customers: 99.99%
- Free tier: 99.5%
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 · 285 lines · 85 tokens per session scan A 7c7ea4b7d03c
slo-sli-error-budgets is a skill published in the GitHub repository latestaiagents/agent-skills (5 stars, last pushed 4mo ago), licensed MIT. It adds 85 tokens to every session and 2,082 once invoked, about $0.0004 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 2026-09-03.
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