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 agentmods add skills/uptimerobot/ai/sla-reportnpx skills add uptimerobot/ai --skill sla-reportgit clone --depth 1 https://github.com/uptimerobot/aiWrote 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/uptimerobot/ai/sla-report)<a href="https://agentmods.dev/skills/uptimerobot/ai/sla-report"><img src="https://agentmods.dev/badge/skills/uptimerobot/ai/sla-report.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 | $0.00044 | $0.01755 |
| Opus 5 | $0.00022 | $0.00877 |
| Sonnet 5 | $0.00009 | $0.00351 |
| Haiku 4.5 | $0.00004 | $0.00176 |
Grade A, and why
sla-report 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 6d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SLA report
Preflight — read first. If you cannot see any
uptimerobot:*MCP tools in your tool list, invoke theuptimerobot:setupskill before doing anything else. Do not tell the user the MCP is misconfigured —setup's Step 0 detects the common case (server connected, tools loaded after session start) and resolves it without re-keying.
Produces a stakeholder-ready Markdown report of uptime % and incident stats for each monitor over a given time range. Designed for copy-paste into Confluence, Slack, Notion, or a post-mortem doc.
Use this when the user asks "what was our uptime last month?", "generate an SLA report", "how many nines did we hit?", or "monthly monitoring review".
Step 1 — Clarify scope and range
Before calling any tools, confirm two things if not already clear:
- Which monitors? All monitors, a search filter (e.g.
"prod"), or an explicit list? - What time range? Default to
"30d". Accept"7d","90d", or an ISO 8601 interval like"2026-04-01T00:00:00Z/2026-04-30T23:59:59Z".
If the user says "last month", convert to the ISO interval for the previous calendar month.
Step 2 — Account aggregate
{ "timeRange": "30d" }
Call get-monitor-stats to get the aggregate uptime % and total downtime for the opening summary.
Step 3 — List monitors in scope
{ "search": "prod", "limit": 50 }
Omit search to get all monitors. Paginate until hasMore: false. Collect monitorId, friendlyName, and status for every monitor in scope.
Exclude PAUSED and NOT_STARTED monitors from the report unless the user explicitly wants them — they have no meaningful uptime data for the range. Note how many were excluded.
Track any monitors currently in DOWN or SEEMS_DOWN state — they need a callout in the narrative.
Step 4 — Per-monitor incidents
For each monitor, fetch downtime incidents for the range:
{ "monitorId": 800123456, "timeRange": "30d", "limit": 50 }
Paginate until hasMore: false. Sum duration across all incidents to get total downtime seconds. Count the incidents.
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.
- 6d ago First seen · 163 lines · 44 tokens per session scan A c22ddc259222
sla-report is a skill published in the GitHub repository uptimerobot/ai (24 stars, last pushed 23d ago), licensed MIT. It adds 44 tokens to every session and 1,755 once invoked, about $0.0002 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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