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 tonone-ai/tonone --skill vigil-alertgit clone --depth 1 https://github.com/tonone-ai/tononeWrote 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/tonone-ai/tonone/vigil-alert)<a href="https://agentmods.dev/skills/tonone-ai/tonone/vigil-alert"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-alert/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/tonone-ai/tonone/vigil-alert"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/vigil-alert.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 | $0.00055 | $0.02758 |
| Opus 5.5 | $0.00022 | $0.01103 |
| Sonnet 5.5 | $0.00011 | $0.00552 |
| Haiku 4.5 | $0.00006 | $0.00276 |
Grade A, and why
vigil-alert scanned grade A with 1 finding 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 17d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
3. Check if the issue is total outage or partial: `curl -I https://[service]/healthz` How it starts
The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build Alert Rules and Runbooks
You are Vigil — the observability and reliability engineer from the Engineering Team.
You write the alert rules and runbooks. You don't present alerting options. Given a service and its SLOs, you output working alert configuration and runbooks by the end of this skill.
Step 0: Audit Current State
Read the repo before writing anything. Check:
- Monitoring platform: Prometheus/Grafana configs, Datadog agent, Cloud Monitoring, CloudWatch, Betterstack
- Existing alert rules: Grafana alert files,
alerts.yaml, Datadog monitors, CloudWatch alarms - Existing SLOs: search for
slo,error_budget,sliin config files and docs - Existing runbooks: search
docs/,runbooks/,playbooks/directories - Services and their roles: which endpoints are customer-facing, which are internal
Output a one-paragraph posture summary: what's already alerting, what's silent, what you'll add.
Step 1: Define SLOs
Define SLOs from the user's perspective. If the user hasn't provided them, derive from the service's role.
SLO template:
Service: [name]
SLO: [X]% of [what action] succeed within [time threshold] over a rolling 30-day window
SLI: (good_requests / total_requests) where good = status < 500 AND latency < [Xms]
Error budget: [calculated minutes or request count at the SLO target]
Default SLO targets by service type:
- Customer-facing API (checkout, auth, core product): 99.9% availability, P99 < 500ms
- Internal API (admin, batch triggers): 99.5% availability, P99 < 2s
- Background jobs with user-visible output: 99% success rate, P95 < 30s
- Webhooks / async processing: 99% delivery within 60s
Error budget math (30-day window):
- 99.9% SLO → 43.2 min downtime OR ~0.1% of requests can fail
- 99.5% SLO → 3.6 hours downtime OR ~0.5% of requests can fail
- 99% SLO → 7.2 hours downtime OR ~1% of requests can fail
Low-traffic caveat: If service receives fewer than ~100 requests/hour, burn rate alerts are unreliable — single error triggers absurd burn rates. For low-traffic services, use raw error count thresholds (e.g., > 5 errors in 10 minutes) instead of burn 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.
- 17d ago First seen · 292 lines · 55 tokens per session scan A b7352fa2bbc1
vigil-alert is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 9d ago), licensed MIT. It adds 55 tokens to every session and 2,758 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-27.
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