Nightingale is an open-source monitoring and alerting system that connects to stored metrics and log data, evaluates alert rules, and distributes notifications. Operations teams use it to manage alarms and explore observability data alongside existing data sources and collectors. Catalogue add-ons provide skills for operating Nightingale.
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 ccfos/nightingale --skill query-alert-eventsgit clone --depth 1 https://github.com/ccfos/nightingaleWrote 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/ccfos/nightingale/query-alert-events)<a href="https://agentmods.dev/skills/ccfos/nightingale/query-alert-events"><img src="https://agentmods.dev/badge/skills/ccfos/nightingale/query-alert-events.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.02716 |
| Opus 5 | $0.00023 | $0.01358 |
| Sonnet 5 | $0.00009 | $0.00543 |
| Haiku 4.5 | $0.00005 | $0.00272 |
Grade A, and why
query-alert-events 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 8d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nightingale (n9e) Query Alert Events
Query and view alert events on the Nightingale monitoring platform. Supports querying current active alerts (not yet recovered), historical alerts (recovered/not recovered), and retrieving the detailed information of a single alert.
Prerequisites
The user must provide:
- n9e address: e.g.
http://<n9e-host>:<port> - Username/password: e.g.
<username>/<password> - Query requirement description: e.g. "what level-1 alerts occurred in the last hour", "view active alerts", "details of alert ID 123"
If the user has not provided the information above, use the AskUserQuestion tool to ask.
Execution Steps
Step 1: Log in to obtain a Token
POST /api/n9e/auth/login
Content-Type: application/json
Body: {"username":"<username>","password":"<password>"}
Extract dat.access_token from the response, and include Authorization: Bearer <token> in all subsequent requests.
Step 2: Choose the query type based on the user's requirement
Determine which query method to use based on the user's intent:
- View active alerts (alerts currently not recovered) → use the active alerts query API
- View historical alerts (including recovered and not recovered) → use the historical alerts query API
- View alert details (the complete information of a specific alert) → use the alert details API
Decision rules:
- The user mentions "active", "current", "not recovered", "currently alerting" → active alerts
- The user mentions "historical", "past", "recovered", "has recovered" → historical alerts
- The user mentions a specific alert ID → alert details
- When not explicitly specified, query active alerts by default
Step 3: Execute the query
Method 1: Query active alerts
GET /api/n9e/alert-cur-events/list?<query_params>
Authorization: Bearer <token>
Method 2: Query historical alerts
GET /api/n9e/alert-his-events/list?<query_params>
Authorization: Bearer <token>
Method 3: Query alert details
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.
- 8d ago First seen · 318 lines · 45 tokens per session scan A 830cbb76e265
query-alert-events is a skill published in the GitHub repository ccfos/nightingale (13,280 stars, last pushed 3d ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,716 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.
Other skills, from other repositories
cis-aws-database-10.8
Ensure Monitoring and Alerting is Enabled.
monitoring
Use when setting up uptime and health monitoring, alerts, or on-call basics for a service already in production, so you learn it is down before customers do — health and readiness probes, alerting on SLO error-budget burn rather than raw counts, curing alert fatigue, on-call rotation with escalation, and a status…
grafana-expert
Expert-level Grafana dashboards, visualization, data sources, alerting, and production operations. Use when the user mentions dashboards, visualization, monitoring, observability, or alerting, or when the task involves Grafana Architecture, Installation on Kubernetes, Data Sources, or Dashboard JSON.
datadog
Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.
monitoring-expert
Expert-level monitoring and observability with Prometheus, Grafana, logging, and alerting. Use when the user mentions observability, Prometheus, Grafana, logging, metrics, or alerting, or when the task involves The Three Pillars of Observability, Monitoring Fundamentals, Prometheus Configuration, or Alert Rules.
prometheus-expert
Expert-level Prometheus monitoring, metrics collection, PromQL queries, alerting, and production operations. Use when the user mentions monitoring, metrics, observability, alerting, or PromQL, or when the task involves Prometheus Architecture, Installation on Kubernetes, ServiceMonitor, or PromQL Queries.