# alert-investigation

Analyzes triggered observability alerts, pinpoints probable root causes, and generates a structured incident summary for on-call engineers.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 659 installs · ★ 28
- Author: launchdarkly
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/launchdarkly/ai-tooling/tree/HEAD/skills/observability/alert-investigation/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/alert-investigation

## What it does

The skill processes alert metadata: alert identifiers, trigger names, threshold figures, and time boundaries. Depending on the alert category, it loads a matching companion document (`logs.md`, `traces.md`, `errors.md`, `sessions.md`, or `metrics.md`) to guide the diagnostic workflow.

Telemetry queries run through LaunchDarkly observability MCP tools: `query-logs`, `query-traces`, `query-error-groups`, `query-sessions`, and `query-aggregations`. Without a running remote LaunchDarkly MCP server, the skill cannot fetch telemetry and will fail to inspect the system.

The final diagnosis follows a fixed layout: what triggered, root cause citing trace IDs or log timestamps, affected scope, and up to three direct remediation steps. When an alert falls within normal operational variance, the skill flags it as noise rather than fabricating causes.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add launchdarkly/ai-tooling --skill alert-investigation -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/alert-investigation/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/alert-investigation/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add launchdarkly/ai-tooling --skill alert-investigation -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/alert-investigation/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add launchdarkly/ai-tooling --skill alert-investigation -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/alert-investigation/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install launchdarkly/ai-tooling alert-investigation
```

2. **Manually: put the files in place**
- File: `.github/skills/alert-investigation/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add launchdarkly/ai-tooling --skill alert-investigation -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/launchdarkly/ai-tooling --path skills/observability/alert-investigation
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/alert-investigation/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add launchdarkly/ai-tooling --skill alert-investigation -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/launchdarkly/ai-tooling/tree/HEAD/skills/observability/alert-investigation/SKILL.md

## When to use it
- diagnose root causes behind firing observability alerts
- evaluate incident blast radius across sessions and services
- filter out benign alert noise from real operational incidents
- generate concrete next steps for on-call responders

## Example prompts
- Investigate alert `alertID: 504-spike`, threshold crossed between 10:00 and 10:20 UTC.
- Check the latency alert for `groupValue: payment-api` using the `traces.md` guide.

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 8afb3cb42fea7a5d.

BEGIN THIRD-PARTY FILE 8afb3cb42fea7a5d
````text
---
name: alert-investigation
description: "Investigates a triggered observability alert and returns a structured diagnosis with likely cause, scope, and next steps."
license: Apache-2.0
compatibility: Requires the remotely hosted LaunchDarkly MCP server
metadata:
  author: launchdarkly
  version: "0.1.0"
---

# Alert investigation

You are investigating a specific triggered alert. Alerts arrive with structured context — an alert ID, name, threshold, value that crossed it, and a time range. Your job is to explain *why* it fired, assess *scope*, and recommend *action*.

## Prerequisites

This skill uses the following LaunchDarkly observability MCP tools:

- `query-logs` — query log records
- `query-traces` — query distributed traces
- `query-error-groups` — query error groups
- `query-sessions` — query sessions
- `query-aggregations` — query aggregated/time-bucketed metrics
- `get-keys` — discover available attribute keys before filtering

## Workflow

1. **Parse the alert context.** The first turn of the conversation carries alert variables: `alertID`, `alertName`, `alertValue`, `group`, `groupValue`, `query`, `thresholdWindow`, `timeRange`, plus a product-specific link. Use these, don't re-derive them.
2. **Load the per-product companion.** Based on the alert's product type, load the matching companion: `logs.md`, `traces.md`, `errors.md`, `sessions.md`, or `metrics.md`. Each captures the per-product investigation shape.
3. **Run the investigation** using the methodology from the investigate skill (cross-reference logs/traces/errors/sessions/metrics; cite identifiers; aggregate before paginating). Scoped to the alert's time range and filter.
4. **Produce a structured diagnosis.** See output template below.

## Output template

Alert investigations have a consistent structure so consumers (notification channels, dashboards) can parse them.

```
## What triggered

<1-2 sentences naming the alert, the threshold, and the value that crossed it.>

## Likely cause

<Root-cause narrative citing specific evidence: trace IDs, log timestamps, error group IDs, flag keys, deploy timing.>

## Scope

<Who or what is affected. Number of users, services, sessions, error groups. Time window of impact.>

## Next steps

<1-3 concrete actions the on-call or owner should take. Prefer specifics: "roll back flag X in env Y", "restart service Z", "investigate trace <id> for the downstream failure". Avoid "investigate further" — if you don't have a root cause, say what specifically should be investigated and how.>
```

## When to load which companion

- **`logs.md`** — log alert, log pattern alert
- **`traces.md`** — latency alert, trace-error-rate alert, span-specific alert
- **`errors.md`** — error-rate alert, new-error-group alert, crash-rate alert
````
END THIRD-PARTY FILE 8afb3cb42fea7a5d

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