Agent skill

Observability Service Health

by aspectrr in aspectrr/deer

Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies.

MITAuto-check passedDevOps & Cloud

Install Observability Service Health

skills CLI
$ npx skills add aspectrr/deer --skill observability-service-health -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aspectrr/deer observability-service-health --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aspectrr/deer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/deer-cli/internal/skill/defaults/observability-service-health .claude/skills/observability-service-health && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
observability-service-health
GitHub stars
405
Token cost
~1.2k tokens
SKILL.md length
381 words
Files
1
Skills in repo
14
Repo updated
First seen
Licence
MIT

At a glance

Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies.

  • Works in 7 steps: Identify the service → Check SLOs and firing alerts → Check ML anomalies → …
  • Checking service status
  • SKILL.md covers Health criteria, Using ES|QL for APM metrics, Workflow and Guidelines
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Observability Service Health is an agent skill from aspectrr/deer. Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies. Use when checking service status, performance, or when the user asks about service health.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Site reliability engineering, Monitoring and alerting and Observability. The repository describes itself as: 🦌 The AI Elasticsearch Engineer. The licence is MIT.

When your agent uses it

  • Checking service status
  • The user asks about service health

Example prompts

  • “/observability-service-health”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Identify the service
  2. Check SLOs and firing alerts
  3. Check ML anomalies
  4. Review throughput, latency, and error rate
  5. Assess dependency health
  6. Correlate with infrastructure and logs
  7. Summarize and recommend

What it can do on your machine

Read from SKILL.md and the folder at commit e4f9845. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are esql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Observability Service Health loads about 1.2k tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 381 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aspectrr/deer at commit e4f9845, republished under its MIT licence (© aspectrr). 381 words, ~1,151 tokens.

Download SKILL.mdSave it as .claude/skills/observability-service-health/SKILL.md (or your agent's skills folder).
name
observability-service-health
description
Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies. Use when checking service status, performance, or when the user asks about service health.
metadata.author
elastic
metadata.version
0.1.0
metadata.source
elastic/agent-skills//skills/observability/service-health

APM Service Health

Assess APM service health using Observability APIs, ES|QL against APM indices, and Elasticsearch APIs. Use SLOs, firing alerts, ML anomalies, throughput, latency, error rate, and dependency health.

Health criteria

Synthesize health from all of the following when available:

SignalWhat to check
SLOsBurn rate, status (healthy/degrading/violated), error budget.
Firing alertsOpen or recently fired alerts for the service or dependencies.
ML anomaliesAnomaly jobs; score and severity for latency, throughput, or error rate.
ThroughputRequest rate; compare to baseline or previous period.
LatencyAvg, p95, p99; compare to SLO targets or history.
Error rateFailed/total requests; spikes or sustained elevation.
Dependency healthDownstream latency, error rate, availability.
InfrastructureCPU usage, memory; OOM and CPU throttling on pods/containers/hosts.
LogsApp logs filtered by service or trace ID for context and root cause.

Using ES|QL for APM metrics

Always filter by service.name (and service.environment when relevant). Combine with a time range on @timestamp:

esql
WHERE service.name == "my-service-name" AND service.environment == "production"
  AND @timestamp >= "2025-03-01T00:00:00Z" AND @timestamp <= "2025-03-01T23:59:59Z"
Example: Throughput and error rate
esql
FROM traces*apm*,traces*otel*
| WHERE service.name == "api-gateway"
  AND @timestamp >= "2025-03-01T00:00:00Z" AND @timestamp <= "2025-03-01T23:59:59Z"
| STATS request_count = COUNT(*), failures = COUNT(*) WHERE event.outcome == "failure" BY BUCKET(@timestamp, 1 hour)
| EVAL error_rate = failures / request_count
| SORT @timestamp
| LIMIT 500

Workflow

text
- [ ] Step 1: Identify the service (and time range)
- [ ] Step 2: Check SLOs and firing alerts
- [ ] Step 3: Check ML anomalies (if configured)
- [ ] Step 4: Review throughput, latency (avg/p95/p99), error rate
- [ ] Step 5: Assess dependency health
- [ ] Step 6: Correlate with infrastructure and logs
- [ ] Step 7: Summarize health and recommend actions
Step 1: Identify the service

Confirm service name and time range. If the user has not provided the time range, assume last hour.

Step 2: Check SLOs and firing alerts

SLOs: Call the SLOs API to get SLO definitions and status for the service. Alerts: For active APM alerts, call /api/alerting/rules/_find?search=apm&search_fields=tags&per_page=100&filter=alert.attributes.executionStatus.status:active.

Step 3: Check ML anomalies

If ML anomaly detection is used, query ML job results for the service and time range.

Show full SKILL.md (148 more words)Show less
Step 4: Review throughput, latency, and error rate

Use ES|QL against traces*apm*,traces*otel* or metrics*apm*,metrics*otel* for throughput, latency, and error rate.

Step 5: Assess dependency health

Obtain dependency data via ES|QL on traces or metrics. Flag slow or failing dependencies.

Step 6: Correlate with infrastructure and logs
  • Infrastructure: Use resource attributes from traces (k8s.pod.name, container.id, host.name) and query infrastructure indices for CPU and memory.
  • Logs: Use ES|QL or Elasticsearch on log indices with service.name or trace.id to explain behavior.
Step 7: Summarize and recommend

State health (healthy / degraded / unhealthy) with reasons; list concrete next steps.

Guidelines

  • Use Observability APIs and ES|QL on traces*apm*,traces*otel*/metrics*apm*,metrics*otel*.
  • Always use the user's time range; avoid assuming "last 1 hour" if the issue is historical.
  • When SLOs exist, anchor the health summary to SLO status and burn rate.
  • Add LIMIT n to cap rows and token usage.
  • Prefer coarser BUCKET(@timestamp, ...) when only trends are needed.

© aspectrr, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in deer-cli/internal/skill/defaults/observability-service-health of aspectrr/deer.

Open the folder on GitHubat commit e4f9845

Compare with similar skills

Observability Service Health next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Observability Service Health compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Observability Service Health this skillaspectrr/deer405—~1.2kAutomated safety check: PassMIT
Service Mesh Observabilitywshobson/agents40k9 repos~607Automated safety check: PassMIT
Monitoring Observabilityahmedasmar/devops-claude-skills203—~3.9kAutomated safety check: PassNone
Prometheus Error Rate Investigatorprometheus/prometheus-mcp121—~592Automated safety check: PassApache-2.0
Oma Observabilityfirst-fluke/oh-my-agent1.3k—~4.9kAutomated safety check: PassMIT
Observability Sre Triageelastic/agent-skills592—~7.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Observability Service Health

What does Observability Service Health do?

Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies. Observability Service Health is an agent skill from aspectrr/deer. Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies.

When should I use Observability Service Health?

Observability Service Health fits situations like: checking service status; the user asks about service health.

How do I install Observability Service Health in Claude Code?

Run `npx skills add aspectrr/deer --skill observability-service-health -a claude-code`. Or copy the skill folder (deer-cli/internal/skill/defaults/observability-service-health in aspectrr/deer) into .claude/skills/observability-service-health in your project. Claude Code loads it when a task matches its description.

How do I install Observability Service Health in Codex?

Run `npx skills add aspectrr/deer --skill observability-service-health -a codex`. Or copy the skill folder (deer-cli/internal/skill/defaults/observability-service-health in aspectrr/deer) into .agents/skills/observability-service-health in your project. Codex loads it when a task matches its description.

Can I use Observability Service Health in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aspectrr/deer --skill observability-service-health -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/observability-service-health, .gemini/skills/observability-service-health, .github/skills/observability-service-health and .opencode/skills/observability-service-health in your project.

What does Observability Service Health need to run?

SKILL.md names no scripts, command-line tools or credentials: Observability Service Health is instructions for the agent only.

Does Observability Service Health access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Observability Service Health safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Observability Service Health use?

Observability Service Health is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Observability Service Health use?

About 1.2k tokens (SKILL.md is roughly 4.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Observability Service Health?

Skills that share tags, products or a category with Observability Service Health: Service Mesh Observability (wshobson/agents, 40k stars), Monitoring Observability (ahmedasmar/devops-claude-skills, 203 stars), Prometheus Error Rate Investigator (prometheus/prometheus-mcp, 121 stars) and Oma Observability (first-fluke/oh-my-agent, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Observability Service Health?

aspectrr (a GitHub user) maintains it in aspectrr/deer, which has 405 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on April 21, 2026.

Source: aspectrr/deer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.