Observability Monitor
CheckedProactively detects and alerts on infrastructure anomalies using real-time metrics and logs via customizable dashboards.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add ajianaz/skills-collection --skill observability-monitor -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
ajianaz
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned ajianaz/skills-collection at f1d8f59331.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- f1d8f59331
- Scanned
- 1 file, 363 lines
About this skill
What it does
This skill allows AI agents to monitor system metrics and logs, providing insights into application performance and infrastructure health. It can collect data from various sources, aggregate them, and present them in a user-friendly format for analysis and troubleshooting. The agent can also be configured to trigger alerts based on predefined thresholds or anomalies.
When to use it
- Troubleshooting production issues: Quickly identify the root cause of performance bottlenecks or errors by analyzing real-time metrics and logs.
- Proactive monitoring: Set up dashboards and alerts to detect potential problems before they impact users.
- Capacity planning: Analyze resource utilization trends to predict future needs and optimize infrastructure investments.
- Performance optimization: Identify areas for improvement in application code or system configuration based on performance data.
Key capabilities
- Metric collection from various sources
- Log aggregation and analysis
- Dashboard creation and visualization
- Alerting based on thresholds and anomalies
Example prompts
- "Show me the CPU utilization of my web servers over the last hour."
- "Create a dashboard displaying memory usage for all database instances."
- "Alert me if the error rate exceeds 5%."
- “What are the top 5 errors logged by the application in the past 24 hours?”
Tips & gotchas
The agent requires access to system metrics and logs. Ensure appropriate permissions are configured for data collection and analysis.