gcx is a command-line tool that lets people and AI coding agents manage and inspect Grafana Cloud, Enterprise, and open-source instances. It provides access to dashboards, alerts, SLOs, metrics, logs, and traces, with workflows for alert investigation, dashboard management, GitOps, and observability setup. Its catalogue entries provide agent instructions and extensions for using gcx.
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 grafana/gcx --skill gcx-observabilitygit clone --depth 1 https://github.com/grafana/gcxWrote 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/grafana/gcx/gcx-observability)<a href="https://agentmods.dev/skills/grafana/gcx/gcx-observability"><img src="https://agentmods.dev/badge/skills/grafana/gcx/gcx-observability/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/grafana/gcx/gcx-observability"><img src="https://agentmods.dev/badge/skills/grafana/gcx/gcx-observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 59 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00107 | $0.01760 |
| Opus 5 | $0.00053 | $0.00880 |
| Sonnet 5 | $0.00021 | $0.00352 |
| Haiku 4.5 | $0.00011 | $0.00176 |
Grade A, and why
gcx-observability 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 9d 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are helping the user implement comprehensive Grafana Cloud observability for their application using a test-driven approach. Use gcx to automate setup.
Test-driven observability principle: Define what "healthy" looks like before deploying instrumentation. Every signal needs a test that can fail: SLOs express availability/latency contracts, k6 tests express load requirements with pass/fail thresholds, and synthetic checks express uptime expectations. Instrumentation exists to make those tests meaningful - not the other way around. Phase 2 captures all test definitions up front; later phases deploy infrastructure to satisfy them.
Work interactively - explain each phase, generate YAML from gcx resources list-examples <type> where one exists (not every kind ships an example — fall back to gcx resources list-types <type> and a minimal manifest), confirm before creating anything, and validate success.
Command discovery: Before executing any action in a phase, use gcx <group> --help to discover the exact commands and flags available. Use gcx commands --flat -o json to see all command groups. Never assume a command's exact syntax - always discover it first. For Kubernetes operations, use kubectl --help and kubectl <verb> --help to discover the right flags.
Parallelism rules:
- Use
TaskCreateto register every unit of work before starting anything, so the user can see progress. - Use the
Agenttool to run independent operations concurrently. Launch multiple agents in a single message whenever their inputs don't depend on each other. - Within a phase, identify which resources are independent and launch them as parallel agents. Only serialize when there is a true dependency (e.g. a contact point must exist before a notification policy references it).
- Use background agents (
run_in_background: true) for slow operations (k8s prep, large exports) so you can continue other work while they run. - After all agents in a wave complete, collect results, report to the user, and move on.
Step 1: Select Phases
If the user passed arguments ($ARGUMENTS), use them directly as the selected phases - do not show the menu. all means all phases; a space-separated list like 0 1 2 means those specific phases.
Otherwise, show the following menu and ask which phases to run:
Grafana Cloud Observability Setup
══════════════════════════════════
Phase 0 Bootstrap Verify gcx config + stack auth
Phase 1 Discovery & Context Gather app info (clusters, namespaces, journeys)
Phase 2 Test Definitions Define SLOs, k6 thresholds, synthetic checks FIRST
Phase 3 Instrumentation Alloy collector, setup instrumentation, Faro frontend
Phase 4 SLO-Based Alerting Wire alert rules, contact points, policies
Phase 5 Synthetic Monitoring Deploy uptime checks (defined in Phase 2)
Phase 6 k6 Load Testing Deploy load tests + schedules (defined in Phase 2)
Phase 7 IRM Setup Oncall integrations, escalation chains, schedules
Phase 8 Custom Dashboards Dashboards via gcx resources push
Phase 9 Cost Optimization Adaptive metrics/logs/traces for cardinality control
Phase 10 GitOps Export Export managed resources as declarative YAML
Phase 11 Observability Review Validate signals, find gaps, recommend next steps
Enter phases to run (e.g. "0 1 2" or "all"):
Once phases are selected, immediately create a task for every selected phase using TaskCreate before executing anything. This gives the user a live progress view.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 131 lines · 107 tokens per session scan A fe1a78820235
gcx-observability is a skill published in the GitHub repository grafana/gcx (590 stars, last pushed today), licensed Apache-2.0. It adds 107 tokens to every session and 1,760 once invoked, about $0.0005 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.
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