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 slo-investigategit 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/slo-investigate)<a href="https://agentmods.dev/skills/grafana/gcx/slo-investigate"><img src="https://agentmods.dev/badge/skills/grafana/gcx/slo-investigate/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/slo-investigate"><img src="https://agentmods.dev/badge/skills/grafana/gcx/slo-investigate.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00115 | $0.02267 |
| Opus 5 | $0.00057 | $0.01133 |
| Sonnet 5 | $0.00023 | $0.00453 |
| Haiku 4.5 | $0.00012 | $0.00227 |
Grade A, and why
slo-investigate scanned grade A with 1 finding 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
1. Use gcx commands — do not call Grafana APIs directly (no curl, no HTTP libraries) How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SLO Investigator
Deep-dive investigation of breaching SLOs: dimensional breakdown, alert correlation, runbook access. For experienced operators — no hand-holding.
Core Principles
- Use gcx commands — do not call Grafana APIs directly (no curl, no HTTP libraries)
- Trust the user's expertise — skip obvious context, get to the root cause
- Use
-o jsonfor agent processing, default format for user display; show graphs for time-series data - Errors collected at the end — do not interleave error handling in workflow steps
- Use
--from/--tofor all time-range commands (never--start/--end)
Investigation Workflow
Step 1: Retrieve SLO Definition
gcx slo definitions get <UUID> -o json
Extract from the JSON response:
.metadata.name— SLO name.spec.query.type— query type:ratio,freeform, orthreshold- For ratio:
.spec.query.ratio.successMetric,.spec.query.ratio.totalMetric,.spec.query.ratio.groupByLabels[] - For freeform:
.spec.query.freeform.query .spec.objectives[0].value— objective (0–1),.spec.objectives[0].window— window.spec.destinationDatasource.uid— Prometheus datasource UID.spec.alerting.fastBurn.annotations,.spec.alerting.slowBurn.annotations— runbook/dashboard URLs.metadata.annotations— additional runbook/dashboard references
If no UUID is given, list SLOs and ask which to investigate:
gcx slo definitions list
Step 2: Check Status with Wide Output
gcx slo definitions status <UUID> -o wide
This shows SLI, ERROR_BUDGET, BURN_RATE, SLI_1H, SLI_1D, and STATUS.
Early exit — OK status: If STATUS is OK, report health metrics and stop:
SLO: <name> — Status: OK
SLI: <value> | Error budget remaining: <budget>% | Burn rate: <rate>x
1h SLI: <sli_1h> | 1d SLI: <sli_1d>
No action needed.
Early exit — NODATA status: If STATUS is NODATA, branch to NODATA diagnosis:
SLO: <name> — Status: NODATA
Recording rule metrics unavailable. Likely causes:
- Destination datasource misconfigured (check .spec.destinationDatasource.uid)
- Grafana recording rules not yet evaluated (can take 1–2 minutes after creation)
- Prometheus federation/remote write issue
Check: gcx datasources list --type prometheus
Then verify the destination datasource UID matches what the SLO expects.
What ships with it
1 file 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.
- 12d ago First seen · 203 lines · 115 tokens per session scan A ec32d8b8b3c3
slo-investigate is a skill published in the GitHub repository grafana/gcx (597 stars, last pushed today), licensed Apache-2.0. It adds 115 tokens to every session and 2,267 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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