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.
Borrowing it
Nothing to install: this file belongs to grafana/gcx. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/grafana/gcx/main/.agents/skills/create-rfc/SKILL.mdgit 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/create-rfc)<a href="https://agentmods.dev/skills/grafana/gcx/create-rfc"><img src="https://agentmods.dev/badge/skills/grafana/gcx/create-rfc/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/create-rfc"><img src="https://agentmods.dev/badge/skills/grafana/gcx/create-rfc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00047 | $0.01375 |
| Opus 5.5 | $0.00019 | $0.00550 |
| Sonnet 5.5 | $0.00009 | $0.00275 |
| Haiku 4.5 | $0.00005 | $0.00137 |
Grade A, and why
create-rfc 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 8d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create RFC
Produce one self-contained RFC that engineers outside the conversation can review. Research establishes facts; the interview resolves consequential decisions. Maintain the same document throughout, using the Rust-based RFC template. This skill ends with RFC review, not implementation or publication.
This is a public repository. Use public evidence or independently developed material suitable for public review. Keep restricted research outside the checkout; removing links or attribution does not make internal findings publishable. See RFC conventions for location and conventions.
Establish the starting point
Read the supplied material, relevant repository guidance, and existing RFC conventions. Identify the problem, audience, constraints, settled decisions, and consequential gaps. An existing draft is the starting artifact: preserve its accepted decisions and focus on contradictions or missing reasoning.
In this repository, use docs/rfcs/NNN-title.md and record status near the title. Select the next available number starting at 001. Outside a repository, use a suitable user-visible working directory. Keep subsequent revisions in the same file. If the destination is shared, prepare a private copy until publication is authorized.
Create an initial RFC with established facts and clearly marked open questions. Use it as the single design document rather than creating separate glossaries, context documents or research reports. Place terminology near the end, followed by a references section when needed. Required private execution notes may hold resumption state, but must not become an alternative design source. Keep incidental experiment artifacts out of the RFC's narrative.
Research and interview in rounds
Map the design as decisions and their dependencies. In each round, ask the independent consequential questions whose prerequisites are settled; defer questions that depend on unanswered ones. Use manageable batches, stable question numbers, concrete scenarios, and a recommended answer with its main tradeoff. Use the host's question tool when suitable, otherwise chat. Allow the user to propose a different answer.
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.
- 8d ago Changed 1190fd2ae4ab
- 23d ago First seen · 57 lines · 47 tokens per session scan A 39b7e1bb718e
create-rfc is a skill published in the GitHub repository grafana/gcx (805 stars, last pushed yesterday), licensed Apache-2.0. It adds 47 tokens to every session and 1,375 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-06.
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