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 G1Joshi/Agent-Skills --skill argocdgit clone --depth 1 https://github.com/G1Joshi/Agent-SkillsWrote 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/g1joshi/agent-skills/argocd)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/argocd"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/argocd/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/g1joshi/agent-skills/argocd"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/argocd.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 | $0.00022 | $0.00458 |
| Opus 5 | $0.00011 | $0.00229 |
| Sonnet 5 | $0.00004 | $0.00092 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
argocd 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 5d 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.
What it actually says
ArgoCD
ArgoCD is the industry standard for GitOps. It syncs the state of a Kubernetes cluster with a Git repository. 2025 features: ApplicationSets for multi-tenant management.
When to Use
- Kubernetes CD: Continuous Delivery specifically for K8s.
- GitOps: You want your cluster state (YAML) versioned in Git.
- Drift Detection: ArgoCD alerts you if someone manually hacks
kubectl editin production.
Quick Start
# Application.yaml
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: guestbook
namespace: argocd
spec:
project: default
source:
repoURL: https://github.com/argoproj/argocd-example-apps.git
targetRevision: HEAD
path: guestbook
destination:
server: https://kubernetes.default.svc
namespace: guestbook
Core Concepts
Application
The link between a Git source and a K8s destination.
ApplicationSet
A generator that spawns multiple Application resources. Example: "Deploy every folder in this repo as an app" or "Deploy this app to every cluster".
Sync Phases
Pre-Sync (Schema migration), Sync (Deployment), Post-Sync (Health check).
Best Practices (2025)
Do:
- Use ApplicationSets: The modern way to manage many apps.
- Separate Config from Code: Keep app source code and K8s manifests in separate repos or at least separate folders.
- Use "App of Apps": A bootstrap pattern where one root Argo app deploys all other apps.
Don't:
- Don't manage Secrets in plain Git: Use Sealed Secrets, External Secrets Operator, or ArgoCD Vault Plugin.
References
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.
- 5d ago First seen · 65 lines · 22 tokens per session scan A 47688d6d15ef
argocd is a skill published in the GitHub repository G1Joshi/Agent-Skills (12 stars, last pushed 7mo ago), licensed MIT. It adds 22 tokens to every session and 458 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
ci-cd-pipelines
When designing GitHub Actions workflows, optimizing pipeline speed, implementing deployment gates.
general-dev-tools
Core development tools used across any project — git, docker, make, CI/CD, linting, formatting, pre-commit hooks.
git-workflow-and-versioning
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, opening or reviewing a pull request (PR), pushing to a remote, or when you need to organize work across multiple parallel streams. Use when cutting a release, choosing a semantic version bump…
ci-cd-and-automation
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
chinese-git-workflow
A reference for configuring Git with Chinese code-hosting services such as Gitee, Coding.net, GitLab China, and CNB, including SSH, HTTPS, credentials, CI, and repository mirroring.
conductor-revert
Reverts previous work (tracks, phases, or tasks) by identifying associated commits and performing Git reverts.