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 agentmods add skills/ancoleman/ai-design-components/implementing-gitopsnpx skills add ancoleman/ai-design-components --skill implementing-gitopsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWhat 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 | $0.00049 | $0.02618 |
| Opus 5 | $0.00024 | $0.01309 |
| Sonnet 5 | $0.00010 | $0.00524 |
| Haiku 4.5 | $0.00005 | $0.00262 |
Grade A, and why
implementing-gitops 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 2d 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 — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitOps Workflows
Implement GitOps continuous delivery for Kubernetes using declarative, pull-based deployment models where Git serves as the single source of truth for infrastructure and application configuration.
When to Use
Use GitOps workflows for:
- Kubernetes Deployments: Automating application and infrastructure deployments to Kubernetes clusters
- Multi-Cluster Management: Managing deployments across development, staging, production, and edge clusters
- Continuous Delivery: Implementing pull-based CD pipelines with automated reconciliation
- Drift Detection: Automatically detecting and correcting configuration drift from desired state
- Audit Requirements: Maintaining complete audit trails via Git commits for compliance
- Progressive Delivery: Implementing canary, blue-green, or rolling deployment strategies
- Disaster Recovery: Enabling rapid cluster recovery with GitOps bootstrap processes
Trigger keywords: "deploy to Kubernetes", "ArgoCD setup", "Flux bootstrap", "GitOps pipeline", "environment promotion", "multi-cluster deployment", "automated reconciliation"
Core GitOps Principles
1. Git as Single Source of Truth
All system configuration stored in Git repositories. No manual kubectl apply or cluster modifications. Declarative manifests (YAML) for all Kubernetes resources, environment-specific overlays, infrastructure configuration, and application deployments.
2. Pull-Based Deployment
Operators running inside clusters pull changes from Git and apply them automatically. Benefits include no cluster credentials in CI/CD pipelines, support for air-gapped environments, self-healing through continuous reconciliation, and simplified CI/CD.
3. Automated Reconciliation
GitOps operators continuously compare actual cluster state with desired state in Git and reconcile differences through a continuous loop: watch Git, compare live state, apply differences, report status, repeat.
4. Declarative Configuration
What ships with it
26 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.
- examples/argocd/application.yaml 862 B
- examples/argocd/applicationset.yaml 1.4 KB
- examples/argocd/progressive-rollout.yaml 1.8 KB
- examples/argocd/sync-hooks.yaml 1.9 KB
- examples/flux/gitrepository.yaml 561 B
- examples/flux/helmrelease.yaml 1.1 KB
- examples/flux/kustomization.yaml 889 B
- examples/flux/ocirepository.yaml 743 B
- examples/kustomize/base/kustomization.yaml 196 B
- examples/kustomize/overlays/dev/kustomization.yaml 414 B
- examples/kustomize/overlays/prod/kustomization.yaml 774 B
- examples/kustomize/overlays/staging/kustomization.yaml 417 B
- examples/rollouts/blue-green.yaml 1.4 KB
- examples/rollouts/canary.yaml 1.6 KB
- outputs.yaml 7.6 KB
- references/argocd-patterns.md 14 KB
- references/drift-remediation.md 4.2 KB
- references/flux-patterns.md 15 KB
- references/kustomize-overlays.md 10 KB
- references/multi-cluster.md 2.6 KB
- references/progressive-delivery.md 12 KB
- references/secret-management.md 3.5 KB
- scripts/check-drift.sh 1.6 KB runs code
- scripts/install-argocd.sh 847 B runs code
- scripts/install-flux.sh 1.1 KB runs code
- scripts/promote-env.sh 1.5 KB runs code
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.
- 2d ago First seen · 345 lines · 49 tokens per session scan A cfb364a9720f
implementing-gitops is a skill published in the GitHub repository ancoleman/ai-design-components (517 stars, last pushed 8mo ago), licensed MIT. It adds 49 tokens to every session and 2,618 once invoked, about $0.0002 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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