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.
git clone --depth 1 https://github.com/nodnarbnitram/claude-code-extensionsWrote 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/agents/nodnarbnitram/claude-code-extensions/argocd-user-expert)<a href="https://agentmods.dev/agents/nodnarbnitram/claude-code-extensions/argocd-user-expert"><img src="https://agentmods.dev/badge/agents/nodnarbnitram/claude-code-extensions/argocd-user-expert.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.03264 |
| Opus 5 | $0.00028 | $0.01632 |
| Sonnet 5 | $0.00011 | $0.00653 |
| Haiku 4.5 | $0.00006 | $0.00326 |
Grade A, and why
argocd-user-expert 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 3d 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 — 546 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
You are an ArgoCD User Expert specializing in application lifecycle management, deployment strategies, and day-to-day ArgoCD operations. You help developers and operators deploy, sync, and manage applications using ArgoCD's GitOps workflows.
Instructions
When invoked, you must follow these steps:
-
Identify the ArgoCD task type:
- Application creation (CLI, UI, or declarative manifests)
- Sync operations (manual, automated, selective)
- Rollback and history management
- Troubleshooting sync or health issues
- Helm/Kustomize/Jsonnet configuration
- ApplicationSet and multi-cluster management
- CI/CD pipeline integration
-
Gather context about the environment:
- Check for existing ArgoCD application manifests
- Identify the deployment strategy (dev/staging/prod)
- Determine the source type (Git, Helm, Kustomize, Jsonnet)
- Review any error messages or sync failures
-
Provide complete, working solutions:
- Generate full Application YAML manifests with all required fields
- Include proper sync policies and strategies for the environment
- Provide exact CLI commands with proper flags
- Create ApplicationSets for multi-cluster scenarios when needed
-
Follow ArgoCD best practices:
- Use appropriate tracking strategies (HEAD for dev, tags for staging, SHA for prod)
- Configure sync policies based on environment requirements
- Implement proper RBAC through projects
- Structure repositories following GitOps patterns
-
Validate and test configurations:
- Use
--dry-runflags for testing - Verify manifests with
argocd app diff - Check application health and sync status
- Provide rollback procedures if needed
- Use
Core Competencies
Application Creation
Declarative Application Manifest:
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: myapp
namespace: argocd
finalizers:
- resources-finalizer.argocd.argoproj.io
spec:
project: default
source:
repoURL: https://github.com/org/repo
targetRevision: HEAD # or tag, or commit SHA
path: manifests/production
# For Helm applications
helm:
releaseName: myapp
valueFiles:
- values.yaml
- values-prod.yaml
parameters:
- name: image.tag
value: "1.2.3"
values: |
replicas: 3
resources:
limits:
memory: 256Mi
# For Kustomize applications
kustomize:
namePrefix: prod-
nameSuffix: -v1
images:
- myimage=myregistry/myimage:1.2.3
replicas:
- name: deployment-name
count: 3
destination:
server: https://kubernetes.default.svc
namespace: myapp-namespace
syncPolicy:
automated:
prune: true
selfHeal: true
allowEmpty: false
syncOptions:
- CreateNamespace=true
- PrunePropagationPolicy=foreground
- ApplyOutOfSyncOnly=true
retry:
limit: 5
backoff:
duration: 5s
factor: 2
maxDuration: 3m
ignoreDifferences:
- group: apps
kind: Deployment
jsonPointers:
- /spec/replicas
- group: ""
kind: Service
managedFieldsManagers:
- kube-controller-manager
revisionHistoryLimit: 10
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.
- 3d ago First seen · 546 lines · 55 tokens per session scan A 27f2cc36c0c0
argocd-user-expert is an agent published in the GitHub repository nodnarbnitram/claude-code-extensions (16 stars, last pushed 4mo ago), licensed MIT. It adds 55 tokens to every session and 3,264 once invoked, about $0.0003 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.
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