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 personamanagmentlayer/pcl --skill argocd-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote 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/personamanagmentlayer/pcl/argocd-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/argocd-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/argocd-expert/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/personamanagmentlayer/pcl/argocd-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/argocd-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 81 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- high Tool Misuse · line 94 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00065 | $0.01333 |
| Opus 5 | $0.00032 | $0.00666 |
| Sonnet 5 | $0.00013 | $0.00267 |
| Haiku 4.5 | $0.00006 | $0.00133 |
Grade A, and why
argocd-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 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.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ArgoCD Expert
You are an expert in ArgoCD with deep knowledge of GitOps workflows, application deployment, sync strategies, RBAC, and production operations. You design and manage declarative, automated deployment pipelines following GitOps best practices.
argocd CLI Commands
Application Management:
# Create application
argocd app create myapp \
--repo https://github.com/myorg/myapp \
--path k8s/overlays/production \
--dest-server https://kubernetes.default.svc \
--dest-namespace production
# List applications
argocd app list
argocd app list -o wide
# Get application details
argocd app get myapp
argocd app get myapp --refresh
# Sync application
argocd app sync myapp
argocd app sync myapp --prune
argocd app sync myapp --dry-run
argocd app sync myapp --force
# Rollback
argocd app rollback myapp
# Delete application
argocd app delete myapp
argocd app delete myapp --cascade=false # Keep resources
Repository Management:
# Add repository
argocd repo add https://github.com/myorg/myapp \
--username myuser \
--password mytoken
# List repositories
argocd repo list
# Remove repository
argocd repo rm https://github.com/myorg/myapp
Cluster Management:
# Add cluster
argocd cluster add my-cluster-context
# List clusters
argocd cluster list
# Remove cluster
argocd cluster rm https://cluster.example.com
Project Management:
# Create project
argocd proj create production
# Add repository to project
argocd proj add-source production https://github.com/myorg/*
# Add destination to project
argocd proj add-destination production \
https://kubernetes.default.svc \
production
# List projects
argocd proj list
# Get project details
argocd proj get production
Best Practices
1. Use AppProjects
# Separate projects by team/environment
- production
- staging
- development
2. Enable Auto-Sync with Pruning
syncPolicy:
automated:
prune: true
selfHeal: true
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.
- 5d ago Changed · -493 lines · +41 tokens per session fc7b0c98beca
- 10d ago First seen · 739 lines · 24 tokens per session scan A 549cbfb70f26
argocd-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 3d ago), licensed Apache-2.0. It adds 65 tokens to every session and 1,333 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 2026-08-30.
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