Kubeshark
Repository: kubeshark
Author: kubeshark · Source status: Clear source
eBPF-powered network observability for Kubernetes.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
Score-basis diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Pre-install score, evidence completeness, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
coolify-mcp
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
accessibility-scanner
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
dapr
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | coolify-mcp | accessibility-scanner | dapr |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 79 · Manual review | 90 · Manual review | 92 · Manual review |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap |
Evidence completeness | 67% | 65% | 65% |
| Source & provenance | |||
Provenance | StuMason/coolify-mcp | github/accessibility-scanner | dapr/dapr |
Category | Operations & Infra | Agent & Tools | Automation & Workflows |
Freshness | |||
| Risk & permission signals | |||
Audit signals | No explicit signals | metadata-only | metadata-only |
Permission hints | repository clone, local runtime dependencies | repository clone | repository clone |
| Install & compatibility | |||
Install friction | 40 | 75 | 75 |
| Community | |||
Stars | 297 | 260 | 25.7K |
Repository: mcp-for-argocd
Author: argoproj-labs · Source status: Clear source
An implementation of Model Context Protocol (MCP) server for Argo CD.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: certctl
Author: shankar0123 · Source status: Clear source
Self-hosted certificate lifecycle automation platform.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: mcp-ssh-manager
Author: bvisible · Source status: Clear source
MCP SSH Server: 37 tools for remote SSH management | Claude Code & OpenAI Codex | DevOps automation, backups, database operations, health monitoring Topics: anthropic, automation, backup, claude-code, database, deploymen
Score basis:Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: claude-code
Author: anthropics · Source status: Clear source
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT}
Score basis:Clear source · High execution risk · Claude · Evidence completeness 65%
Repository: skillhub
Author: iflytek · Source status: Clear source
Self-hosted, open-source agent skill registry for enterprises.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-08 |
2026-04-14 |
2026-04-11 |