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 neverinfamous/mysql-mcp --skill troubleshoot-ssigit clone --depth 1 https://github.com/neverinfamous/mysql-mcpWrote 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/neverinfamous/mysql-mcp/troubleshoot-ssi)<a href="https://agentmods.dev/skills/neverinfamous/mysql-mcp/troubleshoot-ssi"><img src="https://agentmods.dev/badge/skills/neverinfamous/mysql-mcp/troubleshoot-ssi/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/neverinfamous/mysql-mcp/troubleshoot-ssi"><img src="https://agentmods.dev/badge/skills/neverinfamous/mysql-mcp/troubleshoot-ssi.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 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 YARA Match · line 97 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
- medium Data Exfiltration · line 48 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Excessive Agency · line 408 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00052 | $0.04425 |
| Opus 5 | $0.00026 | $0.02212 |
| Sonnet 5 | $0.00010 | $0.00885 |
| Haiku 4.5 | $0.00005 | $0.00443 |
Grade A, and why
troubleshoot-ssi scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
PUP_VERSION=$(curl -s https://api.github.com/repos/datadog-labs/pup/releases/latest | grep '"tag_name"' | cut -d'"' -f4) How it starts
The opening of the file, as written. The whole thing — 420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Troubleshoot APM SSI on Kubernetes
Triggers
Invoke this skill when the user expresses intent to:
- Debug why a pod is not being instrumented
- Investigate why traces are not appearing in Datadog
- Diagnose admission webhook or init container injection failures
- Follow up on failed checks from
verify-ssi - Report that a specific service or pod has no traces
Do NOT invoke this skill if:
- SSI has not been enabled yet — run
enable-ssifirst
Prerequisites
- kubectl configured to target cluster —
kubectl config current-context
pup-cli: check, install, and authenticate
Claude runs
pup --version
If not found, install it (OS-aware):
Claude runs
if [[ "$(uname)" == "Darwin" ]]; then
brew tap datadog-labs/pack && brew install pup
else
PUP_VERSION=$(curl -s https://api.github.com/repos/datadog-labs/pup/releases/latest | grep '"tag_name"' | cut -d'"' -f4)
curl -L "https://github.com/datadog-labs/pup/releases/download/${PUP_VERSION}/pup_linux_amd64.tar.gz" | tar xz -C /usr/local/bin pup
chmod +x /usr/local/bin/pup
fi
pup --version
Check auth:
pup auth status
If not authenticated:
Claude runs
pup auth login
This opens a browser tab for OAuth. Complete the login there — Claude will continue once the command exits.
If no browser available: export DD_APP_KEY=<your-app-key>.
Context to resolve before acting
| Variable | How to resolve |
|---|---|
AGENT_NAMESPACE |
Namespace where Datadog Agent is installed |
APP_NAMESPACE |
Namespace of the application with missing traces |
CLUSTER_NAME |
kubectl config current-context or spec.global.clusterName in datadog-agent.yaml |
SERVICE_NAME |
tags.datadoghq.com/service label on the Deployment, or ask the user |
ENV |
tags.datadoghq.com/env label on the Deployment, or ask the user |
POD_NAME |
kubectl get pods -n <APP_NAMESPACE> — use the specific pod the user mentioned |
DEPLOYMENT_NAME |
Check metadata.name in the Deployment manifest, or ask the user |
APP_LABEL |
Check spec.selector.matchLabels.app in the Deployment manifest |
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.
- 10d ago First seen · 420 lines · 52 tokens per session scan A 4977aee0bab4
troubleshoot-ssi is a skill published in the GitHub repository neverinfamous/mysql-mcp (10 stars, last pushed 3d ago), licensed MIT. It adds 52 tokens to every session and 4,425 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
kubernetes-patterns
Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.
image-pull-debug
Diagnose container image pull failures (ErrImagePull / ImagePullBackOff). Checks pod status, containerd logs, and events to identify root cause.
pod-pending-debug
Diagnose pod scheduling failures (Pending, Unschedulable). Checks events, node resources, taints, affinity, and PVC bindings to identify why a pod cannot be scheduled.
deploy-gen
Generate deployment configurations (Docker, Kubernetes) for the current project.
kubernetes-specialist
Use when managing Kubernetes clusters, debugging Pods and workloads, designing Helm charts, reviewing manifests, or improving deployment, scaling, and observability practices.
gke-workload-troubleshooting
Systematic Standard Operating Procedure (SOP) for diagnosing GKE workload failures, crash loops, resource OOMs, mounting errors, and connectivity timeouts.