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verify-ssi
Verify Single Step Instrumentation (SSI) is working end-to-end on Kubernetes — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run.
Resumen
Verify Single Step Instrumentation (SSI) is working end-to-end on Kubernetes — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run.
Leer documentación completa
Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.
Verify APM SSI on Linux
Before doing anything else: Fully resolve all variables in
## Context to resolve before acting. Do not begin Step 1 until every variable has a concrete value.
Triggers
Invoke this skill when the user expresses intent to:
- Confirm SSI is working after installing the Datadog Agent on Linux
- Check whether a Linux process is being instrumented
- Verify the tracer is running and reporting telemetry
Do NOT invoke this skill if:
- SSI has not been enabled yet — run
agent-installfirst - Services have not been restarted since the agent was installed — restart them first, then verify
Prerequisites
-
agent-installis complete - Application services have been restarted since the agent was installed
pup-cli: check, install, and authenticate
Claude runs
pup --version
If not found:
Claude runs
brew tap datadog-labs/pack
brew install pup
Check auth:
pup auth status --site <DD_SITE>
If not authenticated:
Claude runs
pup auth login --site <DD_SITE>
This opens a browser tab for OAuth. Complete the login there — Claude will continue once the command exits.
If valid token — proceed.
ERROR: No browser available: export DD_APP_KEY=<your-app-key>
Context to resolve before acting
| Variable | How to resolve |
|---|---|
DD_HOSTNAME | Hostname as Datadog sees it — from sudo datadog-agent status output |
SERVICE_NAME | Expected service name in APM — ask the user |
ENV | Environment tag — ask the user |
DD_SITE | grep "^site:" /etc/datadog-agent/datadog.yaml via SSH, or ask the user |
SSH_KEY | Path to SSH private key |
SSH_USER | SSH username |
SSH_HOST | Hostname or IP of the target host |
Step 1: Confirm the Process is Injected
Use /proc/<pid>/maps — this is the authoritative check. It shows the actual shared libraries loaded into the running process, which is the only way to confirm the launcher and tracer .so files were actually loaded.
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"pgrep -a -f '<SERVICE_NAME>' | head -5"
Use the PID from above:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo cat /proc/<PID>/maps | grep -E 'launcher|apm-library|datadog'"
If the output includes both the launcher (e.g. launcher.preload.so) and a language library (e.g. apm-library-python) — injection succeeded for this process.
ERROR: Launcher present but no language library — launcher ran but couldn't inject. Check for injection errors:
Claude runs
pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h
ERROR: Neither present — process was not injected. Check /etc/ld.so.preload:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> "cat /etc/ld.so.preload"
If empty — install did not set up the launcher. Re-run the install script with DD_APM_INSTRUMENTATION_ENABLED=host. If non-empty but the process still isn't injected — the process was started before the launcher was installed. Restart the service and recheck.
Step 2: Confirm the Agent is Receiving Traces
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo datadog-agent status 2>&1 | grep -A 15 'APM Agent'"
Healthy output shows:
feature_auto_instrumentation_enabled: trueReceiver (previous minute)with> 0traces
ERROR: feature_auto_instrumentation_enabled: false — SSI not active on the agent. Check apm_config in /etc/datadog-agent/datadog.yaml.
ERROR: Receiver (previous minute): 0 — agent running but no traces yet. Generate traffic first (see Step 3), then recheck.
Step 3: Confirm the Service is Visible in Datadog
Claude runs
DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 1h
If <SERVICE_NAME> appears with isTraced: true — traces are reaching the Datadog backend.
Flask / ddtrace v3 naming note: With ddtrace >=3.x, Flask spans are emitted as
service:flaskrather thanservice:<DD_SERVICE>. TheDD_SERVICEvalue appears asbase_serviceon the spans. If you setDD_SERVICE=my-app, search forservice:flaskin the APM UI — the service list will showflask, notmy-app. Check thebase_servicetag to confirm it matches yourDD_SERVICE.
ERROR: Service missing — generate traffic to trigger trace creation:
Claude runs
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"sudo ss -tlnp 2>/dev/null | grep <PID> || sudo netstat -tlnp 2>/dev/null | grep <PID>"
Use the port from above:
ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \
"for i in \$(seq 1 10); do curl -s -o /dev/null http://localhost:<PORT>/; done"
Wait 30 seconds, then retry:
DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 10m
DD_SITE=<DD_SITE> pup traces search --query "service:<SERVICE_NAME>" --from 10m --limit 5
ERROR: Still missing — check for injection errors and go to troubleshoot-ssi:
pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h
Done
Exit when ALL of the following are true:
- Step 1: launcher + language library both visible in
/proc/<PID>/maps - Step 2: agent APM receiver shows
> 0traces/min - Step 3: service appears in
pup apm services list
If any check fails, go to troubleshoot-ssi.
When all steps pass, automatically proceed to onboarding-summary now — do not ask the user for permission.
Security constraints
- Never write a raw API key into any file or chat message
- Always confirm before restarting production services
Metadatos del archivo
name: verify-ssi description: Verify Single Step Instrumentation (SSI) is working end-to-end on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run. metadata: version: "1.0.0" author: datadog-labs repository: https://github.com/datadog-labs/agent-skills tags: datadog,apm,linux,ssi,verification,instrumentation,ld-preload alwaysApply: "false"
Ver texto original
--- name: verify-ssi description: Verify Single Step Instrumentation (SSI) is working end-to-end on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run. metadata: version: "1.0.0" author: datadog-labs repository: https://github.com/datadog-labs/agent-skills tags: datadog,apm,linux,ssi,verification,instrumentation,ld-preload alwaysApply: "false" --- # Verify APM SSI on Linux > **Before doing anything else:** Fully resolve all variables in `## Context to resolve before acting`. Do not begin Step 1 until every variable has a concrete value. ## Triggers Invoke this skill when the user expresses intent to: - Confirm SSI is working after installing the Datadog Agent on Linux - Check whether a Linux process is being instrumented - Verify the tracer is running and reporting telemetry Do NOT invoke this skill if: - SSI has not been enabled yet — run `agent-install` first - Services have not been restarted since the agent was installed — restart them first, then verify --- ## Prerequisites - [ ] `agent-install` is complete - [ ] Application services have been restarted since the agent was installed ### pup-cli: check, install, and authenticate ### Claude runs ```bash pup --version ``` If not found: ### Claude runs ```bash brew tap datadog-labs/pack brew install pup ``` Check auth: ```bash pup auth status --site <DD_SITE> ``` If not authenticated: ### Claude runs ```bash pup auth login --site <DD_SITE> ``` > This opens a browser tab for OAuth. Complete the login there — Claude will continue once the command exits. If valid token — proceed. ERROR: No browser available: `export DD_APP_KEY=<your-app-key>` --- ## Context to resolve before acting | Variable | How to resolve | |---|---| | `DD_HOSTNAME` | Hostname as Datadog sees it — from `sudo datadog-agent status` output | | `SERVICE_NAME` | Expected service name in APM — ask the user | | `ENV` | Environment tag — ask the user | | `DD_SITE` | `grep "^site:" /etc/datadog-agent/datadog.yaml` via SSH, or ask the user | | `SSH_KEY` | Path to SSH private key | | `SSH_USER` | SSH username | | `SSH_HOST` | Hostname or IP of the target host | --- ## Step 1: Confirm the Process is Injected Use `/proc/<pid>/maps` — this is the authoritative check. It shows the actual shared libraries loaded into the running process, which is the only way to confirm the launcher and tracer `.so` files were actually loaded. ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "pgrep -a -f '<SERVICE_NAME>' | head -5" ``` Use the PID from above: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo cat /proc/<PID>/maps | grep -E 'launcher|apm-library|datadog'" ``` If the output includes both the launcher (e.g. `launcher.preload.so`) and a language library (e.g. `apm-library-python`) — injection succeeded for this process. ERROR: Launcher present but no language library — launcher ran but couldn't inject. Check for injection errors: ### Claude runs ```bash pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h ``` ERROR: Neither present — process was not injected. Check `/etc/ld.so.preload`: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> "cat /etc/ld.so.preload" ``` If empty — install did not set up the launcher. Re-run the install script with `DD_APM_INSTRUMENTATION_ENABLED=host`. If non-empty but the process still isn't injected — the process was started before the launcher was installed. Restart the service and recheck. --- ## Step 2: Confirm the Agent is Receiving Traces ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo datadog-agent status 2>&1 | grep -A 15 'APM Agent'" ``` Healthy output shows: - `feature_auto_instrumentation_enabled: true` - `Receiver (previous minute)` with `> 0` traces ERROR: `feature_auto_instrumentation_enabled: false` — SSI not active on the agent. Check `apm_config` in `/etc/datadog-agent/datadog.yaml`. ERROR: `Receiver (previous minute): 0` — agent running but no traces yet. Generate traffic first (see Step 3), then recheck. --- ## Step 3: Confirm the Service is Visible in Datadog ### Claude runs ```bash DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 1h ``` If `<SERVICE_NAME>` appears with `isTraced: true` — traces are reaching the Datadog backend. > **Flask / ddtrace v3 naming note:** With ddtrace >=3.x, Flask spans are emitted as `service:flask` rather than `service:<DD_SERVICE>`. The `DD_SERVICE` value appears as `base_service` on the spans. If you set `DD_SERVICE=my-app`, search for `service:flask` in the APM UI — the service list will show `flask`, not `my-app`. Check the `base_service` tag to confirm it matches your `DD_SERVICE`. ERROR: Service missing — generate traffic to trigger trace creation: ### Claude runs ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "sudo ss -tlnp 2>/dev/null | grep <PID> || sudo netstat -tlnp 2>/dev/null | grep <PID>" ``` Use the port from above: ```bash ssh -o StrictHostKeyChecking=no -i <SSH_KEY> <SSH_USER>@<SSH_HOST> \ "for i in \$(seq 1 10); do curl -s -o /dev/null http://localhost:<PORT>/; done" ``` Wait 30 seconds, then retry: ```bash DD_SITE=<DD_SITE> pup apm services list --env <ENV> --from 10m DD_SITE=<DD_SITE> pup traces search --query "service:<SERVICE_NAME>" --from 10m --limit 5 ``` ERROR: Still missing — check for injection errors and go to `troubleshoot-ssi`: ```bash pup apm troubleshooting list --hostname <DD_HOSTNAME> --timeframe 1h ``` --- ## Done Exit when ALL of the following are true: - [ ] Step 1: launcher + language library both visible in `/proc/<PID>/maps` - [ ] Step 2: agent APM receiver shows `> 0` traces/min - [ ] Step 3: service appears in `pup apm services list` If any check fails, go to `troubleshoot-ssi`. When all steps pass, automatically proceed to `onboarding-summary` now — do not ask the user for permission. --- ## Security constraints - Never write a raw API key into any file or chat message - Always confirm before restarting production services
Revisar el código fuente
Precio y costes de ejecución
- Obtener el skill
- Precio sin confirmar
- Ejecutarlo
- Requisitos sin confirmar. Consulta los costes del agente, API y servicios en la fuente.
- Licencia
- MIT
- Precio sin confirmar
- No hemos confirmado el precio. Los enlaces existentes al código y a la instalación siguen disponibles.
Obtener gratis no significa ejecutar gratis. El precio no es una evaluación de seguridad. Enviar información de precio →
La fuente requiere revisión
La fuente cambió o no pudo sincronizarse. Revísala antes de instalar.
Revisar antes de instalar: Evitar instalación automática
Licencia: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.
Empieza con una tarea pequeña
- 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
- 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
- 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.
Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.
Fuente y notas de uso
Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.
- Repositorio fuente
- datadog-labs/agent-skills
- Licencia
- MIT
- Versión
- 1.0.0
- Último push de GitHub
- 26 ago 2026
- Registro actualizado
- 6 sept 2026
- Ruta de instrucciones
- dd-apm/linux-ssi/verify-ssi/SKILL.md @ 157edafdc100
Versión declarada en el registro; consulta las versiones de la fuente.
Calidad
66/100
Prometedor
Confianza
63/100
Solo sandbox
Auditoría
75/100
Riesgoso
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Resultados
- —
Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.
Acceso para agentes
La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.
Más detalles
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"installSafety": "standard package or runtime install path",
"permissionSurface": "secrets or environment access, shell or command execution",
"documentation": "Strong README/SKILL.md context",
"agentOutcomes": "No agent outcome data yet"
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"label": "No agent outcome data yet"
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"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access",
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"signals": [],
"penalties": [
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"audit": {
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"risk_level": "risky",
"risk_label": "Risky",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
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"This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Stars/forks activity: 165 stars, 27 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access"
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"blocked": true,
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"label": "Promising"
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"Audit risk risky exceeds max_risk=medium",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required"
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"Trust: 71/100 Manual review",
"Audit: 75/100 Risky",
"Safety: 27/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "datadog-labs-verify-ssi (verify-ssi)",
"install_command": "",
"risk_summary": "Risky; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
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"method": "POST",
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"expected_outcomes": [
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"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
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"task": "Use verify-ssi in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
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"workspace": "sandbox",
"time_to_useful_ms": 120000,
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"endpoints": {
"web": "https://www.openagentskill.com/skills/datadog-labs-verify-ssi",
"api": "https://www.openagentskill.com/api/agent/skills/datadog-labs-verify-ssi",
"audit": "https://www.openagentskill.com/skills/datadog-labs-verify-ssi/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=datadog-labs-verify-ssi&task=Use%20verify-ssi%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20verify-ssi%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20verify-ssi%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/datadog-labs-verify-ssi/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/datadog-labs-verify-ssi"
}
}Para el creador
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