SKILL.md
Datadog Observability — Gram Project
Gram Services
Always filter by the relevant service(s) when querying Datadog:
| Service | Description |
|---|---|
gram |
Dashboard frontend (RUM) |
gram-dashboard |
Dashboard backend |
gram-server |
Main backend API server |
gram-worker |
Temporal worker |
fly |
Fly.io — where Gram Functions logs are collected |
Available Tools
Use only the following Datadog MCP tools unless the user explicitly asks for others:
Logs
mcpdatadog-mcpsearchdatadoglogs— Search and filter log eventsmcpdatadog-mcpanalyzedatadoglogs— Analyze log patterns and aggregate stats
Metrics
mcpdatadog-mcpgetdatadogmetric— Get a specific metric's time-series datamcpdatadog-mcpgetdatadogmetric_context— Get context and metadata for a metricmcpdatadog-mcpsearchdatadogmetrics— Search available metrics by name
Traces & Spans
mcpdatadog-mcpgetdatadogtrace— Get a specific trace by IDmcpdatadog-mcpsearchdatadogspans— Search spans (useful for latency investigation)
Incidents & Monitors
mcpdatadog-mcpsearchdatadogincidents— Search active/recent incidentsmcpdatadog-mcpgetdatadogincident— Get details for a specific incidentmcpdatadog-mcpsearchdatadogmonitors— Find monitors and their current state
RUM & Events
mcpdatadog-mcpsearchdatadogrum_events— Search Real User Monitoring events (frontend errors, sessions)mcpdatadog-mcpsearchdatadogevents— Search Datadog events stream
Services & Infrastructure
mcpdatadog-mcpsearchdatadogservices— Discover services in APMmcpdatadog-mcpsearchdatadogservice_dependencies— View service dependency map
Guidelines
- Always scope queries to one or more Gram services using the service filter when available.
- Start narrow, expand if needed: Query a 15–30 minute window first, then widen.
- For error investigations: start with
searchdatadoglogs, filter bystatus:error, then follow trace IDs withgetdatadogtrace. - For latency issues: use
searchdatadogspanswithservice:<name>and sort by duration. - For frontend issues: prefer
searchdatadogrum_eventsforgram. - For incidents: check
searchdatadogincidentsfirst before deep-diving into logs.