Query CPU, memory, network, and disk usage metrics for Railway services.
Works with
Supports nine metric types including CPU usage, memory, network traffic (RX/TX), and disk usage across deployments and instances
Query metrics for a single service or all services in an environment using optional groupBy parameters (by deployment, instance, region, or service)
Requires environmentId from railway status --json ; serviceId is optional to retrieve metrics across all services
Time-based queries w
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmetricsExecute the skills CLI command in your project's root directory to begin installation:
Fetches metrics from railwayapp/railway-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate metrics. Access via /metrics in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Query resource usage metrics for Railway services.
service skill)Get environmentId and serviceId from linked project:
railway status --json
Extract:
environment.id β environmentIdservice.id β serviceId (optional - omit to get all services)| Measurement | Description |
|---|---|
| CPU_USAGE | CPU usage (cores) |
| CPU_LIMIT | CPU limit (cores) |
| MEMORY_USAGE_GB | Memory usage in GB |
| MEMORY_LIMIT_GB | Memory limit in GB |
| NETWORK_RX_GB | Network received in GB |
| NETWORK_TX_GB | Network transmitted in GB |
| DISK_USAGE_GB | Disk usage in GB |
| EPHEMERAL_DISK_USAGE_GB | Ephemeral disk usage in GB |
| BACKUP_USAGE_GB | Backup usage in GB |
| Tag | Description |
|---|---|
| DEPLOYMENT_ID | Group by deployment |
| DEPLOYMENT_INSTANCE_ID | Group by instance |
| REGION | Group by region |
| SERVICE_ID | Group by service |
query metrics(
$environmentId: String!
$serviceId: String
$startDate: DateTime!
$endDate: DateTime
$sampleRateSeconds: Int
$averagingWindowSeconds: Int
$groupBy: [MetricTag!]
$measurements: [MetricMeasurement!]!
) {
metrics(
environmentId: $environmentId
serviceId: $serviceId
startDate: $startDate
endDate: $endDate
sampleRateSeconds: $sampleRateSeconds
averagingWindowSeconds: $averagingWindowSeconds
groupBy: $groupBy
measurements: $measurements
) {
measurement
tags {
deploymentInstanceId
deploymentId
serviceId
region
}
values {
ts
value
}
}
}
Use heredoc to avoid shell escaping issues:
bash <<'SCRIPT'
START_DATE=$(date -u -v-1H +"%Y-%m-%dT%H:%M:%SZ" 2>/dev/null || date -u -d "1 hour ago" +"%Y-%m-%dT%H:%M:%SZ")
ENV_ID="your-environment-id"
SERVICE_ID="your-service-id"
VARS=$(jq -n \
--arg env "$ENV_ID" \
--arg svc "$SERVICE_ID" \
--arg start "$START_DATE" \
'{environmentId: $env, serviceId: $svc, startDate: $start, measurements: ["CPU_USAGE", "MEMORY_USAGE_GB"]}')
scripts/railway-api.sh \
'query metrics($environmentId: String!, $serviceId: String, $startDate: DateTime!, $measurements: [MetricMeasurement!]!) {
metrics(environmentId: $environmentId, serviceId: $serviceId, startDate: $startDate, measurements: $measurements) {
measurement
tags { deploymentId region serviceId }
values { ts value }
}
}' \
"$VARS"
SCRIPT
Omit serviceId and use groupBy to get metrics for all services:
bash <<'SCRIPT'
START_DATE=$(date -u -v-1H +"%Y-%m-%dT%H:%M:%SZ" 2>/dev/null || date -u -d "1 hour ago" +"%Y-%m-%dT%H:%M:%SZ")
ENV_ID="your-environment-id"
VARS=$(jq -n \
--arg env "$ENV_ID" \
--arg start "$START_DATE" \
'{environmentId: $env, startDate: $start, measurements: ["CPU_USAGE", "MEMORY_USAGE_GB"], groupBy: ["SERVICE_ID"]}')
scripts/railway-api.sh \
'query metrics($environmentId: String!, $startDate: DateTime!, $measurements: [MetricMeasurement!]!, $groupBy: [MetricTag!]) {
metrics(environmentId: $environmentId, startDate: $startDate, measurements: $measurements, groupBy: $groupBy) {
measurement
tags { serviceId region }
values { ts value }
}
}' \
"$VARS"
SCRIPT
| Parameter | Description |
|---|---|
| startDate | Required. ISO 8601 format (e.g., 2024-01-01T00:00:00Z) |
| endDate | Optional. Defaults to now |
| sampleRateSeconds | Sample interval (e.g., 60 for 1-minute samples) |
| averagingWindowSeconds | Averaging window for smoothing |
Tip: For last hour, calculate startDate as now - 1 hour in ISO format.
{
"data": {
"metrics": [
{
"measurement": "CPU_USAGE",
"tags": { "deploymentId": "...", "serviceId": "...", "region": "us-west1" },
"values": [
{ "ts": "2024-01-01T00:00:00Z", "value": 0.25 },
{ "ts": "2024-01-01T00:01:00Z", "value": 0.30 }
]
}
]
}
}
ts - timestamp in ISO formatvalue - metric value (cores for CPU, GB for memory/disk/network)status skill or railway status --jsonservice skill for deployment statusdeployment skill if metrics show issuesenvironment skill to adjust resourcesServices without active deployments return empty metrics arrays. When processing with jq, handle nulls:
# Safe iteration - skip nulls
jq -r '.data.metrics[]? | select(.values != null and (.values | length) > 0) | ...'
# Check if metrics exist before processing
jq -e '.data.metrics | length > 0' response.json && echo "has metrics"
Service may be new or have no traffic. Check:
Verify IDs with railway status --json.
User needs access to the project to query metrics.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
β Do
β Don't
π‘ Pro Tips
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
mattpocock/skills
ailabs-393/ai-labs-claude-skills
We added metrics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
metrics reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend metrics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: metrics is focused, and the summary matches what you get after install.
Registry listing for metrics matched our evaluation β installs cleanly and behaves as described in the markdown.
metrics has been reliable in day-to-day use. Documentation quality is above average for community skills.
metrics fits our agent workflows well β practical, well scoped, and easy to wire into existing repos.
metrics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in metrics β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: metrics is focused, and the summary matches what you get after install.
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