render-debug
GitHub用于调试 Render 部署失败，通过分析日志、指标和数据库状态定位根因（如缺失环境变量、OOM等）并提供修复建议。适用于服务崩溃、健康检查超时或生产环境报错场景。
Trigger Scenarios
Install
npx skills add fanfan-de/anybox --skill render-debug -g -y
SKILL.md
Frontmatter
{
"name": "render-debug",
"license": "MIT",
"metadata": {
"author": "Render",
"version": "1.1.0",
"category": "debugging"
},
"description": "Debug failed Render deployments by analyzing logs, metrics, and database state. Identifies errors (missing env vars, port binding, OOM, etc.) and suggests fixes. Use when deployments fail, services won't start, or users mention errors, logs, or debugging.",
"compatibility": "Requires Render MCP tools or CLI"
}
Debug Render Deployments
Analyze deployment failures using logs, metrics, and database queries. Identify root causes and apply fixes.
When to Use This Skill
Activate this skill when:
- Deployment fails on Render
- Service won't start or keeps crashing
- User mentions errors, logs, or debugging
- Health checks are timing out
- Application errors in production
- Performance issues (slow responses)
- Database connection problems
Prerequisites
MCP tools (preferred): Test with list_services() - provides structured data
CLI (fallback): render --version - use if MCP tools unavailable
Authentication: For MCP, use an API key (set in the MCP config or via the RENDER_API_KEY env var, depending on tool). For CLI, verify with render whoami -o json.
Workspace: get_selected_workspace() or render workspace current -o json
Note: MCP tools require the Render MCP server. If unavailable, use the CLI for logs and deploy status; metrics and structured database queries require MCP.
MCP Setup
If list_services() fails, set up the Render MCP server. For detailed per-tool walkthroughs, see render-mcp.
Quick setup: Add the Render MCP server to your AI tool's MCP config:
- URL:
https://mcp.render.com/mcp - Auth header:
Authorization: Bearer <YOUR_API_KEY> - API key:
https://dashboard.render.com/u/*/settings#api-keys
After configuring, restart your tool and retry list_services(). Then set your workspace with list_workspaces() / get_selected_workspace().
Debugging Workflow
Step 1: Identify Failed Service
list_services()
If MCP isn't configured, ask whether to set it up (preferred) or continue with CLI. Then proceed.
Look for services with failed status. Get details:
get_service(serviceId: "<id>")
Step 2: Retrieve Logs
Build/Deploy Logs (most failures):
list_logs(resource: ["<service-id>"], type: ["build"], limit: 200)
Runtime Error Logs:
list_logs(resource: ["<service-id>"], level: ["error"], limit: 100)
Search for Specific Errors:
list_logs(resource: ["<service-id>"], text: ["KeyError", "ECONNREFUSED"], limit: 50)
HTTP Error Logs:
list_logs(resource: ["<service-id>"], statusCode: ["500", "502", "503"], limit: 50)
Step 3: Analyze Error Patterns
Match log errors against known patterns:
| Error | Log Pattern | Common Fix |
|---|---|---|
| MISSING_ENV_VAR | KeyError, not defined |
Add to render.yaml or update_environment_variables |
| PORT_BINDING | EADDRINUSE |
Use 0.0.0.0:$PORT |
| MISSING_DEPENDENCY | Cannot find module |
Add to package.json/requirements.txt |
| DATABASE_CONNECTION | ECONNREFUSED :5432 |
Check DATABASE_URL, DB status |
| HEALTH_CHECK | Health check timeout |
Add /health endpoint, check port binding |
| OUT_OF_MEMORY | heap out of memory, exit 137 |
Optimize memory or upgrade plan |
| BUILD_FAILURE | Command failed |
Fix build command or dependencies |
Full error catalog: references/error-patterns.md
If errors repeat across deploys: Switch from incremental fixes to a broader sweep. Scan the codebase/config for all likely causes in that error class (related env vars, build config, dependencies, or type errors) and address them together before the next redeploy.
Step 4: Check Metrics (Performance Issues)
For crashes, slow responses, or resource issues:
get_metrics(
resourceId: "<service-id>",
metricTypes: ["cpu_usage", "memory_usage", "memory_limit"]
)
get_metrics(
resourceId: "<service-id>",
metricTypes: ["http_latency"],
httpLatencyQuantile: 0.95
)
Detailed metrics guide: references/metrics-debugging.md
Step 5: Debug Database Issues
For database-related errors:
# Check database status
list_postgres_instances()
# Check connections
get_metrics(resourceId: "<postgres-id>", metricTypes: ["active_connections"])
# Query directly
query_render_postgres(
postgresId: "<postgres-id>",
sql: "SELECT state, count(*) FROM pg_stat_activity GROUP BY state"
)
Detailed database guide: references/database-debugging.md
Step 6: Apply Fix
For environment variables:
update_environment_variables(
serviceId: "<service-id>",
envVars: [{"key": "MISSING_VAR", "value": "value"}]
)
For code changes:
- Edit the source file
- Commit and push
- Deploy triggers automatically (if auto-deploy enabled)
Step 7: Verify Fix
# Check deploy status
list_deploys(serviceId: "<service-id>", limit: 1)
# Check for new errors
list_logs(resource: ["<service-id>"], level: ["error"], limit: 20)
# Check metrics
get_metrics(resourceId: "<service-id>", metricTypes: ["http_request_count"])
Quick Workflows
Pre-built debugging sequences for common scenarios:
| Scenario | Workflow |
|---|---|
| Deploy failed | list_deploys → list_logs(type: build) → fix → redeploy |
| App crashing | list_logs(level: error) → get_metrics(memory) → fix |
| App slow | get_metrics(http_latency) → get_metrics(cpu) → query_postgres |
| DB connection | list_postgres → get_metrics(connections) → query_postgres |
| Post-deploy check | list_deploys → list_logs(error) → get_metrics |
Detailed workflows: references/quick-workflows.md
Quick Reference
MCP Tools
# Service Discovery
list_services()
get_service(serviceId: "<id>")
list_postgres_instances()
# Logs
list_logs(resource: ["<id>"], level: ["error"], limit: 100)
list_logs(resource: ["<id>"], type: ["build"], limit: 200)
list_logs(resource: ["<id>"], text: ["search"], limit: 50)
# Metrics
get_metrics(resourceId: "<id>", metricTypes: ["cpu_usage", "memory_usage"])
get_metrics(resourceId: "<id>", metricTypes: ["http_latency"], httpLatencyQuantile: 0.95)
# Database
query_render_postgres(postgresId: "<id>", sql: "SELECT ...")
# Deployments
list_deploys(serviceId: "<id>", limit: 5)
# Environment Variables
update_environment_variables(serviceId: "<id>", envVars: [{key, value}])
CLI Commands (Fallback)
render services -o json
render logs -r <service-id> --level error -o json
render logs -r <service-id> --tail -o text
render deploys create <service-id> --wait
References
- Error patterns: references/error-patterns.md
- Metrics debugging: references/metrics-debugging.md
- Database debugging: references/database-debugging.md
- Quick workflows: references/quick-workflows.md
- Log analysis: references/log-analysis.md
- Troubleshooting: references/troubleshooting.md
Related Skills
- render-deploy — Deploy new applications to Render
- render-monitor — Ongoing service health monitoring
- render-mcp — MCP server setup and tool catalog
Version History
- 08dc189 Current 2026-07-05 19:05
