Debug Logs
Read and analyze Salesforce debug logs. Paste the error, AI finds the root cause and tells you exactly what to fix.
Skill Details
Install this skill
Works with
Use this skill when the user needs root-cause analysis from debug logs: governor-limit diagnosis, stack-trace interpretation, slow-query investigation, heap / CPU pressure analysis, or a reproduction-to-fix loop based on log evidence.
When This Skill Owns the TaskWorkflow
Use sf-debug when the work involves:
.logfiles from Salesforce- stack traces and exception analysis
- governor limits
- SOQL / DML / CPU / heap troubleshooting
- query-plan or performance evidence extracted from logs
Delegate elsewhere when the user is:
- running or repairing Apex tests → sf-testing
- implementing the code fix → sf-apex
- debugging Agentforce session traces / parquet telemetry → sf-ai-agentforce-observability
Required Context to Gather FirstWorkflow
Ask for or infer:
- org alias
- failing transaction / user flow / test name
- approximate timestamp or transaction window
- user / record / request ID if known
- whether the goal is diagnosis only or diagnosis + fix loop
Recommended Workflow
1. Retrieve logs
sf apex list log --target-org <alias> --json
sf apex get log --log-id <id> --target-org <alias>
sf apex tail log --target-org <alias> --color
2. Analyze in this order
3. Classify severity
- Critical — runtime failure, hard limit, corruption risk
- Warning — near-limit, non-selective query, slow path
- Info — optimization opportunity or hygiene issue
4. Recommend the smallest correct fix
Prefer fixes that are:
- root-cause oriented
- bulk-safe
- testable
- easy to verify with a rerun
Expanded workflow: references/analysis-playbook.md
High-Signal Issue Patterns
| Issue | Primary signal | Default fix direction |
|---|---|---|
| SOQL in loop | repeating SOQL_EXECUTE_BEGIN in a repeated call path | query once, use maps / grouped collections |
| DML in loop | repeated DML_BEGIN patterns | collect rows, bulk DML once |
| Non-selective query | high rows scanned / poor selectivity | add indexed filters, reduce scope |
| CPU pressure | CPU usage approaching sync limit | reduce algorithmic complexity, cache, async where valid |
| Heap pressure | heap usage approaching sync limit | stream with SOQL for-loops, reduce in-memory data |
| Null pointer / fatal error | EXCEPTION_THROWN / FATAL_ERROR | guard null assumptions, fix empty-query handling |
| Need | Delegate to | Reason |
| Implement Apex fix | sf-apex | code change generation / review |
| Reproduce via tests | sf-testing | test execution and coverage loop |
| Deploy fix | sf-deploy | deployment orchestration |
| Create debugging data | sf-data | targeted seed / repro data |
| Score | Meaning | |
| 90+ | Expert analysis with strong fix guidance | |
| 80–89 | Good analysis with minor gaps | |
| 70–79 | Acceptable but may miss secondary issues | |
| 60–69 | Partial diagnosis only | |
| < 60 | Incomplete analysis |
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