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Debugging Apex Logs

  • 486 installs
  • 787 repo stars
  • Updated August 5, 2026
  • forcedotcom/afv-library

This is a copy of debugging-apex-logs by forcedotcom - installs and ranking accrue to the original listing.

debugging-apex-logs is a Salesforce skill that analyzes Apex debug logs for governor-limit violations, slow queries, and heap or CPU pressure while producing structured root-cause findings and a 100-point quality score.

About

debugging-apex-logs is an agent skill that analyzes Salesforce debug logs to surface root causes of governor limit violations, slow queries, heap and CPU pressure, and exception stack traces. It extracts query plans, transaction context, and performance bottlenecks then returns a 100-point scoring breakdown plus a prioritized reproduction-to-fix loop. Developers working on Salesforce orgs use it after an error surfaces in production or a sandbox to turn raw log output into actionable next steps instead of manually scanning thousands of lines. The skill gathers required context such as org alias and failing transaction before starting analysis and will hand off to code-generation skills once the root cause is confirmed.

  • Performs governor-limit diagnosis, stack-trace interpretation, and SOQL/DML performance analysis from .log files
  • Delivers 100-point scoring system for debug log quality and issue severity
  • Creates reproduction-to-fix loop based on concrete log evidence
  • Explicitly routes to running-apex-tests or generating-apex when those tasks are detected

Debugging Apex Logs by the numbers

  • 486 all-time installs (skills.sh)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/forcedotcom/afv-library --skill debugging-apex-logs

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Listed on Skillselion
Installs486
repo stars787
Last updatedAugust 5, 2026
Repositoryforcedotcom/afv-library

Why is my Salesforce Apex debug log failing?

Get structured root-cause analysis and a 100-point score when Salesforce debug logs show governor limit violations, slow queries, or heap pressure.

Who is it for?

Salesforce developers debugging governor-limit exceptions, slow queries, or heap and CPU warnings from downloaded Apex debug logs.

Skip if: Teams only running Apex tests, generating Apex source, or analyzing Agentforce session traces without classic debug logs.

When should I use this skill?

User uploads or references Salesforce debug .log files, governor limits, stack traces, or heap and CPU pressure symptoms.

What you get

Root-cause analysis report, governor-limit diagnosis, and 100-point debug-log quality score.

  • root-cause report
  • 100-point log score

By the numbers

  • Uses a 100-point scoring rubric for debug-log analysis
  • Skill metadata version 1.1 in afv-library

Files

SKILL.mdMarkdownGitHub ↗

debugging-apex-logs: Salesforce Debug Log Analysis & Troubleshooting

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 Task

Use debugging-apex-logs when the work involves:

  • .log files 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 → running-apex-tests
  • generating or implementing the code fix → generating-apex
  • debugging Agentforce session traces / parquet telemetry → observing-agentforce

---

Required Context to Gather First

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

Use the commands in references/cli-commands.md to list, download, or stream logs for the target org.

2. Analyze in this order

1. entry point and transaction type 2. exceptions / fatal errors 3. governor limits 4. repeated SOQL / DML patterns 5. CPU / heap hotspots 6. callout timing and external failures

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

IssuePrimary signalDefault fix direction
SOQL in looprepeating SOQL_EXECUTE_BEGIN in a repeated call pathquery once, use maps / grouped collections
DML in looprepeated DML_BEGIN patternscollect rows, bulk DML once
Non-selective queryhigh rows scanned / poor selectivityadd indexed filters, reduce scope
CPU pressureCPU usage approaching sync limitreduce algorithmic complexity, cache, async where valid
Heap pressureheap usage approaching sync limitstream with SOQL for-loops, reduce in-memory data
Null pointer / fatal errorEXCEPTION_THROWN / FATAL_ERRORguard null assumptions, fix empty-query handling

Expanded examples: references/common-issues.md

---

Output Format

When finishing analysis, report in this order:

1. What failed 2. Where it failed (class / method / line / transaction stage) 3. Why it failed (root cause, not just symptom) 4. How severe it is 5. Recommended fix 6. Verification step

Suggested shape:

Issue: <summary>
Location: <class / line / transaction>
Root cause: <explanation>
Severity: Critical | Warning | Info
Fix: <specific action>
Verify: <test or rerun step>

---

Rules / Constraints

RuleRationale
Always base fix recommendations on log evidenceAvoid speculative diagnosis — root cause must be traceable in the log
Report all six output fields for every issue foundEnsures actionable, complete findings for each problem
Classify every finding as Critical, Warning, or InfoHelps the user prioritize which issues to address first
Delegate code generation to generating-apexThis skill diagnoses; it does not rewrite Apex code
Delegate test execution to running-apex-testsThis skill does not run or repair test classes
Never assume limits are safe without reading LIMIT_USAGE eventsLimits may be consumed by earlier operations not visible in the failure point

---

Gotchas

PitfallResolution
Log truncated at 2 MBReduce debug levels (e.g., ApexCode: INFO, ApexProfiling: FINE) and re-capture
Same issue appears as both SOQL and CPU problemFix SOQL-in-loop first — it typically drives the CPU spike as a secondary effect
No logs appear after trace flag is setVerify the trace flag ExpirationDate is in the future and the correct user is traced
Async context changes limit valuesCPU limit is 60,000 ms async vs 10,000 ms sync — check transaction type before flagging limits
Stack trace points to framework line, not user codeWalk up the call stack past trigger handlers to find the originating user code

---

Cross-Skill Integration

NeedDelegate toReason
Implement Apex fixgenerating-apexcode change generation / review
Reproduce via testsrunning-apex-teststest execution and coverage loop
Deploy fixdeploying-metadatadeployment orchestration
Create debugging datahandling-sf-datatargeted seed / repro data

---

Reference File Index

FileWhen to read
references/analysis-playbook.mdStart here — expanded step-by-step workflow for any debugging session
references/common-issues.mdQuick lookup for SOQL in loop, DML in loop, CPU/heap pressure, null pointer patterns
references/cli-commands.mdSF CLI commands for retrieving, streaming, and managing debug logs
references/debug-log-reference.mdFull event type catalog, log levels, and governor limit reference values
references/log-analysis-tools.mdTool guide: Apex Log Analyzer, Developer Console, CLI grep patterns
references/benchmarking-guide.mdPerformance benchmarking techniques, benchmark data, and anti-patterns
references/scoring-rubric.md100-point scoring rubric for evaluating analysis quality
assets/benchmarking-template.clsCopy-paste Anonymous Apex template for running performance benchmarks
assets/cpu-heap-optimization.clsApex patterns for reducing CPU time and heap allocation
assets/dml-in-loop-fix.clsBefore/after example for resolving DML-in-loop violations
assets/soql-in-loop-fix.clsBefore/after example for resolving SOQL-in-loop violations
assets/null-pointer-fix.clsPatterns for guarding against null pointer exceptions

---

Score Guide

ScoreMeaning
90+Expert analysis with strong fix guidance
80–89Good analysis with minor gaps
70–79Acceptable but may miss secondary issues
60–69Partial diagnosis only
< 60Incomplete analysis

Related skills

How it compares

Use debugging-apex-logs for downloaded .log triage; switch to running-apex-tests when failures appear only during test execution.

FAQ

What does the 100-point score measure in debugging-apex-logs?

debugging-apex-logs applies a 100-point scoring rubric (version 1.1) to rate debug-log quality and issue severity while summarizing governor-limit, SOQL, heap, and CPU root causes.

Which Salesforce tasks should not use debugging-apex-logs?

debugging-apex-logs should not run Apex tests (use running-apex-tests), generate Apex code (use generating-apex), or trace Agentforce sessions (use observing-agentforce).

Debuggingbackendintegrations

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