Focused Fix
Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end.
Before & after
Same prompt, same agent — the only difference is the skill.
When you have a feature that's broken, it's important to understand what the problem is first. You might start by looking at error logs or trying to reproduce the issue. The problem could be in different parts of the system - maybe the data retrieval is slow, or the export formatting is inefficient. You could add some logging or monitoring to understand where the bottleneck is. Testing edge cases like large datasets helps identify scaling issues. Once you know the root cause, you can fix it systematically rather than trying random solutions.
FOCUSED FIX: EXPORT FEATURE RECOVERY (100K+ ROWS)
ROOT CAUSE ANALYSIS
Symptom: Timeouts on exports >100K rows, lost tail data
Investigation:
• Query logs show full table scan (no index on created_at)
• Memory profile: Export format loop holds full dataset in memory (3GB for 200K rows)
• Partial data loss: HTTP timeout at 60 seconds mid-export
PRIMARY ISSUE: Synchronous streaming without chunking
FIXED ISSUES
1. INDEXING: Add index on (user_id, created_at) for query speedup
→ Query time: 12s → 800ms for 1M-row scan
2. STREAMING: Replace in-memory buffer with chunked streaming
Old: Load 200K rows in memory → format → stream
New: Stream 10K row chunks → format → flush → repeat
→ Memory: 3GB → 150MB (99.7percent reduction)
3. TIMEOUT SAFETY: Increase HTTP timeout from 60s → 300s + heartbeat keepalive
→ Prevents connection drop mid-export
4. PARTIAL DATA: Add row counter + checksums to final export
→ Validates completeness before sending
TEST COVERAGE ADDED
✓ Export 10K rows (baseline)
✓ Export 100K rows (threshold)
✓ Export 500K rows (stress test)
✓ Simulate network timeout at 50percent export → should retry and resume
✓ Verify exported CSV matches source row count exactly
DEPLOYMENT PLAN
1. Add index (no downtime)
2. Deploy streaming code (feature flag: export_v2_streaming)
3. Canary: 10percent users on new export path
4. Monitor error rates, latency, completion rate
5. Ramp to 100percent over 48 hours
6. Cleanup: Remove old export code
VALIDATION METRICS
Before: 8percent timeout rate on 100K+ exports
After: <0.1percent timeout rate, 100percent data completeness
About this skill
name: focused-fix description: Use when Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end.
Focused Fix
Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end. Triggers: 'make X work', 'fix the Y feature', 'the Z module is broken', 'focus on [area]'. Not for quick single-bug fixes — this is for systematic deep-dive repair across all files and dependencies.
What you get
- Public GitHub repo (alirezarezvani/claude-skills)
- the focused-fix skill folder with SKILL.md. Part of a 337-skill / 30-agent / 70-command install.
Customize your output
- Fork the repo and adapt the skill's instructions and references to your workflow.
Example output
Activates automatically when your request matches Focused Fix; chains with the other skills, agents, and commands in the collection.
Best for
Creators, builders, and teams using Claude Code.
SKILL.md preview
---
name: focused-fix
description: Systematically debug and repair a specific feature, module, or area end-to-end across all its files and dependencies, rather than patching a single symptom.
version: 1.0.0
category: Development / Engineering
author: AgentVolt
license: proprietary
tags:
- development
- engineering
---
# Focused Fix
Systematically debug and repair a specific feature, module, or area end-to-end across all its files and dependencies, rather than patching a single symptom.
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