Debugging · Analysis · Code Fixes Marketplace Agent

Find the bug. Fix the code. Ship the fix.

Analyzes bug reports, traces through your codebase, identifies root cause, and proposes tested fixes—complete with PR ready for review. Engineers review solutions instead of hunting through logs. All on your infrastructure.

67%
Bugs Auto-Resolved
-74%
Resolution Time
94%
Fix Accuracy
🐛
Bug Resolution Agent
Live investigation
● LIVE
BUG-4521 Critical
Payment fails > $10K
Analyzed 847 logs, 12 traces
2m
Root Cause int16 overflow @ validator.ts:142
8m
Fix Generated int16 → int64 + test
12m
PR Ready Awaiting review
now
Resolution 23 min
vs. Manual Avg 4.2 hrs
Time Saved 91%

Bugs pile up. Engineers burn out.

The backlog grows. The team shrinks.

  • Bug reported. Developer opens it. Spends 2 hours reproducing. Another 3 hours tracing through logs. Finds the issue. 10-minute fix. 5 hours of investigation for 10 minutes of coding. Every. Single. Bug.
  • Context switching kills productivity. Engineer is deep in a feature. Bug escalated. Drop everything. Lose context. Fix bug. Try to remember what you were doing. Lose another hour ramping back up.
  • Tribal knowledge gates everything. "Ask Sarah, she knows that module." Sarah's in a meeting. Sarah's on vacation. Sarah quit last month. Now nobody knows why that code exists or how to debug it.
  • Bugs sit in the backlog for weeks. Not critical enough to interrupt sprint work. Critical enough to annoy customers. Technical debt compounds. Small bugs become big bugs become outages.
  • Junior devs spend 80% of time debugging. They're supposed to be learning architecture. Instead, they're grep-ing through logs trying to understand why a test fails intermittently. Not exactly career development.
  • Same bugs keep coming back. Fixed in one place. Broken in another. No one connects the dots. No one has time to look at patterns. Whack-a-mole forever.

"We tracked engineer time for a month. Average bug took 4.2 hours to resolve. Actual coding time: 18 minutes. The rest was reproduction, investigation, log analysis, and context gathering. Our engineers were spending 80% of their bug time on work a machine could do. Meanwhile, the feature backlog kept growing because everyone was stuck debugging."

— VP of Engineering, E-commerce Platform (45 engineers)

AI that debugs. Humans that review.

Deploy an AI that analyzes bug reports, traces through your codebase, identifies root cause, and proposes fixes—complete with tests. Engineers shift from hunting bugs to reviewing solutions.

01

Intelligent Triage

Analyzes bug reports, error messages, and stack traces. Correlates with recent commits, deployments, and similar past issues. Prioritizes by impact and urgency automatically.

02

Root Cause Analysis

Traces execution paths through your code. Analyzes logs, metrics, and state. Identifies the exact line where things go wrong—and explains why. No more grep-ing through logs for hours.

03

Fix Generation

Proposes code fixes with full context. Generates regression tests. Creates PR ready for review. Engineers verify the fix instead of writing it from scratch.

Every bug type. Every codebase.

💥

Runtime Errors

Null pointers, type errors, exceptions. Stack trace analysis and fix generation.

🔄

Logic Bugs

Wrong calculations, incorrect conditions, edge cases. Behavioral analysis and correction.

🐢

Performance Issues

Slow queries, memory leaks, N+1 problems. Profiling analysis and optimization.

🔗

Integration Failures

API mismatches, contract violations, timeout issues. Cross-service debugging.

🧵

Concurrency Bugs

Race conditions, deadlocks, thread safety. Concurrent execution analysis.

🗄️

Data Issues

Schema mismatches, migration problems, data corruption. Database debugging.

🔐

Security Bugs

Injection vulnerabilities, auth bypasses, data exposure. Security-focused fixes.

📱

UI/UX Bugs

Rendering issues, state problems, responsive failures. Frontend debugging.

Real bugs. Fast fixes.

Production Incident

Critical Bug Fixed in 23 Minutes

Payment processing fails for large orders. 12 customers affected. Revenue bleeding. Old process: page on-call, wake up engineer, reproduce issue, dig through logs, find root cause, write fix, test, deploy. 4+ hours minimum.

Agent Action
📥Bug BUG-4521 received • Critical severity
🔍Traced: checkout → payment-validator → stripe
🎯Root cause: int16 overflow at validator.ts:142
🔧Fix: int16 → int64 + regression test
PR #847 created • All tests pass
23 min vs 4.2 hrs manual
→ Engineer reviews, not investigates.
Backlog Reduction

847 Bugs Resolved in One Month

Bug backlog: 1,200 tickets. Growing 50/week. Team fixes 30/week. Net: 20 more bugs every week. Backlog grows forever.

Agent Action
📊Analyzed 1,200 bugs • 71% auto-resolvable
🔄Week 1-4: 847 bugs auto-resolved
🔗Found 23 duplicates • Consolidated
💡Pattern: 34 bugs share same root cause
Single fix resolved all 34
71% backlog cleared
→ Engineers focus on hard problems.
Regression Prevention

Same Bug Never Returns

Fixed the timezone bug in checkout. Two months later, same bug in reporting. Then in email scheduling. No one connects the dots.

Agent Action
🔍Analyzed BUG-4892 • Timezone issue
🔗94% match to 2 previous bugs
📡Codebase scan: 7 more locations found
🛠️Created shared utility + lint rule
9 PRs + systemic prevention
9 fixes pattern eliminated
→ Fix once, fix everywhere.
Junior Developer Productivity

New Hires Productive in Days

New developer joins. Assigned "easy" bug. Spends 3 days understanding the codebase. Asks 47 questions. Senior engineers interrupted constantly.

Agent Action
📋Bug assigned to junior developer
🗺️Provided: flow diagram + root cause
📚Linked: docs + 2 similar past bugs
💡Proposed fix with explanation
Junior reviews, learns, submits PR
2 hrs vs 3 days before
→ Junior learns faster, seniors uninterrupted.

Everything you need for faster debugging.

🔍

Codebase Understanding

Indexes your entire codebase. Understands relationships, dependencies, and data flow. Traces execution paths.

📊

Log Analysis

Parses logs, correlates events, identifies anomalies. Finds the needle in the haystack automatically.

🎯

Root Cause Identification

Traces from symptom to source. Explains why the bug happens, not just where.

Fix Generation

Proposes code changes with context. Follows your coding standards. Ready for review.

🧪

Test Generation

Creates regression tests for every fix. Ensures bugs don't come back. Increases coverage.

🔗

PR Creation

Creates pull requests with full context. Links to issues. Includes analysis summary.

🔄

Pattern Detection

Identifies similar bugs across codebase. Finds systemic issues. Prevents regressions.

📈

Priority Scoring

Ranks bugs by impact, urgency, and fix complexity. Focus on what matters most.

📚

Knowledge Building

Learns from your codebase over time. Builds institutional knowledge that doesn't walk out the door.

Connects with your dev stack.

GitHub
GitLab
Bitbucket
Jira
Linear
Asana
Sentry
Datadog
New Relic
PagerDuty
Slack
VS Code
JetBrains
Splunk
Elasticsearch
CircleCI
Jenkins
GitHub Actions

Know exactly what you're deploying.

A clear charter, defined triggers, and agreed levels of human oversight—structured for enterprise deployment.

Agent Goal

Reduce bug resolution time by automating investigation, root cause analysis, and fix generation

Priority 1
Metrics
67% bugs auto-resolved
74% faster resolution time
94% fix accuracy rate
Input(s) & Output(s)

Inputs – Bug reports, error logs, stack traces, codebase access, commit history, test results

Outputs – Root cause analysis, proposed fixes with tests, pull requests, pattern reports, codebase documentation

Skills, Tools & Capabilities
  • Intelligent bug triage and prioritization
  • Root cause analysis via code tracing
  • Automated fix generation with tests
  • Pull request creation with context
  • Pattern detection across bug history
Decision Authority
Create branches and pull requests
Update bug status and priority
Add comments and documentation
Merge to main (requires approval)
Deploy fixes (requires approval)
Modify security-critical code
Change database schemas
Fallback

Escalate to engineering when: security vulnerabilities detected, database changes required, fix confidence below threshold, multiple modules affected, critical production issues

📋

Full Job Description

Complete specification including repository access policies, PR requirements, and code review rules.

Download .docx

What's Inside the Full Job Description

  • ◈ Agent description & purpose
  • ◈ Regulation & compliance concerns
  • ◈ Example prompt inputs & outputs
  • ◈ Full capabilities list
  • ◈ Risks & guardrails
  • ◈ Permissions & access requirements
  • ◈ Secrets & credentials
  • ◈ Integration specifications

Customize with Weaver

Connect your repositories, configure code style rules, and define which modules require human review.

Your code. Your bugs. Your infrastructure.

🤖

Agent (One-Time)

Pay once. Own the asset. Full source code on Google ADK. Deploy, modify, extend.

🔒

Code Never Leaves

Your source code, bug reports, and analysis stay on your infrastructure. Zero external access.

🛡️

Annual Assurance

New language support, framework updates, and analysis improvements. You own agents; you subscribe to safety.

🔧

Weaver Customization

Configure coding standards, review requirements, and escalation policies for your team.

Stop hunting bugs. Start reviewing fixes.

Deploy the Bug Resolution Agent on your infrastructure. Faster debugging. Smarter fixes. Engineers who build features.

Book a Demo