{"id":"778731fe-a039-4000-ae36-d47739ff161d","shortId":"dHXJc2","kind":"skill","title":"error-debugging-multi-agent-review","tagline":"Use when working with error debugging multi agent review","description":"# Multi-Agent Code Review Orchestration Tool\n\n## Use this skill when\n\n- Working on multi-agent code review orchestration tool tasks or workflows\n- Needing guidance, best practices, or checklists for multi-agent code review orchestration tool\n\n## Do not use this skill when\n\n- The task is unrelated to multi-agent code review orchestration tool\n- You need a different domain or tool outside this scope\n\n## Instructions\n\n- Clarify goals, constraints, and required inputs.\n- Apply relevant best practices and validate outcomes.\n- Provide actionable steps and verification.\n- If detailed examples are required, open `resources/implementation-playbook.md`.\n\n## Role: Expert Multi-Agent Review Orchestration Specialist\n\nA sophisticated AI-powered code review system designed to provide comprehensive, multi-perspective analysis of software artifacts through intelligent agent coordination and specialized domain expertise.\n\n## Context and Purpose\n\nThe Multi-Agent Review Tool leverages a distributed, specialized agent network to perform holistic code assessments that transcend traditional single-perspective review approaches. By coordinating agents with distinct expertise, we generate a comprehensive evaluation that captures nuanced insights across multiple critical dimensions:\n\n- **Depth**: Specialized agents dive deep into specific domains\n- **Breadth**: Parallel processing enables comprehensive coverage\n- **Intelligence**: Context-aware routing and intelligent synthesis\n- **Adaptability**: Dynamic agent selection based on code characteristics\n\n## Tool Arguments and Configuration\n\n### Input Parameters\n- `$ARGUMENTS`: Target code/project for review\n  - Supports: File paths, Git repositories, code snippets\n  - Handles multiple input formats\n  - Enables context extraction and agent routing\n\n### Agent Types\n1. Code Quality Reviewers\n2. Security Auditors\n3. Architecture Specialists\n4. Performance Analysts\n5. Compliance Validators\n6. Best Practices Experts\n\n## Multi-Agent Coordination Strategy\n\n### 1. Agent Selection and Routing Logic\n- **Dynamic Agent Matching**:\n  - Analyze input characteristics\n  - Select most appropriate agent types\n  - Configure specialized sub-agents dynamically\n- **Expertise Routing**:\n  ```python\n  def route_agents(code_context):\n      agents = []\n      if is_web_application(code_context):\n          agents.extend([\n              \"security-auditor\",\n              \"web-architecture-reviewer\"\n          ])\n      if is_performance_critical(code_context):\n          agents.append(\"performance-analyst\")\n      return agents\n  ```\n\n### 2. Context Management and State Passing\n- **Contextual Intelligence**:\n  - Maintain shared context across agent interactions\n  - Pass refined insights between agents\n  - Support incremental review refinement\n- **Context Propagation Model**:\n  ```python\n  class ReviewContext:\n      def __init__(self, target, metadata):\n          self.target = target\n          self.metadata = metadata\n          self.agent_insights = {}\n\n      def update_insights(self, agent_type, insights):\n          self.agent_insights[agent_type] = insights\n  ```\n\n### 3. Parallel vs Sequential Execution\n- **Hybrid Execution Strategy**:\n  - Parallel execution for independent reviews\n  - Sequential processing for dependent insights\n  - Intelligent timeout and fallback mechanisms\n- **Execution Flow**:\n  ```python\n  def execute_review(review_context):\n      # Parallel independent agents\n      parallel_agents = [\n          \"code-quality-reviewer\",\n          \"security-auditor\"\n      ]\n\n      # Sequential dependent agents\n      sequential_agents = [\n          \"architecture-reviewer\",\n          \"performance-optimizer\"\n      ]\n  ```\n\n### 4. Result Aggregation and Synthesis\n- **Intelligent Consolidation**:\n  - Merge insights from multiple agents\n  - Resolve conflicting recommendations\n  - Generate unified, prioritized report\n- **Synthesis Algorithm**:\n  ```python\n  def synthesize_review_insights(agent_results):\n      consolidated_report = {\n          \"critical_issues\": [],\n          \"important_issues\": [],\n          \"improvement_suggestions\": []\n      }\n      # Intelligent merging logic\n      return consolidated_report\n  ```\n\n### 5. Conflict Resolution Mechanism\n- **Smart Conflict Handling**:\n  - Detect contradictory agent recommendations\n  - Apply weighted scoring\n  - Escalate complex conflicts\n- **Resolution Strategy**:\n  ```python\n  def resolve_conflicts(agent_insights):\n      conflict_resolver = ConflictResolutionEngine()\n      return conflict_resolver.process(agent_insights)\n  ```\n\n### 6. Performance Optimization\n- **Efficiency Techniques**:\n  - Minimal redundant processing\n  - Cached intermediate results\n  - Adaptive agent resource allocation\n- **Optimization Approach**:\n  ```python\n  def optimize_review_process(review_context):\n      return ReviewOptimizer.allocate_resources(review_context)\n  ```\n\n### 7. Quality Validation Framework\n- **Comprehensive Validation**:\n  - Cross-agent result verification\n  - Statistical confidence scoring\n  - Continuous learning and improvement\n- **Validation Process**:\n  ```python\n  def validate_review_quality(review_results):\n      quality_score = QualityScoreCalculator.compute(review_results)\n      return quality_score > QUALITY_THRESHOLD\n  ```\n\n## Example Implementations\n\n### 1. Parallel Code Review Scenario\n```python\nmulti_agent_review(\n    target=\"/path/to/project\",\n    agents=[\n        {\"type\": \"security-auditor\", \"weight\": 0.3},\n        {\"type\": \"architecture-reviewer\", \"weight\": 0.3},\n        {\"type\": \"performance-analyst\", \"weight\": 0.2}\n    ]\n)\n```\n\n### 2. Sequential Workflow\n```python\nsequential_review_workflow = [\n    {\"phase\": \"design-review\", \"agent\": \"architect-reviewer\"},\n    {\"phase\": \"implementation-review\", \"agent\": \"code-quality-reviewer\"},\n    {\"phase\": \"testing-review\", \"agent\": \"test-coverage-analyst\"},\n    {\"phase\": \"deployment-readiness\", \"agent\": \"devops-validator\"}\n]\n```\n\n### 3. Hybrid Orchestration\n```python\nhybrid_review_strategy = {\n    \"parallel_agents\": [\"security\", \"performance\"],\n    \"sequential_agents\": [\"architecture\", \"compliance\"]\n}\n```\n\n## Reference Implementations\n\n1. **Web Application Security Review**\n2. **Microservices Architecture Validation**\n\n## Best Practices and Considerations\n\n- Maintain agent independence\n- Implement robust error handling\n- Use probabilistic routing\n- Support incremental reviews\n- Ensure privacy and security\n\n## Extensibility\n\nThe tool is designed with a plugin-based architecture, allowing easy addition of new agent types and review strategies.\n\n## Invocation\n\nTarget for review: $ARGUMENTS\n\n## Limitations\n- Use this skill only when the task clearly matches the scope described above.\n- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.\n- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.","tags":["error","debugging","multi","agent","review","antigravity","awesome","skills","sickn33","agent-skills","agentic-skills","ai-agent-skills"],"capabilities":["skill","source-sickn33","skill-error-debugging-multi-agent-review","topic-agent-skills","topic-agentic-skills","topic-ai-agent-skills","topic-ai-agents","topic-ai-coding","topic-ai-workflows","topic-antigravity","topic-antigravity-skills","topic-claude-code","topic-claude-code-skills","topic-codex-cli","topic-codex-skills"],"categories":["antigravity-awesome-skills"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/sickn33/antigravity-awesome-skills/error-debugging-multi-agent-review","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"cli":"npx skills add sickn33/antigravity-awesome-skills","source_repo":"https://github.com/sickn33/antigravity-awesome-skills","install_from":"skills.sh"}},"qualityScore":"0.700","qualityRationale":"deterministic score 0.70 from registry signals: · indexed on github topic:agent-skills · 34793 github stars · SKILL.md body (6,913 chars)","verified":false,"liveness":"unknown","lastLivenessCheck":null,"agentReviews":{"count":0,"score_avg":null,"cost_usd_avg":null,"success_rate":null,"latency_p50_ms":null,"narrative_summary":null,"summary_updated_at":null},"enrichmentModel":"deterministic:skill-github:v1","enrichmentVersion":1,"enrichedAt":"2026-04-24T00:50:53.084Z","embedding":null,"createdAt":"2026-04-18T21:36:40.446Z","updatedAt":"2026-04-24T00:50:53.084Z","lastSeenAt":"2026-04-24T00:50:53.084Z","tsv":"'/path/to/project':590 '0.2':609 '0.3':597,603 '1':249,274,580,668 '2':253,332,610,673 '3':256,384,651 '4':259,438 '5':262,480 '6':265,512 '7':541 'across':185,343 'action':96 'adapt':211,523 'addit':711 'agent':5,14,18,31,48,66,111,136,148,155,172,191,213,245,247,271,275,281,289,295,302,305,331,344,350,376,381,417,419,429,431,449,464,489,503,510,524,549,587,591,621,629,638,647,659,663,682,714 'agents.append':326 'agents.extend':312 'aggreg':440 'ai':118 'ai-pow':117 'algorithm':458 'alloc':526 'allow':709 'analysi':130 'analyst':261,329,607,642 'analyz':283 'appli':88,491 'applic':309,670 'approach':169,528 'appropri':288 'architect':623 'architect-review':622 'architectur':257,318,433,600,664,675,708 'architecture-review':432,599 'argument':220,225,723 'artifact':133 'ask':757 'assess':161 'auditor':255,315,426,595 'awar':206 'base':215,707 'best':41,90,266,677 'boundari':765 'breadth':197 'cach':520 'captur':182 'characterist':218,285 'checklist':44 'clarif':759 'clarifi':82 'class':359 'clear':732 'code':19,32,49,67,120,160,217,235,250,303,310,324,421,582,631 'code-quality-review':420,630 'code/project':227 'complex':495 'complianc':263,665 'comprehens':126,179,201,545 'confid':553 'configur':222,291 'conflict':451,481,485,496,502,505 'conflict_resolver.process':509 'conflictresolutionengin':507 'consider':680 'consolid':444,466,478 'constraint':84 'context':142,205,242,304,311,325,333,342,355,414,535,540 'context-awar':204 'contextu':338 'continu':555 'contradictori':488 'coordin':137,171,272 'coverag':202,641 'criteria':768 'critic':187,323,468 'cross':548 'cross-ag':547 'debug':3,12 'deep':193 'def':300,361,372,410,460,500,530,562 'depend':400,428 'deploy':645 'deployment-readi':644 'depth':189 'describ':736 'design':123,619,702 'design-review':618 'detail':101 'detect':487 'devop':649 'devops-valid':648 'differ':74 'dimens':188 'distinct':174 'distribut':153 'dive':192 'domain':75,140,196 'dynam':212,280,296 'easi':710 'effici':515 'enabl':200,241 'ensur':694 'environ':748 'environment-specif':747 'error':2,11,686 'error-debugging-multi-agent-review':1 'escal':494 'evalu':180 'exampl':102,578 'execut':388,390,393,407,411 'expert':108,268,753 'expertis':141,175,297 'extens':698 'extract':243 'fallback':405 'file':231 'flow':408 'format':240 'framework':544 'generat':177,453 'git':233 'goal':83 'guidanc':40 'handl':237,486,687 'holist':159 'hybrid':389,652,655 'implement':579,627,667,684 'implementation-review':626 'import':470 'improv':472,558 'increment':352,692 'independ':395,416,683 'init':362 'input':87,223,239,284,762 'insight':184,348,371,374,378,380,383,401,446,463,504,511 'instruct':81 'intellig':135,203,209,339,402,443,474 'interact':345 'intermedi':521 'invoc':719 'issu':469,471 'learn':556 'leverag':151 'limit':724 'logic':279,476 'maintain':340,681 'manag':334 'match':282,733 'mechan':406,483 'merg':445,475 'metadata':365,369 'microservic':674 'minim':517 'miss':770 'model':357 'multi':4,13,17,30,47,65,110,128,147,270,586 'multi-ag':16,29,46,64,109,146,269 'multi-perspect':127 'multipl':186,238,448 'need':39,72 'network':156 'new':713 'nuanc':183 'open':105 'optim':437,514,527,531 'orchestr':21,34,51,69,113,653 'outcom':94 'output':742 'outsid':78 'parallel':198,385,392,415,418,581,658 'paramet':224 'pass':337,346 'path':232 'perform':158,260,322,328,436,513,606,661 'performance-analyst':327,605 'performance-optim':435 'permiss':763 'perspect':129,167 'phase':617,625,634,643 'plugin':706 'plugin-bas':705 'power':119 'practic':42,91,267,678 'priorit':455 'privaci':695 'probabilist':689 'process':199,398,519,533,560 'propag':356 'provid':95,125 'purpos':144 'python':299,358,409,459,499,529,561,585,613,654 'qualiti':251,422,542,565,568,574,576,632 'qualityscorecalculator.compute':570 'readi':646 'recommend':452,490 'redund':518 'refer':666 'refin':347,354 'relev':89 'report':456,467,479 'repositori':234 'requir':86,104,761 'resolut':482,497 'resolv':450,501,506 'resourc':525,538 'resources/implementation-playbook.md':106 'result':439,465,522,550,567,572 'return':330,477,508,536,573 'review':6,15,20,33,50,68,112,121,149,168,229,252,319,353,396,412,413,423,434,462,532,534,539,564,566,571,583,588,601,615,620,624,628,633,637,656,672,693,717,722,754 'reviewcontext':360 'reviewoptimizer.allocate':537 'robust':685 'role':107 'rout':207,246,278,298,301,690 'safeti':764 'scenario':584 'scope':80,735 'score':493,554,569,575 'secur':254,314,425,594,660,671,697 'security-auditor':313,424,593 'select':214,276,286 'self':363,375 'self.agent':370,379 'self.metadata':368 'self.target':366 'sequenti':387,397,427,430,611,614,662 'share':341 'singl':166 'single-perspect':165 'skill':25,57,727 'skill-error-debugging-multi-agent-review' 'smart':484 'snippet':236 'softwar':132 'sophist':116 'source-sickn33' 'special':139,154,190,292 'specialist':114,258 'specif':195,749 'state':336 'statist':552 'step':97 'stop':755 'strategi':273,391,498,657,718 'sub':294 'sub-ag':293 'substitut':745 'success':767 'suggest':473 'support':230,351,691 'synthes':461 'synthesi':210,442,457 'system':122 'target':226,364,367,589,720 'task':36,60,731 'techniqu':516 'test':636,640,751 'test-coverage-analyst':639 'testing-review':635 'threshold':577 'timeout':403 'tool':22,35,52,70,77,150,219,700 'topic-agent-skills' 'topic-agentic-skills' 'topic-ai-agent-skills' 'topic-ai-agents' 'topic-ai-coding' 'topic-ai-workflows' 'topic-antigravity' 'topic-antigravity-skills' 'topic-claude-code' 'topic-claude-code-skills' 'topic-codex-cli' 'topic-codex-skills' 'tradit':164 'transcend':163 'treat':740 'type':248,290,377,382,592,598,604,715 'unifi':454 'unrel':62 'updat':373 'use':7,23,55,688,725 'valid':93,264,543,546,559,563,650,676,750 'verif':99,551 'vs':386 'web':308,317,669 'web-architecture-review':316 'weight':492,596,602,608 'work':9,27 'workflow':38,612,616","prices":[{"id":"84453c39-452f-4ef4-a230-f0f43f977097","listingId":"778731fe-a039-4000-ae36-d47739ff161d","amountUsd":"0","unit":"free","nativeCurrency":null,"nativeAmount":null,"chain":null,"payTo":null,"paymentMethod":"skill-free","isPrimary":true,"details":{"org":"sickn33","category":"antigravity-awesome-skills","install_from":"skills.sh"},"createdAt":"2026-04-18T21:36:40.446Z"}],"sources":[{"listingId":"778731fe-a039-4000-ae36-d47739ff161d","source":"github","sourceId":"sickn33/antigravity-awesome-skills/error-debugging-multi-agent-review","sourceUrl":"https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/error-debugging-multi-agent-review","isPrimary":false,"firstSeenAt":"2026-04-18T21:36:40.446Z","lastSeenAt":"2026-04-24T00:50:53.084Z"}],"details":{"listingId":"778731fe-a039-4000-ae36-d47739ff161d","quickStartSnippet":null,"exampleRequest":null,"exampleResponse":null,"schema":null,"openapiUrl":null,"agentsTxtUrl":null,"citations":[],"useCases":[],"bestFor":[],"notFor":[],"kindDetails":{"org":"sickn33","slug":"error-debugging-multi-agent-review","github":{"repo":"sickn33/antigravity-awesome-skills","stars":34793,"topics":["agent-skills","agentic-skills","ai-agent-skills","ai-agents","ai-coding","ai-workflows","antigravity","antigravity-skills","claude-code","claude-code-skills","codex-cli","codex-skills","cursor","cursor-skills","developer-tools","gemini-cli","gemini-skills","kiro","mcp","skill-library"],"license":"mit","html_url":"https://github.com/sickn33/antigravity-awesome-skills","pushed_at":"2026-04-24T00:28:59Z","description":"Installable GitHub library of 1,400+ agentic skills for Claude Code, Cursor, Codex CLI, Gemini CLI, Antigravity, and more. Includes installer CLI, bundles, workflows, and official/community skill collections.","skill_md_sha":"4065f7bae38a97eee6fda5d38c7488829d7a47b7","skill_md_path":"skills/error-debugging-multi-agent-review/SKILL.md","default_branch":"main","skill_tree_url":"https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/error-debugging-multi-agent-review"},"layout":"multi","source":"github","category":"antigravity-awesome-skills","frontmatter":{"name":"error-debugging-multi-agent-review","description":"Use when working with error debugging multi agent review"},"skills_sh_url":"https://skills.sh/sickn33/antigravity-awesome-skills/error-debugging-multi-agent-review"},"updatedAt":"2026-04-24T00:50:53.084Z"}}