- Added document start markers (---) to all YAML files
- Fixed line length issues by breaking long lines appropriately
- Removed trailing whitespace throughout all files
- Added proper newlines at end of files
- Fixed truthy value format ('on' -> 'on')
- Standardized YAML formatting across workflows and issue templates
- Used multi-line strings (>) for long descriptions
- Maintained readability while adhering to 80-character line limit
All YAML files now pass yamllint validation with only minor warnings remaining.
Problem Analysis:
- Original workflow used complex GitHub search API causing rate limiting issues
- Custom first-time contributor detection was unreliable and fragile
- Used pull_request instead of pull_request_target for PRs (security issue)
- Complex github-script logic prone to failures
Solution Implemented:
- Replaced custom logic with GitHub's official actions/first-interaction@v1
- Changed to pull_request_target for PR security and reliability
- Eliminated API rate limiting issues by removing search calls
- Simplified permissions and workflow structure
- Added comprehensive welcome messages with community guidelines
Benefits:
- More reliable first-time contributor detection
- No rate limiting issues
- Better security with pull_request_target
- Easier to maintain using official GitHub action
- Consistent messaging across issues and PRs
Also included alternative implementation example using garg3133/welcome-new-contributors@v1.2
- Added Code of Conduct with clear behavioral standards
- Created Contributing guidelines with submission requirements
- Implemented structured issue templates (bug reports, features, new agents, moderation)
- Disabled blank issues to enforce template usage
- Added automated content moderation via GitHub Actions:
* Real-time scanning for hate speech, threats, and profanity
* Automatic closure/locking of critical violations
* Moderation alerts for maintainer review
- Set up welcome system for new contributors with community guidelines
- Enabled GitHub Discussions as alternative to issues for general questions
- Closed and locked existing hate speech issue #30
- Blocked offending user account
This creates a multi-layered defense against inappropriate content while
maintaining an open, welcoming environment for legitimate contributors.
- Added deep configuration change detection and analysis
- Implemented magic number scrutiny for all numeric changes
- Added impact analysis requirements for configuration modifications
- Included real-world outage patterns from 2024 incidents
- Made agent generic (removed framework-specific references)
- Enhanced skepticism for 'just changing numbers' scenarios
- Updated README to reflect new capabilities
Addresses issue #24 - agent now proactively questions configuration changes
that could cause production outages
- Increase total agent count from 48 to 49
- Add typescript-pro to Language Specialists section
- Update Sonnet model agent count from 29 to 30
- Include typescript-pro in model assignments and usage examples
Added 'The prompt needs to be displayed in your response in a single block of text that can be copied and pasted' as previous version was sporadically not displaying the prompt text. The proposed additions seem to improve the frequency of the prompt being displayed in Claude Code.
- Add ios-developer.md: Native iOS development with Swift/SwiftUI
- Add ui-ux-designer.md: Interface design, wireframes, and design systems
- Update README.md: Added both agents to appropriate sections
- Update agent count from 47 to 48 total agents
- Update Sonnet count from 28 to 29 agents (both use sonnet model)
- Add agents to Planning & Architecture and Development sections
- Fixed merge conflict in legal-advisor description
- Updated all model names from full identifiers to simplified names (opus/sonnet/haiku)
- Corrected Sonnet agent count from 26 to 27 (added php-pro)
- Updated section headers to reflect simplified naming
- Updated model configuration documentation to clarify v1.0.64 naming convention
- Updated subagent format example to show simplified model specification
The prompt-engineer agent now explicitly shows the complete prompt text
instead of just describing it. Changes include:
- Added mandatory instruction to always display prompts
- Created required output format with prompt section
- Updated deliverables to prioritize showing the actual prompt
- Added example demonstrating proper output format
- Included completion checklist to ensure prompts are displayed
This ensures users get the actual prompts they can use immediately.
Implements claude-code v1.0.64's model customization feature by adding
model specifications to all 46 subagents based on task complexity:
- Claude Haiku 3.5 (8 agents): Simple tasks like data analysis, documentation
- Claude Sonnet 4 (26 agents): Development, engineering, and standard tasks
- Claude Opus 4 (11 agents): Complex tasks requiring maximum capability
This task-based model tiering ensures cost-effective AI usage while
maintaining quality for complex tasks.
Updates:
- Added model field to YAML frontmatter for all agent files
- Updated README with comprehensive model assignments
- Added model configuration documentation
- Added business-analyst for KPIs, metrics, and growth projections
- Added content-marketer for SEO content and marketing campaigns
- Added sales-automator for cold outreach and proposal automation
- Added customer-support for FAQ, tickets, and support documentation
- Added risk-manager for portfolio risk and hedging strategies
- Added search-specialist for advanced web research and synthesis
Updated README:
- Increased count from 37 to 43 subagents
- Created new Business & Marketing section
- Added usage examples and workflows
- Updated guidance sections
- Added link to Claude Code Commands collection (52 slash commands)
- Highlighted integration between subagents and pre-built workflows
- Added Advanced Workflows section with slash command examples
- Shows how commands leverage subagents for complex orchestrations
- Added mlops-engineer to Data & AI section
- Updated count from 36 to 37 subagents
- Added to usage examples and workflow patterns
- Added to Analysis & Optimization guidance section
- Specializes in ML infrastructure, experiment tracking, model registries, and pipeline automation
- Added database-admin to Infrastructure & Operations section
- Updated count from 35 to 36 subagents
- Added to usage examples and workflow patterns
- Added to Operations & Maintenance guidance section
- Specializes in backups, replication, user management, and disaster recovery
Specializes in log analysis and pattern recognition:
- Log parsing and error extraction with regex patterns
- Stack trace analysis across programming languages
- Error correlation across distributed systems
- Anomaly detection in log streams
- Root cause analysis with actionable findings
- Added error-detective to Quality & Security section
- Updated count from 33 to 34 subagents
- Added to production incident workflow example
- Added to Quality Assurance section
